Seepage Calibration Model and Seepage Testing Data Rev 02, ICN 00 Erratas 001-002

MDL-NBS-HS-000004

April 2003

1. PURPOSE 
The purpose of this Model Report is to document the Seepage Calibration Model (SCM). The 
SCM is developed (1) to establish the conceptual basis for the Seepage Model for Performance 
Assessment (SMPA), and (2) to derive seepage-relevant, model-related parameters and their 
distributions for use in the SMPA and seepage abstraction in support of the Total System 
Performance Assessment for License Application (TSPA-LA). 
The SCM is intended to be used only within this Model Report for the estimation of seepagerelevant 
parameters through calibration of the model against seepage-rate data from liquidrelease 
tests performed in several niches along the Exploratory Studies Facility (ESF) Main Drift 
and in the Cross Drift. The SCM does not predict seepage into waste emplacement drifts under 
thermal or ambient conditions. Seepage predictions for waste emplacement drifts under ambient 
conditions will be performed with the SMPA (see upcoming REV 02 of CRWMS M&O 2000 
[153314]), which inherits the conceptual basis and model-related parameters from the SCM. 
Seepage during the thermal period is examined separately in the Thermal Hydrologic (TH) 
Seepage Model (see BSC 2003 [161530]). 
The scope of this work is (1) to evaluate seepage rates measured during liquid-release experiments 
performed in several niches in the Exploratory Studies Facility (ESF) and in the Cross 
Drift, which was excavated for enhanced characterization of the repository block (ECRB); (2) to 
evaluate air-permeability data measured in boreholes above the niches and the Cross Drift to 
obtain the permeability structure for the seepage model; (3) to use inverse modeling to calibrate 
the SCM and to estimate seepage-relevant, model-related parameters on the drift scale; (4) to 
estimate the epistemic uncertainty of the derived parameters, based on the goodness-of-fit to the 
observed data and the sensitivity of calculated seepage with respect to the parameters of interest; 
(5) to characterize the aleatory uncertainty of the parameters as a result of spatial variability; (6) 
to evaluate prediction uncertainty based on linear uncertainty-propagation analyses and Monte 
Carlo simulations; (7) to validate the SCM during model development, and validate using the 
post-development activities outlined in the Technical Work Plan (TWP, see below); (8) to 
provide the technical basis for the resolution of unconfirmed issues previously labeled to be 
verified (TBV); and (9) to provide the basis for a screening argument for certain seepage-related 
features, events, and processes (FEPs). 
The primary caveats and limitations in the scope of this Model Report and the results from the 
SCM are as follows: 
 The seepage models are intended to provide estimates of the seepage flux averaged 
over a 5 m drift segment (the approximate length of a waste package). The seepage 
models are not expected to quantitatively predict individual seepage events or the 
precise spatial seepage distribution along the drift. 
 By definition, the derived parameters are related to the specific model structure used, 
i.e., these parameters are only applicable to a conceptual and numerical model similar 
to the SCM. (Note that the SCM and the SMPA are compatible in this sense.) The 
parameters are also process specific and scale dependent, i.e., while they can be 
19 April 2003 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
considered optimal for seepage calculations on the drift scale, they are not necessarily 
applicable to other processes on different scales. 
 The effective parameters derived in this Model Report capture many processes and 
features leading to dripping of formation water into a large underground opening. 
However, this does not include water dripping as a result of condensate accumulation 
on the drift surface or other in-drift moisture redistribution processes. 
More detailed discussion of the appropriateness of the modeling approach, the sufficiency of the 
data, and the inherent limitations and caveats can be found throughout this Model Report. 
The technical scope, content, and management of this Model Report are described in the 
planning document Technical Work Plan for: Performance Assessment Unsaturated Zone (BSC 
2002 [160819], Section 1.13). The software programs GSLIB Module GAMV3 V1.201 (LBNL 
2000 [153099]) and EarthVision V4.0 (Dynamic Graphics 2003 [162369]) were used (see Table 
1) but not planned in the TWP. There were no other deviations from the TWP. In Section 4.2, 
criteria for acceptance of this Model Report are identified; no additional criteria were identified 
in the TWP. 
This Model Report revises the Analysis/Model Report (AMR) MDL-NBS-HS-000004 REV 01, 
Seepage Calibration Model and Seepage Testing Data (CRWMS M&O 2001 [153045]) to 
include new seepage data from liquid-release tests performed in the lower lithophysal zone of the 
Topopah Spring welded unit (Tptpll). These new data were collected in Niche 1620 and in 
additional boreholes drilled as part of the systematic testing in the ECRB. Moreover, evaporation 
at the drift surface has now been incorporated into the model to reduce a potential bias on the 
estimated parameters. This model enhancement obliterates the need for making the nonconservative 
evaporation assumption discussed in CRWMS M&O (2001 [153045], Sections 5.6, 7.3, 
7.4, and 7.5). 
No new testing in the middle nonlithophysal zone of the Topopah Spring welded unit (Tptpmn) 
was conducted, and thus no new analyses were performed. The previously obtained results are 
included in this Model Report for completeness. 
This Model Report supports the reports that document the SMPA (see upcoming REV 02 of 
CRWMS M&O 2000 [153314]), seepage abstraction (see upcoming Model Report MDL-NBSHS-
000019 REV 00, which will supersede CRWMS M&O (2001 [154291])), and TSPA-LA. 
This report also addresses the following issues: The development of a collection system in Niche 
1620 for mass balance considerations (see Sections 6.5.3 and 6.8); monitoring and estimation of 
evaporation effects (see Sections 6.3.3.4, 6.5.4, 6.6.1.3, 6.6.1.4, 6.6.2.3, and 6.6.3.3); inclusion of 
film flow effects (see Sections 6.1.2, 6.3.3, 6.3.3.2, 6.3.4, and 6.6.3.1); inclusion of effects from 
small-scale irregularities at the drift surface (see Sections 6.3.3, 6.3.3.2, 6.3.3.3, 6.3.3.5, 6.3.4, 
6.6.2.2, 6.6.3, 6.6.3.3, 8.2, and Attachments IIIV); justification of the continuum approach (see 
Sections 6.3.2, 6.3.3.2, 6.3.4, and 6.4.1); discussion of differences between continuum models 
and discrete fracture network models (see Sections 6.3.2 and 6.4.1); and the use of Niche 1620 
data to improve parameter estimates (see Sections 1, 4.1, 6.5, 6.6.2, 6.6.3, 7.3, 7.4, 8.1, and 8.2). 
April 2003 20 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
2. QUALITY ASSURANCE 
Development of this model report and the supporting modeling activities have been determined 
to be subject to the Yucca Mountain Projects quality assurance (QA) program as indicated in 
Technical Work Plan for: Performance Assessment Unsaturated Zone, TWP-NBS-HS-000003 
REV 02 (BSC 2002 [160819], Section 8.2, Work Package (WP) AUZM09). Approved QA 
procedures identified in the TWP (BSC 2002 [160819], Section 4) have been used to conduct 
and document the activities described in this model report. The TWP also identifies the methods 
used to control the electronic management of data (BSC 2002 [160819], Section 8.4, WP 
AUZM09) during the modeling and documentation activities. 
This model report examines the properties of natural barriers identified in AP-2.22Q, 
Classification Criteria and Maintenance of the Monitored Geologic Repository Q-List as 
Quality Level  1 items important to waste isolation. The report contributes to the analysis and 
modeling data used to support performance assessment (PA). The conclusions of this model 
report do not affect the proposed repository design or engineered features important to safety, as 
defined in AP-2.22Q. 
21 April 2003 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
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April 2003 Seepage Calibration Model and Seepage Testing Data 
Software Name 
given below. 
The use of the software programs identified in Table 1 is documented in Section 6 and in the 
supporting scientific notebooks (SNs). A summary description of the programs and their use is 
The software program iTOUGH2 V4.0 (LBNL 1999 [139918]) provides forward and inverse 
modeling capabilities for unsaturated and multiphase flow in fractured porous media. The 
iTOUGH2 V5.0 (LBNL 2002 [160106]) program hasamong other featuresthe extended 
capability of efficiently simulating evaporation effects (BSC 2002 [161067], Section 1.2). Both 
programs are used in this Model Report for simulating liquid-release experiments and predicting 
seepage rates. Moreover, they solve the inverse problem by automatically calibrating the model 
against measured data, and calculate prediction uncertainties for model validation. 
Reference 
LBNL 1999 [139918] 
LBNL 2002 [160106] 
LBNL 1999 [134136] 
LBNL 2000 [153100] 
LBNL 1999 [134139] 
LBNL 2000 [153099] 
Dynamic Graphics 2003 [162369] 
LBNL 2000 [152814] 
LBNL 2000 [152824] 
LBNL 2000 [152823] 
LBNL 2000 [152826] 
LBNL 2000 [152815] 
LBNL 2000 [152828] 
LBNL 2000 [152816] 
LBNL 2000 [152822] 
CRWMS M&O 1999 [147402] 
LBNL 1999 [134141] 
3. USE OF SOFTWARE 
The software programs used in this study are listed in Table 1. These are appropriate for the 
intended application and were used only within the range of validation. They were obtained from 
Software Configuration Management and qualified under AP-SI.1Q, Software Management. The 
qualification and baseline status of the software programs listed in Table 1 is given in the 
Document Input Reference System (DIRS). 
Table 1. Qualified Software Used in this Report 
Version Software Tracking Number 
1.0 
iTOUGH2 4.0 10003-4.0-00 
iTOUGH2 5.0 10003-5.0-00 
GSLIB Module SISIM 1.203 10001-1.0MSISIMV1.203-00 
GSLIB Module SISIM 1.204 10397-1.0SISIMV1.204-00 
GSLIB Module GAMV2 1.201 10087-1.0MGAMV2V1.201-00 
GSLIB Module GAMV3 1.201 10398-1.0GAMV3V1.201-00 
EarthVision 4.0 10174-4.0-00 
AddCoord 1.0 10355-1.0-00 
MoveMesh 1.0 10358-1.0-00 
AddBound 1.0 10357-1.0-00 
Perm2Mesh 1.0 10359-1.0-00 
CutNiche 1.2 10356-1.2-00 
CutNiche 1.3 10402-1.3-00 
CutDrift 1.0 10375-1.0-00 
AddBorehole 1.0 10373-1.0-00 
ECRB-XYZ .03 30093-V.03 
EXT 10047-1.0-00 
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The GSLIB modules GAMV2 V1.201 and GAMV3 V1.201 (LBNL 1999 [134139]; LBNL 2000 
[153099]) analyze spatial correlation of, respectively, two-dimensional (2D) and three dimensional 
(3D), irregularly spaced datasets. These programs are used for the geostatistical 
analysis of air-permeability data. 
The GSLIB module SISIM V1.203 (LBNL 1999 [134136]) generates 3D, spatially correlated 
random fields by means of sequential indicator simulations. It is used in this Model Report to 
generate spatially correlated fields of log-permeability modifiers. Module SISIM V1.204 (LBNL 
2000 [153100]) is an extended version of SISIM V1.203 (LBNL 1999 [134136]), in which 
coordinates are directly output along with the log-permeability modifiers, making the use of 
software program AddCoord V1.0 (see below; LBNL 2000 [152814]) unnecessary. 
The following utility programs support the generation of computational meshes. The software 
program MoveMesh V1.0 (LBNL 2000 [152824]) adds a constant to the coordinates of a mesh 
file, translating the coordinate system. The software program AddBound V1.0 (LBNL 2000 
[152823]) adds boundary elements to a mesh file. The software program AddCoord V1.0 (LBNL 
2000 [152814]) adds coordinates to the output file of SISIM V1.203 (LBNL 1999 [134136]) in 
preparation for its use by the software program Perm2Mesh V1.0 (LBNL 2000 [152826]), which 
maps a field of log-permeability modifiers onto a mesh file. The visualization software 
EarthVision V4.0 (Dynamic Graphics 2003 [162369]) is used to extract coordinates of the rough 
ceilings of Niches 3107 and 4788 in preparation for the use of the software program CutNiche 
V1.2 (LBNL 2000 [152815]), which cuts a niche with a rough ceiling from a mesh file. The 
software program CutNiche V1.3 (LBNL 2000 [152828]) cuts a smooth niche from a mesh file. 
The software program CutDrift V1.0 (LBNL 2000 [152816]) cuts a cylindrical drift from a mesh 
file. The software program AddBorehole V1.0 (LBNL 2000 [152822]) inserts a borehole into a 
mesh file. The software program ECRB-XYZ V.03 (CRWMS M&O 1999 [147402]) calculates 
the coordinates of a given ECRB station number, so the location of ECRB test beds can be 
related to the coordinates of the computational mesh. 
The software program EXT V1.0 (LBNL 1999 [134141]) takes the forward output file from 
iTOUGH2 (V4.0 or V5.0) and converts it into a Tecplot (all versions, see Table 2) input file; this 
software is used for visualization purposes only. 
Table 2 summarizes the commercial off-the-shelf software used in support of this Model Report. 
This software is exempt from qualification under AP-SI.1Q. Computations performed using the 
standard functions of the software products listed in Table 2 are described in the model 
documentation (Section 6) and the cited attachments. For visualization purposes, certain units 
have been converted using the equation utility of Tecplot. A factor of 1/86,400 was used to 
convert time from seconds to days; a factor of 1/60,000 was used to convert water flow rates 
from milliliter per minute (ml/min) to kilograms per second (kg/s), which implies a water density 
of 1 gram per milliliter (g/ml). All information needed to reproduce the work, including the 
input, formulae or algorithm, and output, is included in this Model Report and the cited 
references. 
April 2003 24 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
Table 2. Software Products Exempt from Qualification under AP-SI.1Q 
Exceed V6.1/V5.3 PC, Windows 98 Communication and file transfer 
between PC and Unix workstation 
Used for 
Data reduction, computation, 
graphical representation of output 
Word processing 
Text editing 
Schematic figures 
Technical figures 
Platform Information 
PC, Windows 98 
2000 (9.0.3821 SR-1) PC, Windows 98 
2000 (9.0.3821 SR-1) PC, Windows 2000 Professional 
2000 (9.0.3821 SR-1) PC, Windows 98 
2000 (9.0.3821 SR-1) PC, Windows 2000 Professional 
vim 6.0.12 PC, Linux 
Adobe Illustrator V8.0.1 Mac, MacOS 9.0.4 
MS PowerPoint 2000 (9.0.3821 SR-1) PC, Windows 98 
Tecplot Sun, SunOS 5.5.1 
8.0-0-6 PC, Windows 98 
7.5 PC, Windows 98 
PC, Windows 2000 Professional 
PC, Windows 2000 Professional 
Version 
97 (SR-2) 
8.0-1-0 
9.0-3-0 
V5.1 (Build 21) 
Software Name 
MS EXCEL 
MS WORD 
F-Secure 
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4. INPUTS 
27 
4.1 DATA AND PARAMETERS 
All input data and parameters needed for the development of the Seepage Calibration Model 
(SCM) are obtained from the Technical Data Management System (TDMS). As stated in 
Section 1, the SCM is used to estimate seepage-relevant parameters through model calibration. 
In general, calibration is a process of fixing certain parameters considered known, relatively 
certain, or insensitive, and adjusting others that are unknown, uncertain, or highly sensitive to 
minimize the misfit between measured data and model output. Input data are measured in or refer 
to the middle nonlithophysal and the lower lithophysal zones of the Topopah Spring welded unit 
(the repository units). Appropriate data for the middle nonlithophysal zone have been measured 
in Niches 3107, 3650, and 4788, and appropriate data for the lower lithophysal zone have been 
measured in Niche 1620 and in boreholes SYBT-ECRB-LA#1#3 drilled into the ceiling of the 
ECRB Cross Drift. Specific input data sets and the associated Data Tracking Numbers (DTNs) 
are listed in Table 3; specific input parameters are listed in Table 4; Technical Product Output 
(TPO) used as input to calculate local percolation fluxes is summarized in Table 5. These data 
and parameters are considered appropriate as input for the development of the SCM for the 
following reasons: 
 Profile alignments and borehole (BH) survey information (Table 3). These survey data 
are considered appropriate as a basis for defining niche geometry and identifying injection 
elements in the numerical mesh. 
 Air-permeability data (Table 3). These data are used as a basis for the geostatistical 
analysis and generation of spatially correlated permeability fields near the niches and 
the ECRB Cross Drift. The data are location-specific and on the appropriate scale, and 
thus suitable for representing the local rock properties and the structure of sub-driftscale 
heterogeneities. 
 Liquid-release test data (Table 3). These data are used for calibration and validation of 
the SCM. Liquid-release test data are appropriate for the calibration of the SCM and 
the estimation of seepage-relevant parameters, because they reflect the salient 
processes and features affecting seepage. Moreover, they are taken on a representative 
scale comparable to that of a waste emplacement drift. 
 Calibrated drift-scale fracture properties for the middle nonlithophysal and lower 
lithophysal zone of the Topopah Spring welded unit. Because they are directly 
measured or derived from data collected at Yucca Mountain, these fracture parameters 
are considered appropriate to be used as reference input parameters. Only the parameters 
that are fixed during an inversion, and for which no location-specific data are 
available, are needed as input; this subset is summarized in Table 4. Because of their 
small sensitivity on predicted seepage rates (see Section 6.6.3.1), a minor change in any 
of these input parameters has a negligible impact on the estimated model parameters or 
the conclusions of this Model Report. 
MDL-NBS-HS-000004 REV02 April 2003 Seepage Calibration Model and Seepage Testing Data 
& 
 Coordinates of the Unsaturated Zone Flow and Transport Model (UZ Model) grid and 
calculated flow rates for extraction of background percolation flux (Table 5). No direct 
observation of percolation flux is available. The percolation fluxes calculated by the 
UZ Model are based on the current understanding of unsaturated flow at Yucca 
Mountain and are thus considered appropriate. 
MO0003GSC00096.000 [152167] ESF Niche 3650 (Niche 2) profile alignment 
MO0002GSC00076.000 [152623] ESF Niche 3650 (Niche 2) borehole as-built information 
MO0003GSC00103.000 [152176] ESF Niche 3107 (Niche 3) profile alignment 
MO0002GSC00064.000 [152625] ESF Niche 3107 (Niche 3) borehole as-built information 
MO0008GSC00273.000 [152626] ESF Niche 4788 (Niche 4) profile alignment 
MO0107GSC01069.000& [156941] ESF Niche 4788 (Niche 4) borehole as-built information 
MO0009GSC00332.000 [155370] ECRB Niche 1620 (Niche 5) profile survey data 
MO0107GSC01061.000 [155369] ECRB Niche 1620 (Niche 5) slot survey data 
MO0209GSC02116.000 [160407] ECRB Niche 1620 (Niche 5) survey data for collars, bottoms, and intervals 
LB0301N5CEILNG.001 
LB0011AIRKTEST.001 [153155] Air permeability data from ESF Niche 3650 (Niche 2) 
LB990601233124.001 
LB0110AKN5POST.001 [156904] Air permeability data from ECRB Niche 1620 (Niche 5) 
LB00090012213U.001 
This DTN superseded MO0008GSC00310.000 [152627], which was the source for borehole coordinates 
available at the time of model development for Niche 4788. Borehole coordinates in both DTNs are identical, i.e., 
there is no impact on the models, analyses, and conclusions presented in this Model Report. 
Data Description 
[161733] ECRB Niche 1620 (Niche 5) detailed niche ceiling roughness data 
Air-Permeability Data 
[105888] Air permeability data from ESF Niches 3107 (Niche 3) and 4788 (Niche 4) 
[153141] Air permeability data from ECRB borehole SYBT-ECRB-LA#2 
Liquid-Release Test Data 
[153144] Liquid-release test data from ESF Niche 3107 (Niche 3), March 1999 
[153145] Liquid-release test data from ESF Niche 4788 (Niche 4), Nov. 1999 
[160408] Liquid-release test data from ECRB Niche 1620 (Niche 5), June 2000 
[160796] Liquid-release test data from ECRB Niche 1620 (Niche 5), June 2002 
[160792] Liquid-release test data from ECRB Niche 1620 (Niche 5), August 2002 
[156879] Liquid-release test data from ECRB borehole SYBT-ECRB-LA#1, Feb. 2001 
[153154] Liquid-release test data from ECRB borehole SYBT-ECRB-LA#2, May 2000 
[160409] Liquid-release test data from ECRB borehole SYBT-ECRB-LA#2, Oct. 2000 
[158462] Liquid-release test data from ECRB borehole SYBT-ECRB-LA#3, May 2001 
DTN 
LB0010NICH3LIQ.001 
LB0010NICH4LIQ.001 
LB0207NICH5LIQ.001 
LB0209NICH5LIQ.001 
LB0211NICH5LIQ.001 
LB0110ECRBLIQR.002 
LB00090012213U.002 
LB0110SYST0015.001 
LB0203ECRBLIQR.001 
Table 3. Input Data 
DIRS # 
Niche Geometry 
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Table 4. Hydrogeologic Input Parameters 
DTN DIRS # Parameter Value Units 
Middle Nonlithophysal Zone of Topopah Spring Welded Unit (Fracture Parameter for tsw34) 
[104055] van Genuchten parameter, m 0.608 [dimensionless] 
0.01 [dimensionless] [104055] Residual liquid saturation, Slr 
1.00 [dimensionless] 
LB997141233129.001 
LB997141233129.001 
LB997141233129.001 [104055] Satiated saturation, Sls 
Lower Lithophysal Zone of Topopah Spring Welded Unit (Fracture Parameters for tsw35) 
[104055] van Genuchten parameter, m 0.611 [dimensionless] 
0.01 [dimensionless] [104055] Residual liquid saturation, Slr 
1.00 [dimensionless] 
LB997141233129.001 
LB997141233129.001 
LB997141233129.001 [104055] Satiated saturation, Sls 
Table 5. Mesh Coordinates and Flow Field Used to Calculate Local Percolation Flux 
DIRS # DTN 
TPO Description 
LB990701233129.001 [106785] 3D UZ model grid, including coordinates 
LB990801233129.003 [122757] Calculated percolation flux, flow field #3 
The collection of the input data used for the development and calibration of the SCM is 
described in detail in BSC (2001 [158463], Sections 6.2 and 6.11) and is summarized in Section 
6.5. The analysis of the seepage-rate data is described in Section 6.6.3. Uncertainties in the input 
data and parameters are addressed throughout Section 6 and are summarized in Section 8.2. 
April 2003 29 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
Requirement Titlea 
Requirements for Multiple 
Barriers 
YMRP Acceptance Criteriab 
Criteria 1 to 4 for Quantity and Chemistry of 
Water Contacting Waste Packages and Waste 
Forms apply to 10 CFR 63.114 (ac). 
Criteria 1 to 3 for System Description and 
Demonstration of Multiple Barriers apply to 10 
CFR 63.115 (a, b) 
4.2 CRITERIA 
The licensing criteria for postclosure performance assessment are stated in 10 CFR 63 [156605]. 
The requirements to be satisfied by TSPA are identified in the Yucca Mountain Project 
Requirements Document (Curry and Loros 2002 [157916]). The acceptance criteria that will be 
used by the Nuclear Regulatory Commission (NRC) to determine whether the technical requirements 
have been met are identified in Yucca Mountain Review Plan, Information Only (YMRP; 
NRC 2003 [162418]). The pertinent requirements and criteria for this model report are summarized 
in Table 6. 
Table 6. Project Requirements and YMRP Acceptance Criteria Applicable to this Model Report 
Requirement 
Numbera 
PRD-002/T-015 Requirements for 
Performance Assessment 
PRD-002/T-016 
a 
b 
10 CFR 63 
Link 
10 CFR 63.114 
[156605] 
10 CFR 63.115 
[156605] 
from Curry and Loros (2002 [157916]) 
from NRC (2003 [162418], Sections 2.2.1.3.3.3 and 2.2.1.1.3) 
The acceptance criteria identified in Section 2.2.1.3.3.3 of the YMRP (NRC 2003 [162418]) are 
given below, followed by a short description of their applicability to this Model Report: 
 Acceptance Criterion 1, System Description and Model Integration are Adequate: 
The physics of the seepage phenomenon is adequately incorporated into an appropriate seepage 
process model based on a sufficient technical basis, supported by field data and sensitivity 
analyses. The approach and model is documented in a transparent and traceable manner. 
 Acceptance Criterion 2, Data are Sufficient for Model Justification: 
Hydrological values used are adequately justified and described. Liquid-release tests were 
designed and conducted with the explicit objective of providing sufficient seepage-relevant 
data for the formulation of the conceptual model and for the calibration and validation of the 
seepage process model. Sufficient seepage-rate data were collected to characterize the 
seepage-related properties of the natural system. 
 Acceptance Criterion 3, Data Uncertainty is Characterized and Propagated Through the 
Model Abstraction 
The parameters used in and derived by the seepage process model are technically defensible; 
they are based on and consistent with available data from Yucca Mountain; uncertainties and 
variabilities are evaluated and reasonably accounted for and adequately represented. 
April 2003 30 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
 Acceptance Criterion 4, Model Uncertainty is Characterized and Propagated Through the 
Model Abstraction: 
The selected modeling approach is consistent with available data and current scientific 
understanding; alternative modeling approaches to the seepage process model are discussed. 
The acceptance criteria identified in Section 2.2.1.1.3 of the YMRP (NRC 2003 [162418]) are 
given below, followed by a short description of their applicability to this Model Report: 
 Acceptance Criterion 1, Identification of Barriers is Adequate: 
Barriers are adequately identified and linked to their capability. 
 Acceptance Criterion 2, Description of Barrier Capability to Isolate Waste Is Acceptable: 
The capability of the barrier to prevent or substantially reduce the rate of movement of water 
is consistent with the definition of a barrier at 10 CFR 63.2, and is adequately identified and 
described, including the uncertainty associated with the barriers capability. 
 Acceptance Criterion 3, Technical Basis for Barrier Capability is Adequately Presented: 
The technical basis for assertions of barrier capability is commensurate with the importance 
of the barriers capability and the associated uncertainties. 
April 2003 31 
4.3 CODES AND STANDARDS 
No specific, formally established standards have been identified as applying to this modeling 
activity. 
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5. ASSUMPTIONS 
This section contains a list of assumptions used for the development of the Seepage Calibration 
Model (SCM). Each statement of an assumption is immediately followed by the rationale for 
why the assumption is considered valid or reasonable. Assumptions in immediately preceding 
upstream documentations have no significant impact on the results of the present model or they 
are discussed in the following subsections. 
5.1 FRACTURE POROSITY 
Assumption: Fracture porosity is assumed to be approximately 1%. 
Rationale: A fracture-porosity estimate for the lower lithophysal zone of 0.96% is provided in 
DTN: LB0205REVUZPRP.001 [159525]. As demonstrated in Section 6.6.3.1, fracture porosity 
has a negligible impact on late-time, near-steady seepage rates and has thus a negligible impact 
on the estimated parameters. Therefore, no further confirmation is required for this assumption. 
The assumption is used for the seepage models of the lower lithophysal zone, discussed throughout 
Sections 6 and 7. 
5.2 INFORMATION ABOUT BOREHOLE SYBT-ECRB-LA#1 
Assumption: Borehole SYBT-ECRB-LA#1 is upward-inclined at nominal angle of 15 from 
the drift axis. Packers are set to isolate an injection zone between 3.0 m and 4.9 m (zone 2) from 
the collar (BSC 2001 [158463], p. 241). 
Rationale: The borehole inclination and interval location information is taken from a reliable and 
controlled source. A potential deviation between the nominal and as-built drilling inclination or 
packer location is expected to be minor and would have no significant impact on the estimated 
parameters or conclusions presented in this Model Report. This assumption, used in Section 
6.6.2.2 and Table III-1, does not require further confirmation. 
33 MDL-NBS-HS-000004 REV02 April 2003 Seepage Calibration Model and Seepage Testing Data 
MDL-NBS-HS-000004 REV02 
INTENTIONALLY LEFT BLANK 
34 
U0080 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
6. DISCUSSION OF SEEPAGE CALIBRATION MODEL 
6.1.1 Objectives 
The following sections describe the development, calibration, and validation of the Seepage 
Calibration Model (SCM). The purpose of the SCM is to provide a methodological and conceptual 
basis for the subsequent development of the Seepage Model for Performance Assessment 
(SMPA). Furthermore, seepage-relevant parameters are derived as input to the abstraction for 
drift seepage. 
The seepage models are not expected to accurately predict individual seepage events or the 
precise spatial distribution along the drift. Instead, the seepage models are intended to provide 
estimates of the seepage flux averaged over a 5 m drift segment (the approximate length of a 
waste package) as a function of the percolation flux on the drift scale. The seepage experiments 
and modeling approach are designed to address seepage on this specific scale. 
6.1 MODELING OBJECTIVES AND DEFINITIONS 
35 
6.1.2 Definitions 
Seepage is defined as flow of liquid water into an underground opening such as a niche, the 
ECRB Cross Drift, or a waste emplacement drift; the water originates from the rock mass and 
forms drops that subsequently detach from the opening surface. According to this definition, 
seepage does not include advective or diffusive vapor flow into the opening or condensation of 
water vapor on surfaces, which may lead to drop formation and drop detachment. Some of the 
water entering an underground opening may also evaporate or flow along the wall, thus not 
contributing to seepage in the narrow sense defined here. Note, however, that evaporation, 
condensation, and film flow along the surface of the opening affect the moisture conditions in the 
waste emplacement drift and may thus impact repository performance. 
Seepage rate is the amount of water seeping into the opening per unit of time. 
Seepage flux is defined as the seepage rate per unit of projected drift wall area. 
Seepage percentage is defined as the ratio of seepage flux divided by percolation flux. As 
outlined in Section 6.1.1, a five-meter long drift section (the approximate length of a waste 
package) is used as the reference scale for calculating percolation and seepage fluxes. In the 
context of liquid-release tests, seepage percentage is the ratio of the rate or amount of water that 
seeped into the niche divided by the rate or amount of water released. 
Seepage threshold is defined here as the critical percolation flux below which no seepage occurs, 
i.e., all percolating water is diverted around the opening, evaporates, or flows along the drift 
surface as a thin water film. Note that Philip et al. (1989 [105743]) did not consider evaporation 
and film-flow effects when defining the critical seepage conditions. 
Seepage fraction is defined as the fraction of waste packages affected by seepage. This is 
equivalent to the fraction of 5 m drift sections that exhibit a nonzero seepage percentage. 
MDL-NBS-HS-000004 REV02 April 2003 Seepage Calibration Model and Seepage Testing Data 
Table 7. Scientific Notebooks 
Relevant Pages 
6.1.3 Scientific Notebooks 
The scientific notebooks (SN) listed in Table 7 provide details potentially needed to reproduce 
the modeling work discussed in this Model Report. 
LBNL Scientific Notebook ID 
M&O Scientific 
Notebook ID 
SN-LBNL-SCI-180-V1 46, 810, 13, 1558 
SN-LBNL-SCI-143-V1 124 
SN-LBNL-SCI-175-V1 2729 
YMP-LBNL-SAF-1 SN-LBNL-SCI-087-V1 14, 100102, 139 
YMP-LBNL-SAF-2 SN-LBNL-SCI-171-V1 12, 3442, 4795 
YMP-LBNL-SAF-3 SN-LBNL-SCI-228-V1 126, 3137 
YMP-LBNL-SAF-TG-1 SN-LBNL-SCI-223-V1 944 
YMP-LBNL-RCT-DSM-1 SN-LBNL-SCI-157-V1 137 
YMP-LBNL-RCT-2 SN-LBNL-SCI-156-V1 3545 
YMP-LBNL-JSW-6C SN-LBNL-SCI-122-V1 108123 
YMP-LBNL-DSM-CFA-1 
YMP-LBNL-YSW-JH-2 
YMP-LBNL-RCT-RH-1 
Summary Description 
Excavation effects are taken into account through the use 
of post-excavation air-permeability data and the estimation 
of a capillary-strength parameter determined from 
seepage data that reflect seepage from an excavationdisturbed 
zone around a large opening (niche or drift). 
6.2 FEATURES, EVENTS, AND PROCESSES 
Table 8 contains a list of Features, Events, and Processes (FEPs) taken from the LA FEP List 
(DTN: MO0301SEPFEPS1.000 [161496]). The LA FEP List is a revision to the previous project 
FEP list (Freeze et al. 2001 [154365]) used to develop the list of included FEPs in the Technical 
Work Plan for: Performance Assessment Unsaturated Zone (BSC 2002 [160819], Table 2-6). 
The selected FEPs are those taken from the LA FEP List that are associated with the subject 
matter of this report, regardless of the anticipated status for exclusion or inclusion in TSPA-LA 
as represented in BSC (2002 [160819], Table 2-6). The results of this model are part of the basis 
for the treatment of FEPs as discussed in the Total System Performance Assessment-License 
Application Methods and Approach (BSC 2002 [160146], Section 3.2.2). The cross-reference for 
each FEP to the relevant sections of this report is also given in Table 8. 
Table 8. FEPs Addressed in this Model Report 
FEP No. 
1.1.02.00.0B 
Section 
Where FEP 
is Addressed 
6.3.3.2, 6.3.4, 
6.5.2, 6.6.3.1, 
6.6.3.3 
36 
FEP Name 
Mechanical effects of 
excavation/ construction 
in EBS 
MDL-NBS-HS-000004 REV02 
U0080 
Citation 
Finsterle 1999 [153448] 
Finsterle 2002 [161043] 
Wang 2003 [161456] 
Wang 2003 [161456] 
Trautz 2001 [161044] 
Trautz 2001 [156903] 
Wang 1999 [153449] 
Ahlers 2002 [161045] 
Hinds 2001 [155955] 
Hedegaard 2002 [161046] 
April 2003 Seepage Calibration Model and Seepage Testing Data 
1.2.02.01.0A Fractures 
the repository 
2.1.08.02.0A Enhanced influx at 6.3.1, 6.3.2, 
6.3.3, 6.6, 6.8 
2.2.01.01.0A Mechanical effects of 
excavation/ construction 
in the near field 
2.2.03.02.0A Rock properties of 4.1, 6.5.2, 8.2 Location-specific rock properties are (1) taken from UZ 
host rock and other 
units 
2.2.07.02.0A Unsaturated groundwater 
flow in the 
geosphere 
2.2.07.04.0A Focusing of unsaturated 
flow (fingers, 
weeps) 
2.2.07.08.0A Fracture flow in the 
UZ 
2.2.07.09.0A Matrix imbibition in 
the UZ 
2.2.07.18.0A Film flow into the 
repository 
2.2.07.20.0A 
repository drifts 
Flow diversion around 6.3.1, 6.3.2, 
6.3.3, 6.6, 6.8 
MDL-NBS-HS-000004 REV02 
6.3.2, 6.3.3.2, Fracture properties are determined from post-excavation 
6.3.4, 6.5.2, 
6.6.3.1, 
6.6.3.3 
6.3.3.2, 6.3.4, 
6.5.2, 6.6.3.1, 
6.6.3.3 
6.3.2, 6.6.1.1 Unsaturated flow processes are accounted for in the 
conceptual and mathematical model. 
6.3.1, 6.3.3.1, 
6.6.2.1, 
6.6.3.3 
6.3.2, 6.3.3.2, 
6.6.2.1 
6.3.3.2 
6.1.2, 6.3.2, 
6.3.3.2, 6.3.4, 
6.6.3.1 
U0080 
air-permeability data and through estimation of seepagerelevant 
fracture continuum capillary-strength parameter 
The impact of an underground opening on the unsaturated 
flow field (including dry-out from evaporation, capillarybarrier 
effect, and flow diversion around the drift) is 
captured in the seepage process model by solving the 
equations governing unsaturated flow in fractured porous 
media and by specifying appropriate boundary conditions 
at the drift wall. It leads to reduced (not enhanced) influx. 
Excavation effects are taken into account through the use 
of post-excavation air-permeability data and the estimation 
of a capillary-strength parameter determined from 
seepage data that reflect seepage from an excavationdisturbed 
zone around a large opening (niche or drift). 
Model, (2) determined from local air-permeability data 
(including measures of heterogeneity and spatial correlation), 
and (3) determined through inverse modeling. 
Variability is accounted for on various scales. 
Explicitly modeled heterogeneity induces flow focusing. 
Impact of small-scale flow focusing effects on seepage 
are included in effective parameter. 
Liquid flow through unsaturated fractures is simulated 
using site-specific fracture properties; explicit inclusion of 
heterogeneity leads to flow channeling. 
Matrix imbibition is considered small under near-steady 
seepage conditions and is therefore neglected. 
If water originating from film flow seeps into the opening 
during a liquid-release test, it is reflected in the corresponding 
seepage data point used for model calibration, 
i.e., film flow is automatically accounted for in the 
estimated seepage-related parameter and thus in the 
prediction of seepage into waste emplacement drifts. 
The impact of an underground opening on the unsaturated 
flow field (including dry-out from evaporation, capillarybarrier 
effect, and flow diversion around the drift) is 
captured in the seepage process model by solving the 
equations governing unsaturated flow in fractured porous 
media and by specifying appropriate boundary conditions 
at the drift wall. Drift shadow is simulated as a result of 
seepage exclusion. 
April 2003 37 U0080 Seepage Calibration Model and Seepage Testing Data 
6.3 BASE-CASE CONCEPTUAL MODEL 
38 
6.3.1 Seepage Phenomena and Processes 
To understand the seepage process and to identify the factors affecting seepage, a description is 
given of the fate of water percolating through the unsaturated zone of Yucca Mountain, eventually 
encountering the immediate vicinity of a waste emplacement drift. This description is based 
on and consistent with the related discussion found in the scientific literature (see, for example, 
Philip et al. (1989 [105743]) and Finsterle (2000 [151875]) and references therein). 
Water that penetrates the ground surface and reaches a depth that is unaffected by evapotranspiration 
starts to percolate downwards, driven by gravity and capillary forces. The detailed flow 
path is determined by the degree of fracturing, fracture geometry, orientation, and connectivity, 
as well as the hydrogeologic properties of the fractures and the matrix. Depending on these 
factors, the water phase in the unsaturated fracture network will either disperse or focus along the 
flow path. Tilted contacts between hydrogeologic units (especially between welded and 
nonwelded tuffs) may affect the overall flow pattern or lead to a change in the frequency and 
spacing of flow channels. However, the channeling process is likely to diminish with depth. As 
flow concentration continues to occur, the distance between the individual channels carrying 
focused flow increases, so the likelihood of two channels meeting and merging decreases with 
depth. Flow focusing and dispersion of flow paths also happens within a rough-walled fracture, 
where asperity contacts and locally larger fracture openings lead to small-scale redistribution of 
water within the fracture. A general discussion of channeling effects under unsaturated flow 
conditions can be found in Birkholzer and Tsang (1997 [119397]). Flow focusing is important 
for seepage, because seepage depends on the local rather than average percolation flux. 
As water approaches the potential waste emplacement drift (one to several meters above the drift 
ceiling), conditions change in several ways, all affecting the amount of water that will eventually 
seep into the opening. The water may first encounter a dry-out zone caused by drift ventilation. 
The dry-out zone may also develop as a result of increased temperatures, in which case it is 
referred to as a boiling zone. Under these thermal conditions, the dry-out zone may be 
surrounded by a two-phase zone in which heat-pipe effects determine water, vapor, and heat 
fluxes, and a condensation zone with increased saturation. (Note that ventilation and elevated 
temperatures are limited in time and thus do not affect long-term seepage.) 
In addition, formation properties around the openings are likely to be altered as a result of stress 
redistribution during drift excavation, which leads to local opening or partial closing of fractures 
and potentially the creation of new fractures. Thermal expansion of the rock matrix may also 
induce changes in apertures. Finally, the local chemical environment, which is altered by evaporation 
and thermal effects, may lead to dissolution and precipitation of minerals, again affecting 
porosity, permeability, and capillarity of the fracture system as well as fracture-matrix interaction. 
Again, such thermally and geochemically induced alterations were of no significance during 
the ambient liquid-release tests analyzed by the SCM. In general, however, all the conditions 
discussed above lead to a flow pattern in the vicinity of a waste emplacement drift different from 
that in the undisturbed formation under ambient conditions. 
MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
Provided that liquid water penetrates the boiling or dry-out zone (for details, see BSC (2003 
[161530])), it reaches the immediate vicinity of the drift wall, where (at least under ambient 
conditions) a boundary layer of increased saturation is expected to develop as a result of the 
capillary barrier effect (Philip et al. 1989 [105743]). The water is prevented from seeping into 
the drift because of capillary suction, which retains the wetting fluid in the pore space. This 
barrier effect leads to a local saturation build-up and the development of a boundary layer in the 
formation immediately adjacent to the drift. If permeability and capillarity of the fracture 
network within this boundary layer are sufficiently high, all or a portion of the water is diverted 
around the drift under partially saturated conditions. Locally, however, the water potential in the 
formation may be higher than that in the drift, and water exits the formation. At the drift surface, 
the water either evaporates, or follows the inclined, rough wall in a thin film, or forms a drop that 
grows and eventually detaches (Or and Ghezzehei 2000 [144773]). Only this last mechanism is 
considered drift seepage according to the definition of Section 6.1.2. 
To summarize, the rate of water dripping into an opening in an unsaturated geologic formation is 
expected to be less than the downward percolation rate because (1) the cavity acts as a capillary 
barrier, (2) water may flow along the drift surface without dripping into the opening, and (3) 
water may evaporate. Even if the seepage threshold were exceeded and seepage occurred, the 
seepage flux would be lower than the percolation flux. 
Section 6.3.2 describes the rationale and justification for using a heterogeneous continuum model 
for the simulation of drift seepage. Section 6.3.3 discusses specific factors and properties affecting 
seepage during liquid-release tests and how they are incorporated into the conceptual model. 
6.3.2 Continuum Approach 
The Seepage Calibration Model is conceptualized as a heterogeneous continuum model. The 
continuum approach can be considered appropriate for seepage studies if it is capable of 
predicting seepage rates for a drift in a fractured formation. 
Water flow through the TSw and seepage into openings at Yucca Mountain occurs predominantly 
through the fracture network, suggesting that a discrete fracture network model is more 
appropriate than a fracture continuum model for the reproduction and prediction of drift seepage. 
However, it is important to recognize that flow diversion around the opening occurs primarily 
within the fracture plane (in-plane diversion). The need to engage multiple fractures arises only if 
the fracture is too short and the flow path within the fracture plane is interrupted. In this case, 
water is diverted into the next connected fracture. This fracture is again unlikely to be perfectly 
parallel to the drift axis, allowing the in-plane flow-diversion process to continue. The situation 
is schematically illustrated in Figure 1, which shows two fractures intersected by a drift. In 
Figure 1a, the two fractures are aligned with the drift axis (which is an implicit assumption made 
in all two-dimensional fracture network models used to predict drift seepage). As an artifact of 
this specific and unrealistic fracture orientation, in-plane flow diversion is prevented, and the 
resulting impact of discreteness on seepage is exaggerated. Two-dimensional fracture network 
models (including those shown by Finsterle (2000 [151875], Plate 1) and Liu et al. (2002 
[160230], Figures 16)) represent extreme cases that may not be representative of and appropriate 
for site-specific seepage modeling. (The advantages and disadvantages of the discrete 
fracture network model are further discussed in Section 6.4.1). 
MDL-NBS-HS-000004 REV02 April 2003 39 U0080 Seepage Calibration Model and Seepage Testing Data 
In Figure 1b, the fractures are approximately perpendicular to the drift axis. Flow diversion 
occurs within the fracture plane, a process that is appropriately captured by a heterogeneous 
fracture continuum model even for a single fracture. In-plane flow occurring in multiple fractures 
can be readily combined and described by an effective fracture continuum. 
(a) (b) 
Figure 1. Schematic showing two fractures intersecting a drift: (a) a two-dimensional fracture 
network model assumes that all fractures are parallel to the drift axis, preventing flow 
diversion within the fracture plane; (b) a 2D (and 3D) fracture continuum model considers 
flow diversion occurring within multiple fracture planes that are approximately perpendicular 
to the drift axis. 
Given the significance of in-plane flow diversion around the drift in combination with relatively 
high fracture density of variable orientation (Mongano et al. 1999 [149850], pp. 6572, 7679), a 
three-dimensional, heterogeneous fracture continuum model is an appropriate conceptualization. 
It captures the relevant processes more realistically than, for example, a two-dimensional discrete 
fracture network model. 
In addition, the appropriateness of the continuum approach to simulate flow through fractured 
rock was studied by Jackson et al. (2000 [141523]) using synthetic and actual field data. They 
concluded that heterogeneous continuum representations of fractured media are self-consistent, 
i.e., appropriately estimated effective continuum parameters are able to represent the underlying 
fracture-network characteristics. 
Finsterle (2000 [151875]) demonstrated that seepage into underground openings excavated from 
a fractured formation could be simulated using a model based on the continuum concept, 
provided that the model is calibrated against seepage-relevant data (such as data from liquidrelease 
tests). Synthetically generated data from a model that exhibits discrete flow and seepage 
behavior were used to calibrate a simplified fracture continuum model. The calibrated continuum 
model was used to predict average seepage rates into a sufficiently large section of an under- 
April 2003 40 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
ground opening for low percolation fluxes, i.e., conditions significantly different from those 
encountered during calibration. The extrapolation from high-rate liquid-release tests to low-rate 
percolation fluxes is equivalent to the extrapolation from the calibration runs performed with the 
SCM to the predictive simulations that will be performed by the SMPA. As discussed in 
Finsterle (2000 [151875]), the extrapolated seepage predictions performed with the continuum 
model were consistent with the synthetically generated data from the discrete-feature model 
under low percolation conditions. This demonstrates that (1) the calibrated continuum model and 
discrete-feature model yield consistent estimates of average seepage rates, and (2) that the 
continuum approach is appropriate for performing seepage predictions even if extrapolated to 
percolation fluxes that are significantly lower than those induced by liquid-release tests, which 
were performed at relatively high injection rates to generate seepage data useable for model 
calibration. Note that the discrete-feature model used in the study makes the extreme assumption 
that all fractures are oriented parallel to the drift axis, as discussed above and illustrated in Figure 
1a. Even under these unfavorable conditions, the continuum approach proved to be appropriate. 
Note that the fracture density and hydraulic parameters used by Liu et al. (2002 [160230]; see 
also Figure 3a below) result in very little flow diversion around the opening. This is a direct 
result of the unrealistic assumption that all fractures are parallel to the drift axis, which prevents 
in-plane flow diversion. In such a two-dimensional discrete fracture network model, flow diversion 
occurs only if the fracture density and/or the capillary-strength parameter are high. This was 
recognized by Liu et al. (2002 [160230], p. 15-8), who concluded that fracture network models 
need to be three-dimensional for them to be able to realistically evaluate the capillary barrier 
effects in fractured formations. As discussed above, in-plane flow diversion in a threedimensional 
fracture network can be appropriately represented by a heterogeneous continuum 
model. A calibrated continuum model is appropriate even in the extreme case where all fractures 
are perfectly parallel to the drift axis, as demonstrated by Finsterle (2000 [151875]) and 
discussed in the previous paragraph. Note that the synthetic fracture network and hydraulic 
parameters used in the discrete model of Finsterle (2000 [151875]; see also Figure 2a below) 
induced some flow diversion. This difference in flow diversion capability between the models of 
Finsterle (2000 [151875]) and Liu et al. (2002 [160230]) is caused by their respective parameter 
choices. This difference, however, does not affect the finding that the continuum approach 
captures the seepage-relevant processes more appropriately than two-dimensional discrete 
fracture network models. The advantages and disadvantages of the discrete fracture network 
model are further discussed in Section 6.4.1. 
The continuum approach is considered appropriate for seepage studies if applied within the 
framework described in this Model Report. Inverse modeling should be used for the estimation 
of process-specific, model-related, and scale-dependent parameters, and the same or similar 
conceptual model should be used for the subsequent seepage predictions, specifically the SMPA. 
Adopting the continuum approach, water flow under unsaturated conditions is governed by 
Richards equation (Richards 1931 [104252]), which states that isothermal flow of water in a 
porous medium or rough-walled fracture occurs under the combined effect of gravitational and 
capillary forces, that flow resistance is a function of saturation, and that (for the purposes of this 
representation) movement of the nonwetting air phase can be neglected. This general concept is 
believed reasonable, because gravitational force is ubiquitous, and rough-walled or partially 
filled fractures exert varying degrees of capillary pressure at different saturation levels. 
April 2003 41 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
Relative permeability and capillary pressure are described as continuous functions of effective 
liquid saturation, following the expressions given by the van Genuchten-Mualem model (van 
Genuchten 1980 [100610], pp. 892893) as implemented in the iTOUGH2 code (BSC 2002 
[161066], Section 4.3.2). The applicability of relative permeability and capillary pressure 
functions is appropriate also for fractures that are rough-walled and/or partially filled with 
porous material. The constant of proportionalityrelative permeabilityis saturation-dependent 
because porous-medium continuum laws also apply to water flow through fractures filled with 
porous material, and in the absence of fracture fillings, the thickness of the water film and 
connectivity of liquid islands on the fracture surface are saturation dependent (Tokunaga and 
Wan 1997 [139195]). 
Capillary strength (represented by the  1 parameter) and permeability are considered uncorrelated. 
The functional relationship describing the potential correlation between permeability and 
capillary strength is unknown. An increase in the effective (continuum) permeability of a fracture 
block may be attributed to larger fracture apertures (which would reduce capillary strength) or to 
an increase in fracture density (which would not affect capillary strength). The capillary-strength 
parameter  1 is taken to be constant for a given test bed, and will be subjected to estimation by 
inverse modeling. 
The van Genuchten-Mualem model is the basic model used in the suite of UZ models (CRWMS 
M&O 2000 [141187], Sections 5 and 6.4.4); it is chosen in this work to ensure consistency. The 
mountain-scale models may use a modified version of the van Genuchten-Mualem functions to 
account for the fact that unsaturated flow is restricted to a limited number of (active) fractures 
and that flow within a fracture is likely to be channelized. Both effects lead to different effective 
saturations determining capillary pressure and relative permeability, and they reduce fracturematrix 
interaction. This revised model was developed by Liu et al. (1998 [105729]) and is 
referred to as the Active Fracture Model (AFM). For drift-scale seepage models under ambient 
conditions, the standard van Genuchten-Mualem model is employed rather than the AFM, 
because (1) flow segregation into active and inactive portions of the fracture network is a largescale 
effect not engaged during the short-distance liquid-release tests; (2) flow channeling within 
fractures is partially accounted for through explicit modeling of small-scale heterogeneity; (3) 
the correction of the fracture-matrix interface area (the main effect captured by the AFM) is 
insignificant for seepage because of insignificant matrix imbibition during the calibration period 
(see Section 6.3.3.2); and (4) the potential impact of all AFM effects on seepage are automatically 
reflected in the observed seepage-rate data, which are used to estimate an effective 
capillary-strength parameter suitable for simulations with a conceptually consistent seepageprediction 
model. 
This general model conceptualization is consistent with that of the UZ Model (CRWMS M&O 
2000 [141187], Section 5 and 6.4.2). The calibration process and the consistent conceptualization 
in the downstream models (specifically the SMPA) make this a valid and reasonable approach. 
6.3.3 Factors and Properties Affecting Seepage During Liquid-Release Tests 
Seepage is a process that occurs at the interface between the natural and engineered systems. 
Consequently, seepage is not only affected by hydrogeological factors (such as formation 
properties and flow conditions in the natural environment), but also by the engineered system 
42 MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
itself. This second set of factors affecting the amount and distribution of seepage includes the 
design of the repository and waste emplacement drifts (location and geometry), the method of 
construction (excavation effects, drift surface roughness, ground support, backfill), and the 
conditions within the drifts (heat load and ventilation, which determine the relative humidity, 
evaporation potential, and the extent of the dry-out zone). 
The engineered barriers in the waste emplacement drift will be exposed to seeping water if (1) a 
flow channel exists that carries water through the (potentially dry) zone around the drift, (2) the 
local percolation flux in this flow channel is high enough to overcome the local seepage threshold, 
and (3) the water droplets forming at the drift wall do not evaporate or dissipate in a thin 
film flowing along the surface. 
The following subsections describe in more detail the key factors affecting drift seepage and how 
they are included in the base-case conceptual model. 
The most important factors are the magnitude of the local percolation flux in relation to the 
formations permeability, the strength of the capillary forces in the fractures, the connectivity of 
the fracture network in the boundary layer, the local topography of the rough drift wall, and the 
thermodynamic conditions in the drift. 
6.3.3.1 Percolation Flux 
General Description 
The magnitude of the percolation flux is a key factor determining seepage. Seepage is initiated if 
the local percolation fluxes in individual flow channels and their accumulation near the drift 
ceiling exceeds the diversion capacity of the capillary barrier (which is caused by the presence of 
the drift), the evaporation potential of the atmosphere in the drift, and the capacity of thin films 
to carry water along the drift surface. Because it is the local (rather than average) percolation 
flux that controls the onset of seepage, the distribution of flow channels on all scales becomes a 
critical aspect for drift seepage. Flow focusing could concentrate water onto a particular drift 
segment and lead to a flux that exceeds the seepage threshold. On the other hand, if flow is 
concentrated in one location, flow will be reduced in other areas (potentially below the prevalent 
seepage threshold) and may lead to overall less seepage. Therefore, the distribution of flow 
channels, their frequency, width, and hydrologic properties determine the seepage probability 
and seepage amounts. 
The spatial distribution of flow channels may change with the average percolation flux and 
potentially with time. The flux in a flow channel may be near steady state or episodic with a 
wide spectrum, ranging from high-frequency fluctuations triggered by flow instabilities, to 
intermediate variabilities in percolation fluxes in response to changing weather conditions, to 
long-term variations from climate changes. 
In summary, the local (rather than average) percolation flux reaching the drift is the most important 
factor determining whether seepage occurs, the seepage rate, and the spatial and temporal 
distribution of seepage events. 
MDL-NBS-HS-000004 REV02 April 2003 43 U0080 Seepage Calibration Model and Seepage Testing Data 
Model Conceptualization 
The actual percolation flux and its distribution are unknown. Estimates of the average, steadystate 
percolation fluxes at the locations of the liquid-release tests are taken from the UZ Model 
(see Section 6.6.2.3) and applied at the top of the corresponding drift seepage models. Note that 
large-scale redistribution of infiltration and percolation fluxes is captured in the mountain-scale 
UZ Model; intermediate-scale flow concentrations is accounted for in the TSPA calculations 
through the use of a probabilistic flow focusing factor. Small-scale flow concentration is 
included in the SCM by explicitly modeling small-scale heterogeneities (see Section 6.6.2.1). 
The transient SCM simulations capture the time-dependent boundary conditions, saturation, and 
seepage-rate changes induced by the intermittent water release during seepage testing. Potential 
occurrence of small-scale, high-frequency episodic flow events is reflected in the seepage-rate 
data used for calibration. The cumulative effect of these episodic events on seepage is therefore 
appropriately captured in the estimation of an effective capillary-strength parameter. Lowfrequency 
fluctuations in the background percolation flux on account of weather-condition or 
climate changes are of no significance because of the comparatively short duration of the liquidrelease 
tests. In summary, the high-frequency episodic flow events are captured in the effective, 
seepage-relevant capillary-strength parameter, whereas the low-frequency transient events are 
accounted for in the UZ Model, which provides a time-dependent percolation flux as input to the 
seepage TSPA calculations. Additional issues related to the amount, variability, and uncertainty 
of percolation flux, lateral flow diversion, as well as large- and intermediate-scale flow concentration 
are also addressed by the UZ Model, seepage abstraction, and TSPA calculations. 
6.3.3.2 Formation Properties 
General Description 
The key formation properties determining the effectiveness of the capillary barrier are (1) the 
capillary strength and (2) the tangential conductivity in the boundary layer near the drift wall. 
Geologic formations with strong capillarity and high tangential conductivity exhibit a high 
seepage threshold (i.e., low seepage), whereas a weak capillary barrier effect (i.e., high seepage) 
is expected if water retention is small or if the tangential permeability is insufficient to promote 
flow diversion. 
Porous formations with strong capillarity tend to have low permeability and vice versa, which is 
a correlation that reduces the probability of encountering parameter combinations conducive to 
extreme (low or high) seepage behavior, making seepage relatively uniform across different 
geologic units. However, this negative correlation between conductivity and capillary strength 
may not apply to a fractured system, specifically if considering the seepage process. A certain 
hydraulic conductivity may result from a network consisting of a few, large fractures or, alternatively, 
many small, well-connected fractures. The first network would exhibit weak capillarity, 
whereas the second network has strong capillarity, i.e., capillarity is not necessarily correlated to 
permeability. Moreover, if the predominant fracture orientation happens to be aligned with the 
drift axis (see Figure 1a), little or no tangential conductivity is available, flow diversion is 
reduced or prevented, and seepage is increased. Even if fractures are normal to the drift axis, 
they may be too small or poorly connected, i.e., they would not be able to facilitate a continuous 
MDL-NBS-HS-000004 REV02 April 2003 44 U0080 Seepage Calibration Model and Seepage Testing Data 
flow path from the apex of the drift to its spring line. For flow diversion to occur, the fracture 
system must have sufficient connectivity and permeability to provide the necessary effective 
conductivity in tangential direction around the drift. 
Matrix permeability is low, and the potential for imbibition of substantial amounts of water into 
the matrix is limited because of relatively low porosity and relatively high initial liquid saturation. 
In a fracture-matrix system, the transient effects from matrix imbibition are restricted to 
intermediate times, i.e., they are insignificant (1) for a short-term liquid-release test with insufficient 
time for matrix imbibition, and (2) for a long-term seepage experiment, when near-steady 
late-time data are no longer affected by matrix imbibition. Most liquid-release tests analyzed in 
this Model Report are sufficiently long to yield near-steady seepage rates that are insignificantly 
affected by potential matrix imbibition. 
Heterogeneities in formation properties impact seepage as they promote flow concentration and 
increase the probability of locally breaching the capillary barrier. 
Model Conceptualization 
Seepage-related fracture properties on all relevant scales are not available and cannot be reliably 
derived from fracture-trace maps, considering that the mapped geometric characteristics and 
hydraulic properties are not related in a simple or unique way. However, as discussed in Sections 
6.3.2 and 6.4.1 and demonstrated in Finsterle (2000 [151875]), it is not necessary to develop a 
discrete fracture network model for predicting average seepage on the scale of a waste package. 
In this work, the capillarity and the conductivity are conceptualized as effective properties that 
are specifically determined for their intended use in a drift seepage model. The corresponding 
model parameters must not only represent the average hydraulic characteristics of individual 
fractures, but also the connectivity, density, geometry, and orientation of the fracture network as 
it relates to the geometry and orientation of the underground opening. Moreover, they must 
account for seepage processes that cannot be explicitly implemented in the conceptual model 
(such as film flow and small-scale roughness in the drift ceiling), and compensate for certain 
artifacts related to the finite discretization of the numerical model. Model calibration against data 
that reflect all relevant seepage processes is the approach relied upon to determine these effective 
parameters. 
The SCM is conceptualized as a heterogeneous fracture continuum model (see also Section 
6.3.2). The seepage-relevant capillary-strength parameter is determined by calibrating the model 
against seepage-rate data from liquid-release tests (see Section 6.5.3). These data reflect the 
seepage process and contain information about seepage-relevant capillary properties of the 
fractured formation in the vicinity of an open drift. Thus, the inversely determined effective 
capillary-strength parameter is considered pertinent and appropriate for the intended use of the 
model. 
The simulated seepage can be increased by decreasing capillary strength or permeability. Consequently, 
the two parameters are negatively correlated if inversely determined from seepage-rate 
data. Because only seepage data are available for calibration, the parameters are expected to be 
strongly correlated. That is, it is unlikely that they can be determined independently from one 
MDL-NBS-HS-000004 REV02 April 2003 45 U0080 Seepage Calibration Model and Seepage Testing Data 
another and with a reasonably low estimation uncertainty. To reduce correlations and to improve 
the conditioning of the inverse problem, only the capillary-strength parameter is estimated 
through inverse modeling, whereas the permeability is fixed during the inversion. The choice of 
this calibration parameter is further discussed in Section 6.6.3.1. 
The permeability field is considered the result of a stochastic process. Its geostatistical properties 
are determined from air-injection tests (see Section and 6.5.2). Multiple realizations of the 
permeability field are generated and used in the inversions of data from the lower lithophysal 
zone. 
The permeability field generated for simulations with the SCM are representative of the conditions 
currently encountered at the test locations of Yucca Mountain. Therefore, thermally and 
geochemically induced property changes do not need to be considered in this Model Report. 
They are addressed by the TH Seepage Model (BSC 2003 [161530]) and the Thermal- 
Hydrologic-Chemical (THC) Seepage Model (BSC 2002 [158375]). 
6.3.3.3 Drift Geometry 
General Description 
The overall drift size and geometry impact the seepage threshold and the seepage amount. 
Generally, a large drift exhibits a significantly lower seepage threshold because more water 
accumulates in the boundary layer as it migrates over a longer diversion distance around the 
wide opening. Because of the nonlinear impact of cavity size on seepage (Philip et al. 1989 
[105743]), seepage into large openings cannot be easily inferred from cumulative seepage into 
small cavities. 
The effectiveness of a capillary barrier is highest if the shape of the cavity follows an equipotential 
surface. In a homogeneous medium, parabolic cavities are more efficient in preventing 
seepage than circular or flat-roofed openings. Breakouts in the drift ceiling, as a result of rock 
fall and general drift degradation, may change the overall drift geometry and lead to local 
topographic lows, which may trap water, reduce or prevent flow diversion, and thus initiate 
seepage. In addition, small-scale surface roughness tends to increase seepage if the amplitude of 
the irregularity is on the order of boundary-layer thickness. The latter is determined by the 
capillary strength of the formation. 
In a heterogeneous, fractured formation, the importance of drift shape and drift geometry may be 
diminished relative to that of flow channeling and local ponding conditions (see Birkholzer et al. 
(1999 [105170], pp. 372379) and Section 6.4.2). 
Model Conceptualization 
The impact of the overall geometry of the underground opening (ECRB Cross Drift or niche) on 
seepage is accounted for through explicit discretization of the cavity. The ECRB Cross Drift is 
approximated as being cylindrical, with a diameter of 5.0 m. The overall geometry of the niches 
is taken from survey data, thus including some medium-scale roughness from rock fall and large 
lithophysal cavities. 
MDL-NBS-HS-000004 REV02 April 2003 46 U0080 Seepage Calibration Model and Seepage Testing Data 
Small-scale roughness is indirectly included through a discretization effect. The length of the last 
vertical connection from the gridblocks representing the formation and the interface denoting the 
drift surface is 0.05 m (see Attachment III, Attachment IV, and Attachment V; see also discussion 
in Section 6.6.1.2). The choice of this nodal distance affects seepage because no horizontal 
flow diversion can occur closer than 0.05 m from the drift wall. Since water is laterally diverted 
only if capillary suction is on the order of 0.05 m or higher, the discretization has an effect 
similar to that of (1) drift-wall roughness of amplitude of 0.05 m, with troughs at the gridblock 
centers and ridges along the gridblock interfaces, or (2) short fractures cutting into the opening, 
with a distance to the next fracture intersection of 0.05 m. Consequently, the effective capillarystrength 
parameter estimated by inverse modeling depends on the chosen discretization; it 
contains a geometric component related to the length of the nodal distance between the formation 
and the drift. The estimate is thus model-related, and the discretization between the calibration 
model and the prediction model must be consistent. 
In summary, the geometric factors affecting seepage are accounted for through (1) explicit 
discretization of the opening (which includes the overall shape as well as medium-scale roughness 
from break-outs lithophysal cavities), (2) by preventing flow diversion in a 0.05 m thick 
layer around the drift (mimicking small-scale surface roughness with a 0.05 m amplitude of the 
irregularities), and (3) the estimation of an effective capillary-strength parameter. The inclusion 
of small-scale surface roughness (exceeding an amplitude of 0.05 meters) and discrete effects 
from small fractures into an effective capillary-strength parameter is appropriate because their 
impact on seepage rates is directly related to capillarity. 
Note that the nominal diameter of a repository drift is 5.5 m, which is slightly larger than that of 
the ECRB Cross Drift (5.0 m). This difference is of no significance, because the seepage-related 
parameters are determined using a model with the correct diameter (5.0 m) to be used for the 
analysis of liquid-release tests in the ECRB Cross Drift. These parameters are then applied in the 
prediction model, which simulates seepage into an opening with a 5.5 m diameter. The impact of 
drift-shape changes as a result of drift degradation is discussed in the upcoming revision REV 02 
of CRWMS M&O (2000 [153314]). 
6.3.3.4 Evaporation Conditions 
General Description 
Reduced relative humidity in the underground opening leads to evaporation of water at the drift 
surface and the development of a dry-out zone in the vicinity of the cavity. Part or all of the 
water reaching the ceiling of the opening during a liquid-release test may evaporate, depending 
on the evaporation potential in the drift and the wet area exposed to evaporation. The evaporation 
potential depends on the relative humidity in the opening and the thickness of a diffusive boundary 
layer at the drift surface, which in turn is governed by the air velocity in the ventilated drift. 
The size of the wet spot developing at the drift ceiling depends on the formation properties, the 
spreading mechanism along the drift surface, and evaporation itself. As water injected during a 
liquid-release test reaches the opening, it spreads along the surface on account of surface 
adhesion within the rough surface. As a result, water potentially seeping into the opening may 
not only form droplets or lines of water along fracture traces with a small surface area, but may 
MDL-NBS-HS-000004 REV02 April 2003 47 U0080 Seepage Calibration Model and Seepage Testing Data 
spread across the drift surface over a relatively large area. This phenomenon is qualitatively 
confirmed by the geometry of the wet spot observed at the niche ceiling during seepage experiments 
(BSC 2001 [158463], Section 6.2.1.3.4, Figure 6.2.1-7; Trautz and Wang 2002 [160335], 
Figures 7 and 9). The geometry of the wet spot does not have a clear correlation with the visible 
fracture traces. Even though water first appears along fracture traces (Trautz and Wang 2002 
[160335], Figure 10), the wet spot grows in an areal fashion. It is obvious from the short arrival 
time and the average speed at which the leading edge of the plume moves across the ceiling that 
the water is not transmitted through the matrix, but spreads along the ceiling as a surface film, 
possibly supported by flow through microfractures. Evaporation from such wet areas is similar to 
evaporation from a free water surface, where the evaporation rate is governed by onedimensional 
vapor diffusion across a relatively thin boundary layer of linearly decreasing vapor 
concentration. Temporal shrinkage of the wet spot can be correlated to increased evaporation as 
a result of changed ventilation regime, highlighting the coupled nature of the process. 
In a closed-off and humidified niche, potential evaporation at the wall or in the capture system is 
expected to be small compared to the amount of water being released. Seepage experiments in 
the middle nonlithophysal zone of the Topopah Spring welded unit were conducted in niches that 
were closed off by a bulkhead, which leads to comparatively high relative humidity and low air 
circulation. Moreover, a humidifier was used in some of the experiments to ensure high relative 
humidity. For these conditions, Ho (1997 [141521]) and Or and Ghezzehei (2000 [144773]) 
provide a detailed description of evaporation mechanisms on the scale of individual water 
droplets within fractures or emerging from fractured formations. The evapo-infiltration threshold 
calculated by Ho (1997 [141521], p. 2670) is significantly lower than the applied injection rates, 
suggesting a very minor influence of evaporation on measured seepage rates in experiments 
conducted in the niches. 
Model Conceptualization 
Evaporation effects are included in the modeling of liquid-release tests performed in the ventilated 
ECRB Cross Drift as well as in Niche 1620. Evaporation effects are neglected in the 
modeling of liquid-release tests conducted in the closed-off niches in the middle nonlithophysal 
zone, i.e., Niches 3107, 3650, and 4788. As demonstrated in Section 6.7, the impact of slight 
evaporation in a closed-off and moisturized niche on seepage ratesand thus on the estimation 
of seepage-relevant parametersis minor. 
Evaporation effects are accounted for in the model by prescribing the measured relative humidity 
in the opening as a temporally varying water-potential boundary condition. Evaporation is 
calculated as a function of the water-potential gradient at the drift surface, the vapor diffusion 
coefficient, and the thickness of the diffusive boundary layer, which is estimated from evaporation 
pan measurements. A detailed description of the corresponding conceptual and mathematical 
model and the estimation of the evaporation boundary-layer thickness is given in Sections 6.6.1.3 
and 6.6.1.4. 
Predictions of long-term seepage using the SMPA are based on the presumption of 100% relative 
humidity in the waste emplacement drifts, yielding higher seepage estimates than those expected 
in a ventilated environment. 
MDL-NBS-HS-000004 REV02 April 2003 48 U0080 Seepage Calibration Model and Seepage Testing Data 
6.3.3.5 Lithophysal Cavities 
General Description 
The impact of lithophysal cavities on flow and seepage is twofold: (1) lithophysal cavities are 
essentially obstacles to water flow because they act as capillary barriers, focusing the water that 
flows around them; (2) lithophysal cavities intersected by the drift lead to a rough drift wall, 
potentially creating seepage points at local topographic lows. Both effects tend to promote 
seepage. 
Model Conceptualization 
The effect of lithophysal cavities on seepage can be captured through the estimation of an 
effective capillary-strength parameter, making the explicit inclusion of lithophysal cavities into 
the process model unnecessary. This approach is considered appropriate for the following 
reasons: (1) omitting lithophysal cavities in the process model used for inverse modeling yields 
lower estimates of the capillary-strength parameter; (2) consistency between the calibration 
model (the SCM) and the prediction model (the SMPA) removes the impact of a potential 
estimation bias; (3) the approach allows for the development of a single SMPA conceptual model 
for both the middle nonlithophysal and lower lithophysal zones, yielding a single look-up table 
for TSPA to sample from; and (4) explicit modeling of lithophysal cavities is not warranted 
because of insufficient information regarding their location, shape, and frequency. Note that the 
impact of lithophysal cavities on surface roughness in Niche 1620 is accounted for through 
explicit discretization of the niches geometry, based on survey data (see Attachment V). 
6.3.4 General Modeling and Data-Analysis Approach 
The key element of the approach chosen to simulate seepage and determine seepage-relevant 
parameters is the reliance on inverse modeling. Given the complexity of the seepage process in a 
fractured porous medium, it is considered unfeasible to develop a detailed process model with a 
deterministic calculation of unsaturated water flow, through a fracture network that exhibits 
multiscale variabilities in hydraulic properties. Such a model would also require an accurate 
representation of the seepage process, which includes effects from small-scale roughness and 
small-scale heterogeneities, film flow within fractures and along the drift surface, drop formation 
and detachment, and other processes. While modeling these processes is theoretically possible, 
the necessary characterization data needed to warrant such a detailed simulation are not 
available. 
The difficulties mentioned above can be effectively overcome by recognizing that (1) detailed 
simulation of individual seeps is not necessary to estimate average seepage rates into waste 
emplacement drifts, (2) certain factors affecting seepage can be lumped into an effective 
parameter, (3) calibrating a model against data from seepage experiments ensures that the model 
captures the relevant processes, (4) estimating effective parameters partly compensates for 
processes and features that are not explicitly considered in the model, and (5) the estimated 
parameters are optimal and can be directly used in the prediction model. 
The main advantage of this approach is that it relies directly on seepage-rate data, which inherently 
contain information about the relevant processes. Moreover, the calibration data (seepage 
49 MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
rates on the scale of a drift section) are very similar to the measure of interest for the subsequent 
predictions. The consistency between the calibration model used to derive seepage-relevant 
parameters and the prediction model used to forecast seepage minimizes potential conceptual 
differences and large systematic errors. The advantages of the selected method over alternative 
approaches are further evaluated in Section 6.4. 
The SCM is conceptualized as a three-dimensional, heterogeneous continuum model. The 
continuum mainly represents the dense fracture network that dominates the seepage process. The 
SCM is conceptually consistent with the unsaturated zone site-scale model and submodels 
thereof, specifically the SMPA and TH Seepage Model (BSC 2003 [161530]). This makes it 
straightforward to embed the SCM into the current modeling framework. 
As will be discussed in Section 6.6.3.2, the SCM is calibrated against late-time seepage-rate data 
from liquid-release tests. Early-time seepage data are discarded because they are affected by 
storage effects and the properties of a few fractures connecting the injection interval with the 
opening. These fractures are not necessarily representative of the fracture network that is 
engaged in flow diversion around the entire opening under steady-state conditions. Late-time 
data are more representative of near-steady conditions and are less influenced by storage effects. 
Moreover, the relatively large amount of released water at late time has likely encountered a 
significant portion of the capillary barrier. As a result, the late-time seepage data better reflect 
average conditions on the scale of interest. 
Liquid-release tests directly supporting the SCM were conducted in two different hydrogeologic 
units, in multiple test beds, boreholes, and intervals. Each test event probes a different portion of 
the rock and a different section of the underground opening. The question arises how the 
available data should be combined to yield suitable averages and reasonable measures of 
variability and uncertainty, which are needed for model validation and the subsequent PA 
calculations. The goal is to obtain a probability density function of the seepage-relevant parameters 
that reflects both estimation uncertainty and spatial variability. These two aspects are 
discussed separately in the following paragraphs. 
Parameter estimates determined by inverse modeling are uncertain because they are derived from 
limited data, which exhibit random and potentially systematic measurement errors, and because 
the model is a simplification of the real system, which introduces systematic and random 
modeling errors. As discussed above, estimating model-related parameters mitigates the impact 
of some of the residual systematic errors. Estimation uncertainty as a result of random noise in 
the seepage data is relatively minor (see Sections 6.6.3.3 and 8.2). However, there remains 
irreducible uncertainty because of small-scale heterogeneity that affects individual seepage tests. 
The details of these small-scale heterogeneities are unknown (i.e., they cannot be described 
deterministically) and vary from location to location (i.e., they are spatially variable). Consequently, 
they are considered the result of a stochastic process that must be described by geostatistical 
parameters and modeled by performing multiple geostatistical simulations. Each seepage 
data set is obtained from a certain test bed (niche or section of ECRB Cross Drift); it can be 
considered one realization from a number of statistically similar geologic systems. The lack of 
knowledge regarding the details of this specific realization makes the inversely determined 
parameter estimate uncertain. This uncertainty is examined by performing multiple inversions of 
the same data set using different realizations of the underlying heterogeneous permeability field, 
April 2003 50 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
yielding a distribution of estimated capillary-strength parameters rather than a single value. In 
addition to capturing the random nature of the permeability field and its impact on seepage, each 
realization will induce some ergodic fluctuations, which reflect the fact that the model statistics 
are inferred from sparse air-permeability sampling (i.e., they are not deemed exactly representative 
of the population statistics). The average of all inversions performed with different permeability 
fields for a given interval yields one estimate representative of that location. 
The average parameters obtained from multiple simultaneous inversions of one or more seepage 
events conducted in a certain test interval are considered independent, each reflecting the 
seepage-relevant properties at a given location on the drift scale. These estimates are then 
combined to yield a parameter distribution for the entire hydrogeologic unit. This distribution 
reflects spatial variability. By sampling from the distribution of the resulting parameter 
estimates, probabilistic predictions of seepage across the repository horizon can capture the 
spatial variability of average seepage on the scale of the 5 m long drift segment. Uncertainty in 
this average seepage rate as a result of small-scale heterogeneity is calculated based on multiple 
seepage prediction runs by the SMPA, using multiple realizations of the underlying permeability 
field. 
A comparison of seepage predictions with observable data (such as seepage data from transient 
liquid-release tests involving a finite amount of water) is a necessary step in model development 
and confidence building. However, models are often developedand most usefullyto infer 
behavior that cannot be directly observed (such as long-term near-steady seepage under naturally 
low percolation fluxes). The appropriateness of such an extrapolation of the model beyond its 
tested grounds needs to be assessed. While rigorous model testing is fundamentally not possible 
(Oreskes et al. 1994 [152512]), validation of the model for a limited purpose can be accomplished. 
The SCM is partially tested against observable data from seepage experiments that were 
not used for model calibration. The purpose of this validation exercise is to determine whether 
the model is appropriate and adequate for its intended use. Remaining uncertainty will be quantified 
during the seepage abstraction process and propagated through the PA models. Additional 
remarks about model validation can be found in Section 7.1. 
The development of the SCM involves the following steps: 
1. Geostatistical parameters of the permeability field are determined from the results of airinjection 
test data. 
2. Multiple realizations of the permeability field are generated, each being consistent with 
the geostatistical properties of the measured air permeabilities. 
3. A numerical mesh is generated. This step involves (a) making a primary 3D grid, (b) 
translating coordinates to center the mesh, (c) mapping the permeability field onto the 
mesh, (d) cutting out the opening (niche or drift) from the mesh, (e) adding top and 
bottom boundary elements as well as an evaporation boundary in the opening, and (f) 
modifying elements representing injection intervals. 
4. An input file defining the forward problem is prepared. This step involves (a) assembling 
parameters representing hydrogeologic properties, (b) assigning appropriate properties to 
elements representing the excavation and borehole intervals, (c) extracting the back- 
April 2003 51 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
ground percolation flux from the UZ Model, (d) assigning appropriate initial and boundary 
conditions, and (e) selecting computational parameters and program options. 
5. Steady-state runs are performed to obtain initial conditions for the subsequent simulation 
of transient seepage experiments. 
6. Injection rates are specified as time-dependent source terms. 
7. Test events are selected for calibration. Seepage rates are calculated from the cumulative 
seepage data. 
8. An input file defining the inverse problem is prepared. This step involves (a) selecting the 
parameters to be estimated and their initial guesses, (b) selecting points in time at which 
calibration should occur, (c) specifying the data against which calibration should occur, 
(d) assigning measurement uncertainties to the data sets as weighting factors, and (e) 
selecting computational parameters and program options. 
9. Seepage-relevant, model-related parameters are determined by automatic model calibration 
using iTOUGH2 V4.0 (LBNL 1999 [139918]) and V5.0 (LBNL 2002 [160106]). In 
each inversion, seepage-rate data from multiple test events are jointly inverted. 
10. The model is tested by comparing predicted seepage rates to observed data from seepage 
experiments not used during model calibration. Prediction uncertainty is calculated by 
iTOUGH2 V4.0 (LBNL 1999 [139918]) and V5.0 (LBNL 2002 [160106]) using firstorder-
second-moment (FOSM) uncertainty propagation analysis and Monte Carlo 
simulations. 
6.4 ALTERNATIVE CONCEPTUAL MODELS 
The following subsections contain short descriptions of potential alternative ways to evaluate 
seepage into waste emplacement drifts at Yucca Mountain. These alternative conceptual models 
are discussed in a qualitative manner, and references to more detailed analyses are given, if 
available. No quantitative evaluations of these alternative conceptual models are presented in this 
Model Report. 
Natural analogues for seepage also support the concepts of the base-case model; they are briefly 
reviewed in Section 7.2.1. 
In general, the choice of a conceptual model should be based on a careful consideration of the 
study objectives, the available database in comparison with the data needs, the uncertainty in the 
input parameters and the corresponding prediction uncertainties and computational aspects. 
52 
6.4.1 Discrete Fracture Network Model 
A discrete fracture network model (DFNM) is an alternative conceptual model to the heterogeneous 
continuum model used in this Model Report (Pruess et al. 1999 [117112], pp. 307309). A 
high-resolution DFNM is capable of generating channelized flow and discrete seepage events, as 
demonstrated by Finsterle (2000 [151875], Plate 1) and Liu et al. (2002 [160230], Figure 5). 
Note that two-dimensional DFNMs such as those shown in Figure 2 and Figure 3 make the 
MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
implicit assumption that the fractures are oriented parallel to the drift axis. This assumption 
exaggerates the discreteness of the flow and seepage behavior as flow diversion within the 
fracture plane is not possible (see also Figure 1 and related discussion in Section 6.3.2). 
(a) (b) 
Figure 2. Two-dimensional discrete feature model (after Finsterle 2000 [151875], Plate 1): (a) highresolution 
permeability field; (b) discrete flow path and discrete seepage behavior 
(a) (b) 
Figure 3. Two-dimensional discrete fracture network model (after Liu et al. 2002 [160230], Figures 1 
and 2): (a) fracture network; (b) flow paths 
April 2003 53 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
The development of a defensible DFNM requires collecting a very large amount of geometric 
and hydrologic data. While part of the required geometric information can be obtained from 
fracture mappings, the description of the network remains incomplete and potentially biased 
towards fractures of a certain orientation and a certain size. Moreover, unsaturated hydrological 
parameters on the scale of individual fractures are required, along with conceptual models and 
simplifying assumptions regarding unsaturated flow within fractures and across fracture intersections. 
The databases required to develop a defensible DFNM are currently not available and 
are generally difficult or even impossible to obtain for site-specific simulations. As a result, the 
cumulative effect of all the input uncertainties is likely to outweigh the apparent advantage of a 
detailed representation of the fracture network. To reduce prediction uncertainties, the DFNM 
must be calibrated against hydrogeologic datathat is, an approach very similar to that outlined 
in Section 6.3.4 must be followed. 
The appropriateness of using a continuum model for the prediction of average seepage quantities 
was demonstrated in Finsterle (2000 [151875]). In this study, seepage predictions with a 
calibrated fracture continuum model were compared to those of a DFNM, yielding consistent 
results even when applied outside the range of calibration. Given these results, the parsimony of 
the continuum model is considered a key advantage over the complexity of the DFNM, which is 
difficult to support or justify despite its visual appeal. Moreover, a two-dimensional DFNM is 
not capable of capturing flow diversion within the fracture plane, a mechanism appropriately 
represented by a 2D (or 3D) continuum model. 
For the reasons outlined above, the full development of a DFNM as a potential alternative to the 
base-case continuum model was considered unwarranted, infeasible, and unnecessary. Seepage 
calculations with a calibrated DFNM are likely to corroborate the findings of this Model Report. 
6.4.2 Seepage Governed by Ponding Probability 
As an alternative conceptual model to a seepage process model, Birkholzer et al. (1999 [105170], 
pp. 372379) related seepage to the local ponding probability, which was derived from the 
variability of the permeability field. Their approach assumed thatin strongly heterogeneous 
formationsseepage is predominantly affected by pressure variations governed by local heterogeneity 
rather than the presence and geometry of the capillary barrier. This is different from the 
behavior in a homogeneous system, where the geometry of the capillary barrier has a strong 
impact on seepage (Philip et al. 1989 [105743]). Strong medium- to small-scale heterogeneities 
tend to increase seepage because they increase channeling and local ponding. This effect is 
included in the current seepage process models through the estimation of effective, seepagespecific 
parameters for a heterogeneous medium with a heterogeneous permeability field. While 
the approach presented by Birkholzer et al. (1999 [105170], pp. 372379) may provide guidelines 
for how to extrapolate seepage predictions to other units or drift geometries, it nonetheless 
requires a calibration step similar to that described in this Model Report. The approach is 
therefore not further considered. Nevertheless, the concept that ponding probability affects 
seepage is consistent with and thus corroborates the base-case model, which produces random 
seepage locations as a result of local ponding in a stochastic permeability field. 
54 MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
2 
6.4.3 Inferring Seepage from Geochemical Data 
Observations of calcite and opal in lithophysal cavities could be used to estimate long-term 
seepage rates into these small openings (BSC 2002 [160247], Section 6.10.1). Calcite is assumed 
to precipitate from downward-percolating meteoric water because of (1) evaporation, (2) CO 
outgassing as a result of the geothermal gradient, and (3) interaction with a gas phase containing 
less CO2 than the gas with which the water was last equilibrated. Considering these calciteprecipitation 
mechanisms and assuming certain water-to-calcite ratios, seepage into lithophysal 
cavities can be estimated from calcite-deposition data. The analysis of calcite and opal precipitation 
data shows that (1) not all lithophysal cavities encountered seepage, and (2) seepage flux 
derived from mineral deposits is a very small fraction of percolation flux. Both conclusions 
corroborate the general concept of a capillary barrier reducing seepage below the value of the 
percolation flux. 
The advantage of using geochemical information to infer seepage is the fact that calcite and opal 
were deposited over a long period of time under natural percolation conditions. The disadvantage 
of this approach is that (1) seepage is inferred in an indirect manner, requiring a number of 
geochemical models with their associated assumptionsin addition to hydrogeologic model 
assumptions; (2) the calcite depositions on lithophysal cavity floors may not originate from 
dripping water (i.e., seepage); in fact, there is a lack of evidence of dripping from cavity ceilings 
(absence of stalactites or stalagmites), even where fractures containing coatings intersect lithophysae 
ceilings (Whelan et al. 2002 [160442], p. 744); (3) the data reflect seepage into (small) 
cavities instead of seepage into a (large) waste emplacement drift; since the size of the underground 
opening impacts seepage in a nonlinear fashion, a hydrological, physically based process 
model is required to estimate seepage on the scale of interest; (4) seepage into lithophysal 
cavities does not include potential impacts from the excavation-disturbed zone around a 
mechanically constructed drift; and (5) the historic record and the approach does not allow 
making predictions into the future under changed conditions. 
As shown by Marshall et al. (2000 [151018], Figure 1), the seepage rates estimated from the 
calcite-deposition data are significantly lower than those predicted by TSPA using data derived 
from the SMPA, which is based on the methodology outlined in this Model Report. 
6.4.4 Inferring Seepage Threshold Directly From Liquid-Release Tests 
Trautz and Wang (2002 [160335], Section 5) estimated the seepage threshold directly from the 
liquid-release test data, based on a number of simplifying assumptions (with regard to the crosssectional 
area of the flow path between the borehole and the ceiling, evaporation, and the steadystate 
flow field). Once the seepage threshold was determined, a capillary-strength parameter was 
derived assuming seepage into a cylindrical cavity excavated from a homogeneous porous 
medium (Trautz and Wang 2002 [160335], Section 6). The base-case model outlined in this 
Model Report relies on fewer assumptions than the simplified alternative conceptual model and 
predicts a lower seepage threshold; the base-case model described in this Model Report is 
therefore the preferred conceptualization. 
55 MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
6.5 DESCRIPTION OF SEEPAGE EXPERIMENTS 
6.5.1 Test Location and Borehole Configuration 
The data used for the development, calibration, and validation of the SCM were collected as part 
of the ESF Drift Seepage Test and Niche Moisture Study, an ongoing field-testing program. 
Drift-scale seepage tests were initiated in 1997 to investigate potential seepage into an underground 
opening representing a waste emplacement drift. Short drifts ranging from 6.3 m to 15.0 
m in length were constructed at various locations along the ESF and the ECRB Cross Drift. 
Boreholes were installed prior to and after the drifts were excavated to facilitate characterization 
of the rock using air-injection tests and investigation of seepage processes using liquid-release 
tests. The short excavations are called niches, and the drift-scale seepage tests are collectively 
referred to as the Niche Study. In Niche 1620, a horizontal slot on the side of the niche (also 
referred to as batwing) was excavated to obtain direct evidence of the flow-diversion capability 
of the capillary barrier (see Section 6.8). 
A second study referred to as the Systematic Borehole Testing Program was initiated in 2000 to 
complement the niche seepage experiments. The purpose of the program is to provide broad, 
systematic coverage and characterization of the lower lithophysal zone (Tptpll) of the Topopah 
Spring welded unit (TSw). Systematic characterization of the Tptpll is accomplished by 
performing air-injection and liquid-release tests in approximately 20 m long boreholes drilled 
into the ceiling approximately every 30 m along the ECRB Cross Drift. 
The data used in this Model Report are a subset of seepage tests from the Niche Studies and the 
Systematic Borehole Testing Program. A few tests failed and are not used in this Model Report 
(see discussion of Table 11 below). Data include air permeabilities and seepage-rate values from 
tests conducted at three niche sites located along the Main Drift of the ESF, one niche in the 
ECRB Cross Drift, and in three systematic testing boreholes drilled into the ceiling of the Cross 
Drift (see Figure 4). The first three niche sites are located along the west side of the ESF in the 
Tptpmn and were selected for study based on fracture and hydrologic data collected in the ESF. 
The first niche site at construction station (CS) 31+07 (hereafter referred to as Niche 3107) 
consists of a 6.3 m long drift located in an area of relatively low fracture density. Niche 3107 is 
located in close proximity to CS 30+62, where the Cross Drift crosses over the Main Drift of the 
ESF. The second niche site, at CS 36+50 (Niche 3650), consists of a 9 m long drift located in a 
competent rock mass exhibiting relatively moderate fracture density. The third niche site, at CS 
47+88, (Niche 4788) consists of an 8.2 m long drift located in an area exhibiting relatively high 
fracture density. Niche 4788 is located in a 950 m long exposure of an intensely fractured zone. 
Fractures in this zone are not uniformly spaced, but instead occur in clusters of closely spaced 
fractures. The 15.0 m long Niche 1620 is located on the south side of the ECRB Cross Drift in 
the Tptpll. 
56 MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
Figure 4. Schematic geologic map showing approximate location of niches and systematic testing 
boreholes SYBT-ECRB-LA#13. The shape of the openings is approximate. 
Prior to niche excavation, horizontal boreholes were drilled to gain access to the rock for testing 
and monitoring purposes. The boreholes above each niche are approximately one meter apart and 
within the same horizontal plane. Table 9 provides the correlation between the borehole designations 
shown in the schematic cross sections of Figure 4 (and used throughout this document) and 
their respective designations in the survey DTN. Note that throughout Project documents, the 
systematic testing boreholes are designated as either SYBT-ECRB-LA#x or ECRB-SYBTLA#
x; these designations are unambiguous and thus interchangeable without loss of traceability. 
The format SYBT-ECRB-LA#x is used in this Model Report, consistent with most DTN entries. 
April 2003 57 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
Niche 
3107 
(Niche 3) 
3650 
(Niche 2) 
4788 
(Niche 4) 
1620 
(Niche 5) 
sal zone (Tptpll). 
All boreholes listed in Table 9 are approximately parallel to the niche axis. Air-injection tests 
were conducted in several, 1 ft (0.3 m) long borehole packed-off intervals both prior to and after 
niche excavation to determine the permeability distribution of the formation, as well as to study 
potential permeability changes as a result of stress relief during niche excavation. After niche 
construction, water was injected at a specified rate into intervals of the same boreholes to 
observe, document, and quantify any water migrating to and seeping into the niche. 
The systematic testing boreholes SYBT-ECRB-LA#1, 2, and 3 are drilled from the ECRB and 
located in the moderately to densely welded, devitrified, and vapor-phase altered lower lithophy- 
Borehole SYBT-ECRB-LA#1 is collared from the drift crown at ECRB construction station CD 
17+49. It is upward-inclined at nominal 15 from the drift axis. Packers are set to isolate an 
injection zone between 3.0 m and 4.9 m (zone 2) from the collar (BSC 2001 [158463], p. 241). 
Borehole SYBT-ECRB-LA#2 is collared from the drift crown at ECRB construction station CD 
17+26. It is upward-inclined at nominal 15 from the drift axis. Packers are set to isolate three 
6 ft (1.8 m) long injection zones between 17 ft (5.2 m) and 23 ft (7.0 m) (zone 1), 33 ft (10.1 m) 
and 39 ft (11.9 m) (zone 2), and 49 ft (15.0 m) and 55 ft (16.8 m) (zone 3) from the collar 
(DTN: LB00090012213U.002 [153154]). Borehole SYBT-ECRB-LA#3 is collared from the 
drift crown at ECRB construction station CD 16+95. It is upward-inclined at nominal 15 from 
the drift axis. Packers are set to isolate three 6 ft (1.8 m) long injection zones between 18 ft (5.5 
m) and 24 ft (7.3 m) (zone 1), 34 ft (10.4 m) and 40 ft (12.2 m) (zone 2), and 50 ft (15.2 m) and 
56 ft (17.1 m) (zone 3) from the collar (DTN: LB0203ECRBLIQR.001 [158462]). 
DTN of Borehole Survey DIRS# 
ESF-MD-NICHE 3107 #5 MO0002GSC00064.000 [152625] 
ESF-MD-NICHE 3107 #6 
ESF-MD-NICHE 3107 #7 
ESF-MD-NICHE 3650 #1 MO0002GSC00076.000 [152623] 
ESF-MD-NICHE 3650 #2 
ESF-MD-NICHE 3650 #3 
ESF-MD-NICHE 4788 #5 MO0107GSC01069.000 [156941] 
ESF-MD-NICHE 4788 #6 
ESF-MD-NICHE 4788 #7 
ECRB-NICHE 1620 #1 MO0209GSC02116.000 [160407] 
ECRB-NICHE 1620 #2 
ECRB-NICHE 1620 #3 
ECRB-NICHE 1620 #4 
ECRB-NICHE 1620 #5 
ECRB-NICHE 1620 #6 
ECRB-NICHE 1620 #7 
Borehole 
UL 
UM 
UR 
UL 
UM 
UR 
UL 
UM 
UR 
#1 
#2 
#3 
#4 
#5 
#6 
#7 
MDL-NBS-HS-000004 REV02 
U0080 
Table 9. Borehole Designations in Niches 
Designation in DTN 
58 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
6.5.2 Air-Injection Tests 
The purpose of the air-injection tests was to estimate permeabilities as a basis for the stochastic 
generation of heterogeneous permeability fields. The tests were performed by isolating a short 
section of the boreholes (1 ft [0.3 m] in niches, 6 ft [1.8 m] in systematic testing borehole SYBTECRB-
LA#2), using an inflatable packer system, and then injecting compressed air at a constant 
rate into the isolated injection interval. The pressure buildup in the injection interval and in 
nearby observation intervals was monitored with time until steady-state conditions were reached, 
which typically occurred within a few minutes. Air injection was terminated after reaching 
steady-state pressures, and the decline in air pressure was then monitored as it recovered to its 
initial pre-test condition. Air-permeability values were derived from the steady-state pressure 
data based on a commonly used analytical solution (BSC 2001 [158463], Section 6.1.2.1; LeCain 
1995 [101700], p. 10, Eq. (15)). 
Permeabilities determined from air-injection tests are considered representative of the absolute 
permeability of the excavation-disturbed zone around the opening. This is reasonable, because 
post-excavation air-injection tests were conducted in a network of essentially dry fractures, i.e., 
no empirical relative permeability function is needed to translate air conductivity into absolute 
permeability. Since air-injection tests are a standard method to obtain permeability values, the 
use of these values during both calibration and prediction of seepage ensures consistency. The 
distributions representing variability and uncertainty in permeability (see upcoming Model 
Report MDL-NBS-HS-000019 REV 00 (CRWMS M&O 2001 [154291])) are developed also 
based on air-permeability data. This consistency reduces the impact of a potential bias. 
The air permeabilities around the niches and the ECRB Cross Drift are affected by excavation 
(BSC 2001 [158463], Section 6.1.2.2; Wang and Elsworth 1999 [104366], pp. 752756). Since 
seepage is determined by the formation properties in the immediate vicinity of the opening, it is 
reasonable to use post-excavation air-permeability data for seepage calculations. Data that are 
located outside the footprint of the niches were removed from the data set (Ahlers 2002 
[161045], p. 20; Trautz 2001 [161044], p. 20) because they represent a separate population of air 
permeabilities performed in an area of relatively undisturbed, lower-permeability rock. Mean and 
standard deviations for each of the four locations are summarized in Table 10. Here, standard 
deviations reflect spatial variability within the test bed. The number of log-permeability values 
available is indicated in the last column. Mean permeabilities and their spatial variability as 
calculated for the three niches located in the middle nonlithophysal zone are consistent with one 
another. Permeability in the lower lithophysal zone is approximately one order of magnitude 
larger. The variability as measured in Niche 1620 is significantly larger than that obtained in 
borehole SYBT-ECRB-LA#2. This is partly a result of the injection intervals of borehole SYBTECRB-
LA#2 being six times longer than those in Niche 1620. Note no air-permeability data are 
available from boreholes SYBT-ECRB-LA#1 and SYBT-ECRB-LA#3 because of equipment 
problems during air-injection testing. 
MDL-NBS-HS-000004 REV02 April 2003 59 U0080 Seepage Calibration Model and Seepage Testing Data 
Table 10. Mean and Standard Deviation of Post-Excavation Log-Air-Permeability Values 
Location 
Niche 3107 
Niche 3650 
Niche 4788 
Niche 1620 
Input DTN 
LB990601233124.001 [105888] 
LB0011AIRKTEST.001 [153155] 
LB990601233124.001 [105888] 
SYBT-ECRB-LA#2 LB00090012213U.001 [153141] 
n 
6 
Mean 
Log(k 
[m2]) 
-12.14 0.80 78 
-11.66 0.72 84 
-11.79 0.84 63 
-10.95 1.31 61 
Finsterle 2002 [161043], pp. 5455 -10.73 0.21 
Scientific Notebook Reference 
Ahlers 2002 [161045], pp. 3940 
Trautz 2001 [161044], pp. 1925 
Ahlers 2002 [161045], pp. 1521 
LB0110AKN5POST.001 [156904] Wang 2003 [161456], 
SN-LBNL-SCI-223-V1, pp. 1920 
60 
Std. 
Dev. 
April 2003 
6.5.3 Liquid-Release Tests 
Multiple liquid-release tests were performed in the niches and the ECRB Cross Drift to characterize 
seepage into a large underground opening (BSC 2001 [158463], Sections 6.2 and 6.11). 
The tests were performed by sealing a short section of the borehole above the opening using an 
inflatable packer system and then releasing water at a specified rate into the isolated test interval. 
Any water that migrated from the borehole to the ceiling and dripped into the opening was 
captured and weighed. Only a small amount of water (approximately one liter per test event) was 
released during testing at Niche 3650, and only the total amount of water that seeped into the 
capture system was recorded. Seepage experiments at Niches 3107, 4788, 1620, and in the 
systematic testing boreholes SYBT-ECRB-LA#13 involved significantly more water, which 
was injected over longer periods, and cumulative seepage was recorded as a function of time. 
In many intervals, multiple liquid-release tests were conducted using different injection rates 
with different lengths of inactivity between individual test events. The reason for using different 
injection rates and different injection schedules was to collect data that are sensitive to percolation 
rate and water storage effects. While the inverse modeling approach pursued in this Model 
Report does not require data above and below the seepage threshold, increasing the sensitivity of 
the data to seepage-related effects improves the identifiability of seepage-relevant parameters. 
Table 11 summarizes the test events used for the calibration and validation of the SCM. The 
approximate release rate (defined as the injection rate minus the return flow) is indicated in 
Column 4. As shown in Column 5, 52 out of 90 test events led to seepage into the capture 
system. Potential seepage was not recorded in two cases (Events 5 and 46) because of an equipment 
failure. While no data are available to be used for calibration or validation from these three 
test events, the injections that occurred were nevertheless modeled because the released water 
has a potential impact on subsequent test events. Column 6 indicates whether a specific test event 
was used for calibration (C) or validation (V). A few additional seepage tests were conducted in 
Niche 3650 that were not used, because only a very small amount of water was released and 
generally no seepage was observed. Injection attempts at zone 3 of borehole SYBT-ECRB-LA#3 
(Event 77) failed because the zone was too tight. A few test events in Niche 1620 were not 
analyzed because of various difficulties (Event 78: data logger problem; Events 79 and 80: 
packer problem; Event 82: seepage partially bypassed capture system; Event 83: pump problem). 
Partial test interference with Events 83 and 84 was observed during Events 87 and 88 (see also 
discussion of Figure 17 below). 
MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
The events without any seepage cannot be used for calibration (unless jointly inverted with other 
tests that exhibit seepage), because the corresponding inverse problem would be ill posed. These 
tests (along with tests showing seepage) are therefore used for validation of the SCM. The small 
amount of water released during the short-term tests performed in Niche 3560 makes it difficult 
to reliably estimate seepage parameters on the drift scale. If used for calibration, these tests yield 
small-scale parameter values that are likely biased towards the properties of the few fractures 
connecting the release point with the niche ceiling. These fractures may not be representative of 
the fracture network taking part in the diversion of water around the entire niche, which is the 
behavior to be modeled under steady-state flow conditions. Moreover, storage effects are significant 
in short-term tests but are also poorly identifiable. For these reasons, the Niche 3650 liquidrelease 
tests are used for validation purposes only. 
April 2003 61 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
Table 11. Liquid-Release Test Events, Approximate Release Rate, Occurrence of Seepage, and Their 
Use for Calibration or Validation Purposes 
Event Starting Date 
of Test 
Borehole, 
Interval 
Approximate 
Release Rate 
[ml/min] 
Niche 3107, DTN: LB0010NICH3LIQ.001 [153144] 
1 03/10/99 UL, 5.495.80 m 1.5 
2 03/30/99 UL, 5.495.80 m 2.0 
3 09/17/99 UL, 5.495.80 m 1.5 
4 03/04/99 UM, 4.885.18 m 0.9 
5 04/07/99 UM, 4.885.18 m 5.8 
6 04/27/99 UM, 4.885.18 m 2.4 
7 04/30/99 UM, 4.885.18 m 0.8 
8 05/06/99 UM, 4.885.18 m 5.4 
9 09/21/99 UM, 4.885.18 m 5.0 
10 09/23/99 UM, 4.885.18 m 5.3 
11 09/27/99 UM, 4.885.18 m 5.4 
12 10/11/99 UM, 4.885.18 m 5.4 
Niche 3650, DTN: LB980001233124.004 [136583] 
13 12/11/97 UL, 5.185.49 m 4.7 
14 02/12/98 UL, 5.185.49 m 0.4 
15 12/11/97 UL, 5.796.10 m 12.1 
16 12/11/97 UL, 6.406.71 m 12.7 
17 12/10/97 UL, 7.017.32 m 116.9 
18 01/06/98 UL, 7.017.32 m 11.4 
19 11/13/97 UM, 4.274.57 m 121.1 
20 12/03/97 UM, 4.274.57 m 30.2 
21 12/03/97 UM, 4.274.57 m 30.4 
22 01/07/98 UM, 4.274.57 m 2.8 
23 02/10/98 UM, 4.274.57 m 1.0 
24 11/12/97 UM, 4.885.18 m 173.5 
25 12/04/97 UM, 4.885.18 m 30.4 
26 12/05/97 UM, 4.885.18 m 8.6 
27 01/08/98 UM, 4.885.18 m 2.8 
28 03/06/98 UM, 4.885.18 m 0.8 
29 11/13/97 UM, 5.495.79 m 124.1 
30 12/04/97 UM, 5.495.79 m 30.2 
31 01/09/98 UM, 5.495.79 m 3.5 
32 02/11/98 UM, 5.495.79 m 0.8 
62 MDL-NBS-HS-000004 REV02 
U0080 
Seepage? 
No 
No 
No 
No 
? 
Yes 
No 
Yes 
Yes 
Yes 
Yes 
Yes 
No 
No 
No 
No 
Yes 
No 
Yes 
Yes 
Yes 
Yes 
No 
Yes 
Yes 
Yes 
No 
No 
Yes 
Yes 
Yes 
No 
Calibration, 
Validation 
V 
V 
V 
C 
 
C 
V 
C 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
V 
April 2003 Seepage Calibration Model and Seepage Testing Data 
Table 11 (cont.). Liquid-Release Test Events, Approximate Release Rate, Occurrence of Seepage, 
and Their Use for Calibration or Validation Purposes 
Starting Date 
of Test 
11/03/1999 
11/30/1999 
01/24/2000 
06/26/2000 
05/11/2000 
05/17/2000 
05/23/2000 
05/23/2000 
06/01/2000 
05/17/2000 
05/23/2000 
06/01/2000 
06/14/2000 
Event 
40 
41 
42 
43 
52 
53 
54 
55 
56 
57 
58 
59 
60 
33 11/13/1997 UM, 6.106.40 m 30.8 
34 12/04/1997 UM, 6.106.40 m 11.5 
35 01/12/1998 UM, 6.106.40 m 47.5 
36 01/14/1998 UR, 4.274.57 m 11.9 
37 02/05/1998 UR, 4.274.57 m 
38 01/15/1998 UR, 4.885.18 m 11.4 
39 02/06/1998 UR, 4.885.18 m 
44 11/16/1999 UM, 6.106.40 m 5.5 
45 12/10/1999 UM, 6.106.40 m 2.3 
46 02/09/2000 UM, 6.106.40 m 0.5 
47 03/14/2000 UM, 6.106.40 m 0.5 
48 06/08/2000 UM, 6.106.40 m 1.2 
49 12/07/1999 UR, 5.185.48 m 
50 01/05/2000 UR, 5.185.48 m 
51 02/14/2000 UR, 5.185.48 m 
SYBT-ECRB-LA#2, DTN: LB00090012213U.002 [153154] 
Niche 4788, DTN: LB0010NICH4LIQ.001 [153145] 
Approximate 
Release Rate 
[ml/min] 
3.3 
3.2 
5.5 
3.1 
0.5 
1.2 
5.5 
2.4 
0.5 
>450 
34.9 
26.3 
29.5 
31.6 
16.8 
26.1 
35.6 
37.8 
MDL-NBS-HS-000004 REV02 
Borehole, 
Interval 
UL, 7.627.93 m 
UL, 7.627.93 m 
UL, 7.627.93 m 
UL, 7.627.93 m 
LA#2, zone 1 
LA#2, zone 1 
LA#2, zone 1 
LA#2, zone 2 
LA#2, zone 2 
LA#2, zone 3 
LA#2, zone 3 
LA#2, zone 3 
LA#2, zone 3 
63 
U0080 
Seepage? 
No 
No 
No 
Yes 
No 
Yes 
No 
Yes 
Yes 
No 
Yes 
Yes 
Yes 
? 
No 
Yes 
Yes 
Yes 
Yes 
Yes 
Yes 
Yes 
Yes 
Yes 
No 
No 
No 
Yes 
Calibration, 
Validation 
V 
V 
V 
V 
V 
V 
V 
V 
C 
V 
C 
V 
C 
 
V 
C 
V 
C 
C 
V 
V 
V 
V 
V 
V 
V 
V 
V 
April 2003 Seepage Calibration Model and Seepage Testing Data 
Table 11 (cont.). Liquid-Release Test Events, Approximate Release Rate, Occurrence of Seepage, 
and Their Use for Calibration or Validation Purposes 
Starting Date 
of Test 
10/23/2000 
11/27/2000 
10/23/2000 
11/27/2000 
02/28/2001 
04/03/2001 
04/09/2001 
04/17/2001 
04/25/2001 
05/17/2001 
05/23/2001 
05/17/2001 
06/20/2001 
07/05/2001 
07/13/2001 
07/16/2002 
05/17/2001 
05/06/2002 
05/06/2002 
Event 
61 
62 
63 
64 
65 
66 
67 
68 
69 
70 
71 
72 
73 
74 
75 
76 
77 
78 
79 
SYBT-ECRB-LA#2, DTN: LB0110SYST0015.001 [160409] 
SYBT-ECRB-LA#1, DTN: LB0110ECRBLIQR.002 [156879] 
SYBT-ECRB-LA#3, DTN: LB0203ECRBLIQR.001 [158462] 
80 05/17/2002 #2, 2122 ft 
81 05/16/2002 #5, 2829 ft 
82 05/21/2002 #5, 2829 ft 
83 07/17/2002 #3, 2122 ft 
84 07/29/2002 #3, 2122 ft 
85 08/14/2002 #3, 2122 ft 
86 07/15/2002 #5, 2829 ft 
87 07/31/2002 #5, 2829 ft 
88 08/05/2002 #5, 2829 ft 
Approximate 
Release Rate 
[ml/min] 
33.0 
35.3 
38.0 
40.8 
17.0 
41.2 
43.9 
44.5 
43.1 
36.4 
24.7 
71.2 
31.2 
65.7 
47.9 
32.4 
0.0 
Niche 1620, DTN: LB0207NICH5LIQ.001 [160408] 
72.0 
120.0 
120.0 
60.0 
72.0 
Niche 1620, DTN: LB0209NICH5LIQ.001 [160796] 
55.0 
33.0 
9.0 
25.8 
25.8 
11.3 
MDL-NBS-HS-000004 REV02 
Borehole, 
Interval 
LA#2, zone 2 
LA#2, zone 2 
LA#2, zone 3 
LA#2, zone 3 
LA#1, zone 2 
LA#1, zone 2 
LA#1, zone 2 
LA#1, zone 2 
LA#1, zone 2 
LA#3, zone 1 
LA#3, zone 1 
LA#3, zone 2 
LA#3, zone 2 
LA#3, zone 2 
LA#3, zone 2 
LA#3, zone 2 
LA#3, zone 3 
#5, 2829 ft 
#2, 2122 ft 
64 
U0080 
Seepage? 
Yes 
Yes 
Yes 
Yes 
No 
Yes 
Yes 
Yes 
Yes 
No 
Yes 
No 
No 
No 
No 
No 
No 
Yes 
No 
No 
Yes 
Yes 
Yes 
Yes 
Yes 
Yes 
Yes 
Yes 
Calibration, 
Validation 
C 
C 
C 
C 
C 
C 
C 
C 
C 
C 
C 
V 
V 
V 
V 
V 
 
V 
 
 
V 
 
 
 
 
C 
V 
V 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
Table 11 (cont.). Liquid-Release Test Events, Approximate Release Rate, Occurrence of Seepage, 
and Their Use for Calibration or Validation Purposes 
Event Starting Date 
of Test 
Borehole, 
Interval Seepage? 
Yes 
No 
Approximate 
Release Rate 
[ml/min] 
Niche 1620, DTN: LB0211NICH5LIQ.001 [160792] 
9.9 89 09/17/2002 #4, 1011ft 
4.8 90 10/01/2002 #4, 1011ft 
Calibration, 
Validation 
C 
V 
April 2003 
6.5.4 Relative Humidity and Evaporation Rate Measurements 
Reduced relative humidity in the ESF Main Drift, the ECRB Cross Drift, and the niches lead to 
partial evaporation of the water that reaches the opening, effectively reducing seepage. Neglecting 
evaporation effects in a seepage prediction model leads to higher seepage rates and is thus 
conservative. However, an overestimation of seepage in a model used for parameter determination 
would be compensated by a nonconservative increase in the estimated capillary-strength 
parameter. Following the recommendations made to address the evaporation issue (CRWMS 
M&O 2001 [153045], Section 7.5), humidity in the closed-off Niches 3107 and 4788 was artificially 
increased to reduce the evaporation potential, and relative humidity was monitored (BSC 
2001 [158463], Figures 6.2.1-4 and 6.2.1-5). In the systematic testing area, additional curtains 
were installed on the two ends of the V-shaped seepage capture PVC curtains (BSC 2001 
[158463], Figure 6.11.1-2) to reduce air circulation in the ventilated ECRB Cross Drift (after 
June 2000). In addition, relative humidity and evaporation rates from an open pan were measured 
(see, for example, BSC 2001 [158463], Figures 6.11.2-8 through 6.11.2-11). Relative humidity 
and evaporation rate were also measured in Niche 1620 (DTN: LB0207NICH5LIQ.001 [160408] 
and DTN: LB0211NICH5LIQ.001 [160792]). 
The evaporation-rate data will be used to estimate the thickness of the diffusive boundary layer 
(see Section 6.6.1.4). The relative-humidity data will be applied as a time-dependent boundary 
condition determining the water potential in the opening. 
65 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
6.6.1 Mathematical Model 
The mathematical model for unsaturated flow is based on the conceptual model outlined in the 
previous sections. The basic theoretical foundation for unsaturated flow in a continuum is 
outlined first, with a short discussion of the capillary pressure curve and its relevance for seepage 
(Sections 6.6.1.1 and 6.6.1.2). The incorporation of evaporation from a wetted porous surface is 
described in Sections 6.6.1.3 and 6.6.1.4. Section 6.6.1.5 contains a summary description of the 
inverse modeling methodology. 
S = q + q + (1) q z y x 
6.6 MODEL FORMULATION 
  
t 
 
  x 
k r = + k  z g P (2) c z 
 
 
P
x 
 
 

 z 
k 
6.6.1.1 Unsaturated Flow 
Flow in unsaturated porous or fractured media is described by the rate of change in liquid saturation 
and the flow rate at any given point. The continuum concept (see Section 6.3.2) stipulates 
the following equation of continuity, which describes the rate at which liquid saturation changes 
at a given point (Bear 1972 [156269], pp. 496, Equation 9.4.39): 
= 
 
 
k q x k 

 
 
 
  
y z 
Here, t [s] is time,  [dimensionless] is porosity, S [dimensionless] is liquid saturation,  [kg 
m-3] is liquid density, and q [kg m-2 s-1] is the flow rate along the principal axes ( x , y , and z ). 
Considering that liquid flow is driven by gravity and pressure gradients (see Section 6.3.2), the 
liquid-flow rate is described by the Buckingham-Darcy law as follows (after Bear 1972 
[156269], pp. 487.488, Equations 9.4.20 and 9.4.21): 
c c r r , q , and z y y x 
r k
P
y 
Here, k [m2] is absolute permeability, kr [dimensionless] is relative permeability,  [Pa.s] is 
liquid viscosity, g [m s-2] is gravitational acceleration, z [m] is the vertical coordinate (positive 
upward), and Pc [Pa] is the (negatively defined) capillary pressure. Substituting Equation (2) into 
Equation (1) leads to the governing equation of flow in unsaturated porous media (after Bear 
1972 [156269], p. 496, Equation 9.4.41): 
k  
 
k  
 
(3) g  z .. 
q = 
c 

t 
. m . m S S e e r 1 ..
.. 
( ) 
(4) 
April 2003 
P( ). . 
  S = div  + .. 
In Richards equation, the relative permeability ( kr ) and capillary pressure ( Pc ) are functions of 
liquid saturation as given, for example, by van Genuchtens model (after van Genuchten 1980 
[100610], after Equations [8] and [3]): 
/ 1 2 / 1 k = 
MDL-NBS-HS-000004 REV02 
. 1.( ) 2 
66 Seepage Calibration Model and Seepage Testing Data 
In van Genuchtens equations, the effective saturation, Se , is defined as 
 
104 
103 
The parameter m determines the slopes of the capillary pressure and relative permeability 
functions. It is a measure of the spread of the effective pore size distribution; a large m value 
implies a narrow pore size distribution. The use of continuous relative-permeability and 
capillary-pressure functions, which apply to porous media, is considered appropriate also for 
small fracture segments that are rough-walled and/or partially filled with porous material. 
<
m = 0.9 102 
101
0 
Figure 5. (a) Capillary-pressure curves and (b) relative-permeability curves for different illustrative 
Effective Saturation, S 
van Genuchten parameters. 
Effective Saturation, S 
lr S is residual liquid saturation, and  where < m 
fitting parameters. The roles of the parameters in the capillary pressure and relative permeability 
functions are illustrated in Figure 5. The parameter  1 describes the point of inflection in the 
capillary-pressure function (Equation (5)) shown in Figure 5a. The factor  1 scales the 
capillary pressure curve and is therefore referred to as the capillary-strength parameter. 
. Slr
0 / 1 > 
67 
Relative Permeability, kr 
(b) 
.1 1[ ]m 
(6) e 
S . Slr 
1 
[Pa] and 0 
1 
0.8 
0.6 
0.4 
0.2
0
0 
Capillary Pressure, -Pc [Pa] 
(a) 
6.6.1.2 Onset of Seepage 
For a circular opening in a homogeneous medium, the threshold for liquid entry into the cavity is 
full saturation at the apex (Philip et al. 1989 [105743]). For the liquid that enters the opening to 
MDL-NBS-HS-000004 REV02 
U0080 
1. .1/m . = S P (5) e c 
1 [dimensionless] are 
m = 0.9 
m = 0.5 
m = 0.9 
S =
1 
1/ = 100 Pa 
0.2 0.4 0.6 0.8 
m = 0.5 
0.2 0.4 0.6 0.8 1 
1/ = 1000 Pa
e e 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
form a drop at the opening wall and detach (see definition of seepage in Section 6.1.2), a positive 
pressure that offsets the drop pressure is required (Or and Ghezzehei 2000 [144773], pp. 390- 
392). 
For a numerical model in which the continuum is discretized into discrete gridblocks, the 
condition for seepage is determined by the total water-potential gradient at the connection 
between the fractured medium and the opening as depicted in Figure 6. From Equation (2) it 
z q follows that downward seepage in a discrete numerical mesh, 0 > , occurs only when the 
following condition is satisfied: 
P + g .z >0 (7) c 
where c P is the capillary pressure at the last node adjacent to the opening. Given that the 
capillary pressure in the opening is zero, the numerical threshold capillary pressure is defined as 
. = . g .z , where .z is the distance between the last node and the opening. The numerical c 
. 
P 
threshold capillary pressure c P therefore depends on the nodal distance between the last node 
and the opening. The opening surface does not need to be fully saturated for seepage to 
commence as given by the analytical solutions of Philip et al. (1989 [105743]). As indicated in 
Figure 6, given a numerical grid, the seepage-threshold liquid saturation is lower for larger 
z . and for lower capillary strength (  1 ). Consequently, whether liquid that reaches the surface 
seeps or is diverted around the opening (effectiveness of the capillary barrier) is primarily 
determined by the  1 parameter. Note that the relative permeability function (Equation (4)) 
does not depend on  1 . Hence, the capillary-strength parameter is the main subject of the SCM 
presented in this report (see also discussion in Section 6.6.3.1). The fact that the seepage threshold 
depends on the length of the nodal distance to the opening makes the values of the estimated 
capillary-strength parameter (  1 ) applicable only to numerical models of comparable 
discretization (Section 6.6.2.2). 
Figure 6 shows that a reasonable variation in the m parameter has only a limited effect on the 
seepage threshold saturation; a stronger effect is seen for a change in  / 1 , which tends to vary 
more than m . Therefore, fixing the parameter m appears reasonable as confirmed by the formal 
sensitivity analysis (see Section 6.6.3.1 below). Moreover, any potential variability of m is 
accounted for in the calibrated  1 parameter. The relative sensitivity and potential identifiability 
of seepage-relevant parameters are further discussed in Section 6.6.3.1. 
MDL-NBS-HS-000004 REV02 April 2003 68 Seepage Calibration Model and Seepage Testing Data 
Pc
* 
a<b
a
* 
b
S 
a 
Effect of m 
c>d 
Pc
* d
c 
Pc
* 
q
.z 
z 
Effect of 1/.
S 
Mw C = 
seepage threshold saturation than a change in m . 
d x 
exp.  
P
T R 
P M . . c
T R 
where M [0.01802 kg mol-1] is the molecular mass of water, R [8.314 J K-1 mol-1] is the 
universal gas constant, P [Pa] is the saturated vapor pressure, T [K] is the temperature, and the 
expression )] exp[P M /( RT denotes the relative humidity (Ho 1997 [141521], Eq. 10). The 
vapor concentration of bulk air of the opening (C ) is related to the relative humidity h by 
Figure 6. Schematic description of seepage condition. A change in  1 has a greater impact on the 
w (9) .. 
April 2003 
6.6.1.3 Incorporation of Evaporation Effects 
Part of the liquid that reaches the surface of the underground opening evaporates by virtue of the 
vapor concentration gradient at the surface. Considering that the evaporation is an isothermal 
diffusive process, the evaporative flux ( qe [kg m-2 s-1]) applied at the wall of the opening is given 
by: 
dC qe = D (8) 
where D [m2 sec.1] is the vapor diffusion coefficient and C [kg m.3] is the vapor concentration. 
The vapor concentration at the surface of the opening (Co ) is related to the capillary pressure by 
Kelvinfs equation (after Campbell and Norman 1998 [150929], Eqs. 3.11 and 3.17): 
o sat 
w 
sat 
 w c 
69 MDL-NBS-HS-000004 REV02 
U0080 
Sb
* 
Sa
* 
b
* U0080 Seepage Calibration Model and Seepage Testing Data 
P . w sat C . (10) 
8 . 1 
M . h 
R .T 
The vapor concentration undergoes a gradual transition from Co to C within a finite distance 
away from the opening surface, here referred to as the evaporative boundary layer, whose 
thickness ( _ ) is inversely related to the airflow velocity (e.g., Rohsenow and Choi 1961 
[158324], pp. 36V40). The vapor concentration gradient is presumed linear within the boundary 
layer. Then, Equation (8) can be rewritten as: 
o 
C . C 
q = D (11) 
_ 
The vapor diffusion coefficient depends on temperature and pressure as given by (Pruess 1987 
[100684], pp. 5V6]: 
. D = 
= 
e 
.10 o D 
. 
c P 
The available evaporation data are grouped into three classes based on airflow velocity; (1) 
inside Niche 1620 without ventilation, (2) outside of Niche 1620 with active ventilation, and (3) 
outside of Niche 1620 without active ventilation, the regime usually encountered during nights 
and weekends. In Figure 7 and Figure 8, the relative humidity, temperature and measured and 
fitted evaporation rates are plotted for inside and outside of Niche 1620, respectively (Wang 
2003 [161456], SN-LBNL-SCI-223-V1, pp. 22V25). 
5 . 
. T 
. .
P  . . .
. . 
273.15 
. (12) 
 
Do = 2.13  10-5 m2 s-1 is the vapor diffusion coefficient at standard conditions of where 
T = 273.15 K and P = 105 Pa. 
The implementation of evaporation effects into iTOUGH2 V5.0 (LBNL 2002 [160106]) is 
described in detail in BSC (2002 [161067], Section 1.2). 
April 2003 
6.6.1.4 Estimation of Evaporative Boundary-Layer Thickness 
The thickness of the evaporative boundary layer ( _ , see Equation (11)) can be estimated by 
calibration using evaporation data measured under known vapor concentration and temperature 
conditions. The _ values employed in this Model Report were obtained by calibration using 
free-water evaporation data collected inside and outside of Niche 1620 (DTN: 
LB0207NICH5LIQ.001 [160408]) (Section 6.5.4). The vapor concentration at the surface of free 
water is given by Equation (9) with 0 = Pa. 
70 MDL-NBS-HS-000004 REV02 M T W T F S S M T W T F S S M T W T F 
132 
Figure 7. Relative humidity, temperature, and measured and fitted evaporation rates from experiments 
conducted outside Niche 1620 (DTN: LB0207NICH5LIQ.001 [160408]). Relative 
humidity is higher during nights and weekends, and evaporation is decreased accordingly. 
Measured 
Model 
146 
132 
139
Day of Year 2002
Relative Humidity 
139 
Seepage Calibration Model and Seepage Testing Data 
Evaporation Rate (m/day) Evaporation Rate (m/day) 
Relative Humidity Relative Humidity 
1 
0.75 
0.5 
0.25
0 132 
0.012 
0.01 
0.008 
0.006 
0.004 
0.002
0
1 
0.75 
0.5 
0.25
0 
0.002 
0.0015 
0.001 
0.0005
0 
139 
M T W T F S S M T W T F S S M T W T F 
132 
Figure 8. Relative humidity, temperature, and measured and fitted evaporation rates from experiments 
conducted inside Niche 1620 (DTN: LB0207NICH5LIQ.001 [160408]) 
Measured 
Model 
146 139
Day of Year 2002 
MDL-NBS-HS-000004 REV02 
Relative 
Humidity 
71 
Temperature (C) 
April 2003 
Temperature (C) 
U0080 
29 
28 
27 
26 
25 
Temperature 
146 
25 
24 
23 
Temperature 
146
U0080 Seepage Calibration Model and Seepage Testing Data 
The boundary-layer thickness was estimated by fitting Equation (11) to the evaporation data 
(Wang 2003 [161456], SN-LBNL-SCI-223-V1, pp. 2225); the estimated values are listed in 
Table 12. 
Table 12. Boundary-Layer Thickness Estimated Using Equation (11) and Relative Humidity, 
Temperature, and the Evaporation Data from a Free Water Surface Shown in Figure 7 and 
Figure 8. Boundary-layer thickness in DTN: LB0302SCMREV02.002 and reflected in 
meshes of DTN: LB0302SCMREV02.001. 
Location of Evaporation Experiment 
Inside Niche 1620 
Outside Niche 1620, Weekdays (ventilation on) 
Boundary-layer 
thickness (mm) 
20.0 
5.0 
7.5 
Outside Niche 1620 Weekends (ventilation off) 
An evaporative boundary-layer thickness  = 0.02 m was used for the simulation of liquidrelease 
tests in Niche 1620. Some of the liquid-release tests performed in the open drift of the 
ECRB were exposed to ventilation; a boundary-layer thickness  = 0.005 m was used for these 
simulations. In more recent tests, additional curtains were installed at the two ends of the Vshaped 
seepage capture curtains to reduce air circulation and thus partly protect the seepage 
section of the drift from ventilation effects; a boundary-layer thickness  = 0.0075 m was used 
for these simulations. 
r 
p z z 
TC.1 
The residual vector r contains the differences between the measured seepage rate, * z , and the 
corresponding model prediction, ) (p z , which is a function of the unknown, n -dimensional 
m , where m is the number of calibration = 1 
zz 
2 J 
i 
Cpp = s0 
Used For Simulation of 
Liquid-Release Tests in 
Niche 1620 (Niche 5) 
ECRB (no end curtains) 
ECRB (with end curtains) 
April 2003 
6.6.1.5 Summary Description of Inverse Modeling Methodology 
The inverse modeling approach followed here is based on the classical weighted least-squares 
method, which consists of minimizing the objective function 
r (13) S = zz 
* ), ) ( parameter vector p , i.e., . ( i i i r = 
points. The inverse of the covariance matrix C , which holds the expected variances of the final 
residuals on its diagonal, is used as a weighting matrix. The objective function is a measure of 
the misfit between the model output and the measured data. The objective function is automatically 
minimized using the Levenberg-Marquardt algorithm implemented in iTOUGH2 V5.0 
(Finsterle 1999 [104367], Section 2.7.4). 
The covariance matrix of the estimated parameters is asymptotically given by: 
(14) zz 
MDL-NBS-HS-000004 REV02 
TC.1J . ( )1 
72 U0080 Seepage Calibration Model and Seepage Testing Data 
m~ n Jacobian matrix holding the partial derivatives of the predicted seepage where J is an 
with respect to the unknown parameters, p j i , and 2
0 s is the estimated error variance, 
r 
= z  
TC.
zz
1 
r (15) 
pp 
Jij 
which represents the variance of the mean weighted residual; it is an aggregate measure of 
goodness-of-fit: 
2 s0 = 
zz. . 
m . n 
The impact of parameter uncertainty (expressed through matrix C ) on model predictions can 
be evaluated by means of first-order-second-moment uncertainty propagation analysis. The 
covariance matrix of the model prediction, z z. . C , is calculated based on a linearity and normality 
assumption using 
JT (16) C = JCpp 
The inverse modeling methodology and its numerical implementation are described in detail in 
the iTOUGH2 software documentation, specifically Finsterle (1999 [104367], Section 2). 
73 April 2003 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
6.6.2 Development of Forward Model 
The numerical model constructed to simulate liquid-release tests and seepage into the underground 
openings is referred to as the forward model. Different forward models were created for 
the different test locations and liquid-release events. During the inversion, the seepage rates 
calculated by the forward model are compared to the measured seepage rates at discrete points in 
time. (If the calibration time does not coincide with a data collection time, the comparison occurs 
against a value linearly interpolated between the measurements). The discrepancies between the 
two rates are then used to automatically update the input parameters of the forward model. The 
solution to both the forward and inverse problem is calculated by iTOUGH2 V4.0 (LBNL 1999 
[139918]) and V5.0 (LBNL 2002 [160106]). 
6.6.2.1 Generation of Permeability Field 
Air-injection tests performed in borehole intervals at the experimental sites were used to estimate 
effective permeabilities (see Section 6.5.2, Table 10). The spatial structure of the permeability 
data was analyzed, and the resulting geostatistical parameters were used to generate spatially 
correlated permeability fields (for details, see Attachment III, Attachment IV, and Attachment 
V). Multiple realizations of the permeability field were simulated by changing the seed number 
of the random-number generator of the software SISIM V1.203 (LBNL 1999 [134136]) and 
V1.204 (LBNL 2000 [153100]) (see Figure III-5). The permeability fields were eventually 
mapped onto the numerical grid (see Section 6.6.2.2). 
The GSLIB modules GAMV2 V1.201 (LBNL 1999 [134139]) and GAMV3 V1.201 (LBNL 
2000 [153099]) were used to analyze spatial correlation of, respectively, two-dimensional and 
three-dimensional, irregularly spaced, log-transformed air-permeability data. Sequential indicator 
simulation (Deutsch and Journel 1992 [100567], p. 151) as implemented in the GSLIB modules 
SISIM V1.203 (LBNL 1999 [134136]) and V1.204 (LBNL 2000 [153100]) was used to generate 
spatially correlated, random fields of log-transformed permeability modifiers (see Figure III-2). 
Borehole SYBT-ECRB-LA#2, Lower Lithophysal Zone 
Six air-injection tests were performed in 6 ft (approximately 1.8 m) long intervals of borehole 
SYBT-ECRB-LA#2 (DTN: LB00090012213U.001 [153141]), providing an estimate of mean 
log-permeability at the experimental site of -10.73 (corresponding to a permeability of 1.86  
10-11 m2) with a standard deviation of 0.21 (see Table 10). Variability in permeability on the 
scale of a gridblock (which is 1 ft long) is expected to be higher than the standard deviation 
reported in Table 10. For the purpose of generating a heterogeneous field, permeability is taken 
to be log-normally distributed with a standard deviation of one order of magnitude. The number 
of data points was insufficient to reveal the spatial correlation structure of the permeability field. 
A weak spatial correlation was prescribed (consistent with the geostatistical results from airpermeability 
data in the middle nonlithophysal zone, see below). A correlation length of 0.2 m 
was specified. Multiple realizations of the permeability field were generated. 
74 
MDL-NBS-HS-000004 REV02 April 2003 Seepage Calibration Model and Seepage Testing Data 
Niche 1620, Lower Lithophysal Zone 
A total of 61 air-injection tests were conducted in three boreholes (boreholes #2, #3, and #5) 
above Niche 1620 (DTN: LB0110AKN5POST.001 [156904]). The length of the injection 
interval was 1 ft. The mean and standard deviation of the log-transformed permeability values 
are provided in Table 10. The permeability values are approximately log-normally distributed as 
shown in Figure 9. 
15 
10
5
0 -12 -13 
MDL-NBS-HS-000004 REV02 
Frequency 
Figure 9. Cumulative frequency distribution of the log-transformed permeability values and corresponding 
cumulative normal probability density function for Niche 1620. Permeability data 
from DTN: LB0110AKN5POST.001 [156904]; histogram and cumulative probability distribution 
in DTN: LB0302SCMREV02.001. 
The post-excavation air-permeability data were geostatistically analyzed using the software 
GAMV3 V1.201 (LBNL 2000 [153099]) to calculate the empirical semivariogram specific to 
Niche 1620. The nugget effect, correlation length, and sill values were determined by fitting a 
spherical semivariogram (Deutsch and Journel 1992 [100567], p. 23) to the empirical 
semivariogram (Wang 2003 [161456], SN-LBNL-SCI-223-V1, p. 16). Figure 10 shows the 
empirical semivariogram and corresponding theoretical spherical semivariogram of Niche 1620. 
The geostatistical parameters are provided in Table 13 below. The generated spatially correlated 
permeability field is conditioned on the measured post-excavation air-permeability data as shown 
in Figure 11. The stochastic simulation approach may generate permeability values that are 
considerably different from those at the neighboring conditioning points, i.e., the field is more 
heterogeneous than one created by means of an interpolation technique. Multiple realizations 
were generated. 
log(k [m2]) 
75 
1
0.6 
0.2 
0 -10 -11 -8 -9 
Cumulative Probability 
0.8 
0.4 
U0080 
April 2003 U0080 
Niche 1620 
Spherical semivariogram
4 2 6 
Seepage Calibration Model and Seepage Testing Data 
2.5
2 
1.5 Empirical semivariogram 
log(k [m2]) Semivariogram [log(k [m2])2] 
1 
0.5
00 
-8 
-9 
-10 
-11 
-12 
-13 
-14 16 
Lag-Distance [m] 
Figure 10. Empirical post-excavation air-permeability semivariograms and spherical semivariogram 
model for Niche 1620. See Table 13 for geostatistical parameters of the spherical 
semivariogram model. Permeability data from DTN: LB0110AKN5POST.001 [156904]; 
semivariogram in DTN: LB0302SCMREV02.001. 
Niche 1620, Borehole #3 
Permeability data 
18 
Generated permeability 
22 20 
Y-axis [m from datum] 
Figure 11. Post-excavation permeability data of Niche 1620, borehole #3 and the corresponding 
generated permeability values from one representative realization, which honors the 
measured data. Permeability data from DTN: LB0110AKN5POST.001 [156904]; generated 
permeabilities in DTN: LB0302SCMREV02.001. 
April 2003 76 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
Niches 3107, 3650, and 4788, Middle Nonlithophysal Zone 
A total of 225 air-injection tests were performed in 10 boreholes above Niche 3107 (DTN: 
LB990601233124.001 [105888]), Niche 3650 (DTN: LB0011AIRKTEST.001 [153155]), and 
Niche 4788 (DTN: LB990601233124.001 [105888]). The mean, standard deviation, and number 
of air-permeability data for each niche are shown in Table 10. 
For Niche 3650, the software GAMV2 V1.201 (LBNL 1999 [134139]) was used to calculate the 
empirical semivariogram, given that all intervals in boreholes UL, UM, and UR lie within a twodimensional 
plane. The appropriateness of this presumption was confirmed by surveyed borehole 
alignments for Niche 3650 (DTN: MO0002GSC00076.000 [152623]). For Niches 3107 and 
4788, the software GAMV3 V1.201 (LBNL 2000 [153099]) was used to calculate the empirical 
semivariogram. The three-dimensional coordinates of the permeability data were taken from the 
detailed borehole alignment surveys (DTN: MO0002GSC00064.000 [152625] and DTN: 
MO0107GSC01069.000 [156941]). 
1.0 
0.9 
0.8 
0.7 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1 
MDL-NBS-HS-000004 REV02 
Niche 4788 
0.00 1 2 3 4 5 6 7 8 9 
Figure 12. Empirical post-excavation air-permeability semivariograms and fitted spherical 
semivariogram models for Niches 3107, 3650, and 4788. See Table 13 for geostatistical 
parameters of the spherical semivariogram models. Permeability data from DTN: 
LB990601233124.001 [105888] and DTN: LB0011AIRKTEST.001 [153155]; 
semivariograms in DTN: LB0010SCMREV01.001 [154292]. 
Spherical semivariogram models (Deutsch and Journel 1992 [100567], p. 23) with the geostatistical 
parameters shown in Table 13 are used to represent the empirical log-permeability 
semivariograms. The empirical semivariograms (symbols) and the corresponding spherical 
semivariogram models (lines) are shown in Figure 12. Note that the relatively large correlation 
length obtained for Niche 3650 should not be misinterpreted as suggesting that the permeability 
field is strongly correlated. All three semivariograms shown in Figure 12 exhibit either a short 
correlation length (i.e., on the order of 1 meter or less) or a nugget effect that is close to the sill 
Niche 3650 
77 
U0080 
Niche 3107 
Lag-Distance [m] 
April 2003 Seepage Calibration Model and Seepage Testing Data 
value. It can therefore be concluded that the permeability is random without a noticeable or 
significant spatial correlation. No nugget effect is evident for the Niche 3107 data, resulting in a 
permeability field that is slightly spatially correlated (see Figure 16c below). 
Table 13. Geostatistical Parameters of Spherical Semivariogram Models (DTN: LB0302SCMREV02.002) 
10-10 
April 2003 
[m] 
Niche Nugget effect Correlation length 
[log(k)2] 
Niche 1620 
Niche 3107 
Niche 3650 
Niche 4788 
The spherical semivariogram models, along with the cumulative distribution functions shown in 
Figure 13, are used as input to the software SISIM V1.203 (LBNL 1999 [134136]) for Niches 
3107 and 4788; the software SISIM V1.204 (LBNL 2000 [153100]) is used for Niche 3650. The 
random permeability field is conditioned on the measured post-excavation air-permeability data. 
For Niches 3107 and 4788, coordinates are added to the permeability field using software 
AddCoord V1.0 (LBNL 2000 [152814]). The resulting permeability fields are mapped onto the 
numerical grid of the SCM for each of the niches, as described below in Section 6.6.2.2. Only 
one permeability field is produced for each niche. The generation of permeability fields is 
documented in Scientific Notebooks Finsterle (1999 [153448], p. 139) and Ahlers (2002 
[161045], pp. 13, 1519, 21, 3940, 58). 
0.02 
0.01 
0.40 
0.29 
1 
0.9 
0.8 
0.7 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1
0 
Figure 13. Cumulative distribution functions of air permeabilities for Niches 3107, 3650, and 4788. 
Permeability data from DTN: LB990601233124.001 [105888] and DTN: 
LB0011AIRKTEST.001 [153155]; cumulative distribution function in DTN: 
LB0010SCMREV01.001 [154292]. 
Niche 3107 
Niche 3650 
Niche 4788 
10-13 
MDL-NBS-HS-000004 REV02 
0.91 
0.61 
3.87 
1.31 
10-11 10-12 10-14 
78 
U0080 
Sill value 
[log(k)2] 
1.81 
0.49 
0.53 
0.55 
Permeability [m2]
U0080 Seepage Calibration Model and Seepage Testing Data 
6.6.2.2 Mesh Generation 
Three-dimensional meshes of a section of the ECRB Cross Drift and Niches 1620, 3107, 3650, 
and 4788 were created in several steps. The following general steps were followed for all the 
meshes. Detailed and specific descriptions pertaining to the Cross Drift and different niches are 
provided in Attachment III, Attachment IV, and Attachment V. 
1. A primary 3D mesh is generated, consisting of regular gridblocks. The Y-axis is aligned 
with the drift or niche axis. 
2. Constants are added to the coordinates of the primary mesh using software MoveMesh 
V1.0 (LBNL 2000 [152824]) to shift the origin of the mesh to an appropriate datum. 
3. A random, spatially correlated field of log-permeability modifiers is generated using software 
SISIM V1.203 and SISIM V1.204 (LBNL 1999 [134136]; LBNL 2000 [153100]) as 
described in Section 6.6.2.1. Multiple realizations are created for locations in the lower 
lithophysal zone. 
4. The heterogeneous field of log-permeability modifiers is mapped onto the mesh using 
software Perm2Mesh V1.0 (LBNL 2000 [152826]). 
5. For the tests in the ECRB Cross Drift, a cylindrical drift is cut from the primary mesh 
using the software CutDrift V1.0 (LBNL 2000 [152816]); for Niche 3650, a smooth 
niche is cut using software CutNiche V1.3 (LBNL 2000 [152828]); for Niches 1620, 
3107, and 4788, an irregularly shaped niche is cut using software CutNiche V1.2 (LBNL 
2000 [152815]). 
6. Software AddBound V1.0 (LBNL 2000 [152823]) is used to attach boundary elements at 
the top and bottom of the model domain. The bottom boundary gridblock is assigned to a 
special material domain to allow specifying a free-drainage boundary condition. 
7. Gridblocks along the boreholes are modified to represent the injection intervals. For the 
inclined boreholes in the ECRB Cross Drift, software AddBorehole V1.0 (LBNL 2000 
[152822]) was used for this task. 
8. The drift or niche gridblocks are assigned a large volume so that Dirichlet boundary 
conditions can be specified. Flux into these gridblocks represents seepage. 
9. For the tests in the ECRB Cross Drift and Niche 1620, new evaporation gridblocks are 
added and connected to the same formation elements as do the drift and niche gridblocks, 
respectively. The nodal distance from the formation gridblocks to the evaporation gridblocks 
is set to the diffusive boundary-layer thickness (see Table 12). Flux into these 
elements represents evaporation. 
10. A single time step is performed using a generic TOUGH2 input onestep file (as input to 
iTOUGH2 V4.0 or V5.0; see Figure III-4) to test the mesh and to obtain cross-referencing 
information. 
MDL-NBS-HS-000004 REV02 April 2003 79 U0080 Seepage Calibration Model and Seepage Testing Data 
respectively. 
Typical meshes created for the simulation of liquid-release tests in the ECRB Cross Drift, Niche 
1620, and Niches 3107, 3650, and 4788 are shown in Figure 14, Figure 15, and Figure 16, 
-9.0 8
6
4
2
0
-2 
0 1 
2 0 1 3 2 3 4 
X 
[m] 
Y 
[m] 
Z [m] 
log(k [m2]) 
-9.5 
-10.0 
-10.5 
-11.0 
-11.5 
-12.0 
Figure 14. Numerical grid with one realization of the permeability field used for the simulation of 
liquid-release tests conducted in zone 2 of borehole SYBT-ECRB-LA#2. Only half of the 
drift is simulated because of symmetry. The vertical position of the injection interval 
(indicated in light gray) is appropriately adjusted for the simulation of seepage experiments 
conducted in other test zones. Multiple realizations of the permeability field are 
generated. All mesh files in DTN: LB0302SCMREV02.001. 
April 2003 80 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
(a) 
7
6
5
4
3
2
21 
(b) 
6
5
4
3
2 
16 -1 
-2 17 
-3 
-2 
-3 22 
-4 
Figure 15. Numerical grid with one realization of the permeability field used for the simulation of 
liquid-release tests conducted in Niche 1620, (a) borehole #4, (b) borehole #5. In this 
visualization, the meshes are split into two parts to expose the boreholes (indicated by 
thick black lines) and the injection interval (thick white lines). Multiple realizations of the 
permeability field are generated. Note the rough ceilings as well as the left and right slots 
of Mesh (b). All mesh files in DTN: LB0302SCMREV02.001. 
log(k [m2]) 
-14 -13 -12 -11 -10 -9 -8 
2 
3 
MDL-NBS-HS-000004 REV02 
0 
-1 
0 
x [m] 
81 
U0080 
6
5
4
3
2 
16 1 
2 17 
y 
[m] 
3 x [m] 
7
6
5
4
3
2 
21 1 
22 
y 
[m] 
z [m] 
z [m] 
April 2003 Seepage Calibration Model and Seepage Testing Data 
(a) 
(c)
Figure 16. Computational meshes and permeability field for 3D seepage calibration model used for 
6.6.2.3 Boundary Conditions 
No-flow boundary conditions are specified at the left, right, front, and back sides of the model. A 
free-drainage boundary condition (Finsterle 1998 [103783], pp. 1415) is applied at the bottom 
to prevent an unphysical capillary boundary effect. All elements representing large openings 
(i.e., borehole intervals, drift sections, or niches) are assigned a zero capillary pressure independent 
of saturation. The evaporation elements are set at a capillary pressure equivalent to the 
prevailing relative humidity h according to Kelvins equation, 
MDL-NBS-HS-000004 REV02 
as discussed in Section 6.6.1.3. Water is allowed to enter, but prevented from exiting the drift or 
niche. 
A constant flux boundary condition is applied at the top of the model to represent background 
percolation. The percolation flux at the experimental site is taken from the UZ Model (DTN: 
LB990801233129.003 [122757]). (Note that slight changes in the calculated percolation flux as a 
RT 
Mw 
82 
5.0 5.0 
4.0 4.0 
3.0 3.0 
2.0 2.0 
Permeability [m2] 
1.5E-11 
5.7E-12 
2.2E-12 
8.2E-13 
3.1E-13 
1.0 1.0 
3.0 
2.0 
0.0 
4.89 
0.0 
3.67 1.0 
0.0 
Z(m) 
Z(m) 
3.0 
2.0 
Permeability [m2] 
2.0 
7.3E-12 
1.0 
2.3E-12 
1.0 
7.3E-13 
0.0 
2.3E-13 
0.0 7.3E-14 
-1.0 
-1.0 
-2.0 
3.0 9.5 10.45 2.0 1.0 0.0 -1.0 
Y(m) 
-2.0 
Z(m) 
11.0 
X(m) 
12.45 Y(m) 
(d) 
the analysis of seepage data from (a) Niche 3650, centered 4.42 m from the collar of 
borehole UM, (b) Niche 3650, centered 5.64 m from the collar of borehole UM, (c) Niche 
3107, and (d) Niche 4788. Note that the meshes are shown from an angle below horizontal 
to display the ceiling roughness incorporated into Meshes (c) and (d). All mesh files in 
DTN: LB0010SCMREV01.001 [154292]. 
ln(h) (17) . = p w c 
April 2003 
Z(m) 
-1.0 -2.0 
5.17 
X(m) 
Y(m) 
Y(m) 
(b) 
3.0 
U0080 
Permeability [m2] 
1.5E-11 
5.7E-12 
2.2E-12 
8.2E-13 
3.1E-13 
3.0 
2.0 1.0 
0.0 
-1.0 -2.0 
X(m) 
6.39 
Permeability [m2] 
1.6E-11 
5.1E-12 
1.6E-12 
5.1E-13 
1.6E-13 
3.0 2.0 1.0 0.0 
-1.0 -2.0 
X(m) 
U0080 Seepage Calibration Model and Seepage Testing Data 
result of future revisions of the UZ Model will not impact the estimates and conclusions 
presented in this Model Report). Software ECRB-XYZ V.03 (CRWMS M&O 1999 [147402]) is 
used to calculate the coordinates of Cross Drift construction station CS 1726 (Hinds 2001 
[155955], p. 124). The gridblock closest to these coordinates and those of Niches 3107, 3650, 
and 4788 are identified from the UZ Model mesh file (DTN: LB990701233129.001 [106785]), 
and the corresponding percolation flux for the present-day, mean infiltration scenario is extracted 
from the UZ Model output file (DTN: LB990801233129.003 [122757]) (Ahlers 2002 [161045], 
pp. 2931, 45, 55). 
The resulting percolation flux of approximately 13.6 mm/yr is injected into a single boundary 
element connected to all gridblocks across the top of the ECRB Cross Drift and Niche 1620 
model domains. Percolation fluxes of approximately 2.54 mm/yr for Niche 3107, 2.80 mm/yr for 
Niche 3650, and 2.02 mm/yr for Niche 4788 are injected at the top of the respective model 
domains. Note that the inflow into the model is non-uniform as a result of the heterogeneity in 
the permeability field. 
As evident from Figure 18, the average background percolation flux is significantly less than the 
local flux induced by releasing water from the injection intervals. The impact of the background 
percolation flux on simulated seepage rates is thus very limited. 
For the simulation of liquid-release tests, release rates and test durations are determined for each 
event (see Table 11) and applied to the gridblocks representing the injection interval (Ahlers 
2002 [161045], pp. 810, 3435, 47; Finsterle 2002 [161043], p. 57; Wang 2003 [161456], SNLBNL-
SCI-228-V1, pp. 1617, 1920). 
6.6.2.4 Initial Conditions 
The initial saturation distribution is calculated from the steady-state flow field obtained for 
background percolation, followed by a simulation of reduced relative humidity, which creates a 
dry-out zone around the ventilated opening (Niche 1620 and ECRB Cross Drift only). 
The initial saturation distribution in the fracture continuum is generally low but nonuniform. It is 
not expected to have a significant impact on simulation results. The variability in the initial 
saturation distribution is a result of formation heterogeneities and the presence of the underground 
opening and a dry-out zone (if evaporation is simulated). Since the steady-state flow field 
changes if the input parameters are updated during the inversion, a steady-state run precedes 
each transient liquid-release test simulation performed as part of the inversion process. 
Details about the steady-state simulations performed to create initial conditions for the subsequent 
simulation of liquid-release tests can be found in Attachment VII. 
6.6.3 Inversion 
The software iTOUGH2 V4.0 (LBNL 1999 [139918]) and V5.0 (LBNL 2002 [160106]) is used 
to automatically calibrate the forward models against seepage-rate data. The iTOUGH2 V5.0 
(LBNL 2002 [160106]) program is used for calibrating liquid-release tests performed in the 
lower lithophysal zone (Tptpll; Niche 1620 and systematic seepage testing in the ECRB Cross 
Drift); these models include evaporation effects (see Sections 6.3.3.4, and 6.6.1.3). The 
MDL-NBS-HS-000004 REV02 April 2003 83 U0080 Seepage Calibration Model and Seepage Testing Data 
iTOUGH2 V4.0 (LBNL 1999 [139918]) program was used for the analysis of tests conducted in 
closed-off Niches 3107 and 4788 located in the middle nonlithophysal zone (Tptpmn), where 
evaporation is significantly reduced and thus not considered (see Sections 6.3.3.4 and 6.7). The 
parameters and data selected for model calibration are described below in Sections 6.6.3.1 and 
6.6.3.2, respectively. The results of the inversions are discussed in Section 6.6.3.3. 
6.6.3.1 Parameter Selection 
Inverse modeling requires selecting one or more parameters that are considered unknown or 
uncertain and that are to be adjusted to match the model calculations to the observed data. All the 
other input parameters to the numerical model, including model-domain geometry as well as 
initial and boundary conditions, are fixed during the inversion and are thus by definition part of 
the model structure. The estimated parameters are optimal for and depend on this model 
structure. 
The selection of the parameter to be estimated can be based on (1) the physical understanding of 
the system behavior as it relates to the observed data, (2) a sensitivity analysis, or (3) a synthetic 
inversion using a derivative-based algorithm, which reveals both the sensitivity coefficients and 
parameter correlations. In a first step, the parameters most likely to affect seepage rates are 
selected, based on the understanding of the physical system behavior. Subsequently, these 
parameters are subjected to a synthetic inversion to identify the most sensitive parameters and 
their correlation structure. Finally, a selection of the parameters to be estimated is made based on 
their overall sensitivity, relative independence, and the availability and reliability of prior 
knowledge. 
The seepage process and impact of parameterized hydrogeologic properties on seepage rates has 
been discussed in Section 6.3.3. To summarize, the seepage rates observed during liquid-release 
tests are most strongly affected by the following parameters: 
1. Parameters of the capillary pressure function are expected to affect seepage rates because 
they determine the effectiveness of the capillary barrier. The two parameters of interest are 
the van Genuchten capillary-strength parameter 1/  and m , which is related to the pore size 
distribution index. Both parameters have been discussed in Section 6.6.1.1. 
2. Effective permeability impacts the flow-diversion capability of the fractured formation and 
thus seepage rates. 
3. Porosity can be interpreted as an effective parameter capturing storage effects. Storage 
effects may be significant at early times, for short-duration experiments, and if only a small 
amount of water is injected (as in the liquid-release tests conducted in Niche 3650). 
. 
A synthetic inversion (using the layout and test conditions of the liquid-release test conducted in 
zone 2 of borehole SYBT-ECRB-LA#2) was conducted to determine the sensitivities and correlation 
structure of the four parameters (1) log(  / 1 ), where  / 1 [Pa] is the van Genuchten 
capillary-strength parameter, (2) n [dimensionless], which is related to the van Genuchten 
parameter m by n = , (3) log( k ), where k [m2] is the reference permeability of the 1 /( 1 m) 
heterogeneous permeability field, and (4) log( ), where  [dimensionless] is the effective 
April 2003 84 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
porosity. The residual liquid saturation (another parameter of the relative-permeability and 
capillary-pressure functions) is expected to be much less important as seepage is initiated near 
full saturation. A separate sensitivity study was performed to examine the impact of the evaporation 
boundary-layer thickness  (see Section 6.6.1.4) on the estimated parameters. The key 
parameter log(  / 1 ) was estimated using boundary-layer thicknesses of 0.50 cm, 0.75 cm, and 
2.00 cm (see Table 12). 
The sensitivity measure reported below is the sum of the absolute values of the sensitivity 
coefficients, which is defined as the partial derivative of the calculated seepage rate with respect 
to the parameter of interest. The correlation coefficients are obtained from the parameter covariance 
matrix given by Equation (15). Because the inverse problem is highly nonlinear, the results 
of this synthetic analysis depends on the a priori parameter values. The values used are sufficiently 
close to the best estimates obtained by the actual inversion, i.e., there is no need to repeat 
the sensitivity analysis after calibration. The analysis should be considered qualitative in nature. 
The results from the synthetic inversion (Wang 2003 [161456], SN-LBNL-SCI-228-V1, pp. 33, 
3536) and from the sensitivity analysis regarding the evaporation boundary-layer thickness 
(Wang 2003 [161456], SN-LBNL-SCI-228-V1, pp. 2425) can be summarized as follows: 
1. The capillary-strength parameter log(  / 1 ) has the largest impact on calculated seepage rates. 
Provided that log(  / 1 )varies less than log( k ) (approximately proportional to the square-root 
of the permeability variation), both parameters are about equally important for seepage 
predictions. 
2. The two parameters log(  / 1 ) and log( k ) are strongly negatively correlated, i.e., an increase 
in seepage rates by a reduction of log(  / 1 ) can almost be completely compensated by an 
appropriate increase in log( k ). 
3. Overall, log( k ) is the parameter most strongly correlated to all other parameters, i.e., permeability 
is difficult to estimate from seepage-rate data alone. Permeability should be derived 
from independent information; this independent information is available from the air-injection 
tests (see Section 6.5.2). 
4. The van Genuchten parameter n is relatively insensitive and at the same time strongly 
correlated to all the other parameters. 
5. Porosity is the least-sensitive parameter. However, since its impact is restricted to only a 
portion of the data (i.e., the onset of seepage and early-time seepage rates), it is the leastcorrelated 
parameter. If the available data are potentially influenced by storage effects (e.g., 
data from short-term liquid-release tests with small injection volumes), porosity could be 
included in the estimation process. 
6. Changes in the evaporation boundary-layer thickness  within the range considered have a 
limited impact on the estimated parameter log(  / 1 ). Choosing a thin boundary layer of 0.75 
cm (an estimate based on evaporation and relative-humidity data in an open drift section, see 
Section 6.6.1.4) leads to a relatively low log(  / 1 ) value. 
April 2003 85 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
The sensitivity analysis and correlation structure inferred from the synthetic inversion provides 
guidance for the final selection of parameters to be subjected to estimation by automatic model 
calibration. 
The following decisions regarding parameter selection have been made: 
1. As few parameters as possible should be selected to avoid overparameterization. If the 
observed seepage rates can be successfully reproduced by the calibrated model and the 
estimated model parameters can be considered reasonable, the relative parsimony of the 
model and the small number of adjustable parameters provides confidence that the physical 
processes governing seepage are appropriately represented by the model. 
2. The capillary-strength parameter log(  / 1 ) is selected as the primary target parameter to be 
estimated by calibrating the SCM against seepage-rate data from the liquid-release tests. 
Capillarity is the main process behind the seepage exclusion phenomenon, as confirmed by 
the large sensitivity of the calculated seepage rate to changes in the key parameter of the 
capillary pressure-saturation relationship. The seepage-relevant capillary-strength parameter 
on the drift scale cannot be derived from standard laboratory or field measurements, or 
inferred from secondary information (such as fracture trace maps and aperture measurements). 
The parameter is suitable for the inclusion of a number of small-scale features and 
effects (such as surface roughness, film flow, drop detachment), and even numerical artifacts, 
such as increased seepage induced by discretization effects. It is important to realize that all 
the effects lumped into the log(  / 1 ) parameter are related or analogous to a capillarity 
effect, justifying the approach. 
3. Permeability as the second important parameter affecting drift seepage is not estimated from 
seepage-rate data, but is taken from and conditioned on the air-permeability data. Fixing 
permeability at values that are determined independently from seepage-rate data is a reasonable 
means to resolve the non-uniqueness issue that arises from the strong correlation of 
permeability to all the other parameters. The support scale of the air-permeability data is 
consistent with that of the numerical grid. It allows determination and inclusion of heterogeneity 
into the model, which is an important feature affecting seepage. The stochastic nature 
and uncertainty in the heterogeneous permeability field is accounted for by performing 
multiple inversions using different realizations of the simulated permeability field. 
4. Porosity is used as an effective parameter to capture storage effects. Porosity is only 
estimated in those liquid-release tests that involved little water, and where evaporation 
effects (which have an impact similar to increased storage) are not explicitly accounted for, 
affecting the early-time seepage-rate data. The analysis of liquid-release tests performed in 
the middle nonlithophysal zone (Niches 3107 and 4788) include the estimation of porosity; 
the tests conducted in the lower lithophysal zone (Niche 1620 and systematic seepage testing 
area in the ECRB Cross Drift) use a fixed value for porosity of approximately 1% (DTN: 
LB0205REVUZPRP.001 [159525]) and include only the estimation of log(  / 1 ). Note that 
the estimated porosity value is of no interest for the subsequent prediction of steady-state 
seepage into waste emplacement drifts. It is only determined here to avoid an unwanted bias 
in the concurrently estimated log(  / 1 ) parameter, to which it is negatively correlated. 
April 2003 86 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
5. All other parameters are fixed at the values given in Table 4. They become part of the model 
structure along with initial and boundary conditions (see Sections 6.6.2.4 and 6.6.2.3, respectively), 
and spatial discretization (specifically the length of the nodal distance to the drift 
element, see Sections 6.3.3.3, 6.6.1.2, and 8.2). Since the estimated parameters are likely to 
be correlated to these fixed parameters and would change if the model structure were 
modified, the estimated values are to be considered model-related. 
In summary, the logarithm of the capillary-strength parameter  / 1 , which enters the van 
Genuchten capillary-pressure function (see Equation (5)) is estimated as an effective, seepagerelevant, 
model-related parameter through automatic calibration of the SCM against seepage-rate 
data from liquid-release tests. For tests conducted in the middle nonlithophysal zone, porosity is 
also determined to be an effective parameter, accounting for storage effects. 
6.6.3.2 Data Selection 
As described in BSC (2001 [158463], Sections 6.2 and 6.11) and summarized in Section 6.5.3, 
an automatic data acquisition system was set up to monitor the cumulative amount of water 
seeping into the capture system installed within the niches and the ECRB Cross Drift. Taking the 
derivative of these cumulative seepage data (see Attachment VI) yields the seepage rates to be 
used for calibration. Note that measurement noise in the cumulative seepage data induces 
fluctuations in the calculated seepage rates. If no or little seepage occurs, these fluctuations may 
lead to negative seepage-rate values. These nonphysical data points are of no concern, because 
the numerical model (which always produces physical, non-negative seepage rates) does not 
attempt to track the high-frequency fluctuations from measurement noise (the random component 
of the data are described by the stochastic model of the inversion); instead, the model 
follows the smooth, deterministic component of the seepage-rate data, which is non-negative. 
Seepage rates are used instead of cumulative seepage data because an error in the prediction of 
the early-time seepage behavior leads to a shift in the cumulative seepage curve. Such a shift 
induces a bias in the estimated parameters, even if only late-time data were used in the inversion. 
In general, early-time seepage data are relatively strongly affected by storage effects. Moreover, 
they reflect the properties of only a few fractures that connect the injection interval with the point 
at the drift surface where seepage is initiated. These fractures may not be representative of the 
drift-scale properties of the fracture network engaged in the seepage process under near-steadystate 
conditions. These few fractures are likely to be conceptually different from the larger-scale 
network providing connectivity for flow diversion around the drift. Consequently, matching 
early-time data potentially leads to an unwanted bias in the estimated parameters. Late-time, 
near-steady data are less affected by storage effects, allowing for a more representative estimation 
of log(  / 1 ). 
The following paragraphs discuss the data sets used for calibration (see also Table 11). 
Borehole SYBT-ECRB-LA#1, Lower Lithophysal Zone 
DTN: LB0110ECRBLIQR.002 [156879] 
Only one borehole interval (zone 2) was available for liquid-release testing in borehole SYBTECRB-
LA#1 (BSC 2001 [158463], p. 241). Starting on 2/28/2001, water was released for a 
MDL-NBS-HS-000004 REV02 April 2003 87 U0080 Seepage Calibration Model and Seepage Testing Data 
period of almost a month at an average rate of approximately 17 ml/min. No seepage was 
induced. In the following month, four tests with approximate release rates between 41 ml/min 
and 45 ml/min were performed, interrupted by phases of inactivity that lasted from a few hours 
to approximately 6 days. These higher-rate tests led to seepage. Seepage-rate data from all five 
tests (Events 6569 of Table 11) are used for calibration. During the two-month testing period, 
the relative humidity in the drift varied between about 10% and 60% (BSC 2001 [158463], 
Figure 6.11.2-11c). Data preparation is described in Attachment VI and Wang 2003 [161456], 
SN-LBNL-SCI-228-V1, pp. 1517). 
Borehole SYBT-ECRB-LA#2, Lower Lithophysal Zone 
DTN: LB00090012213U.002 [153154], DTN: LB0110SYST0015.001 [160409] 
Borehole SYBT-ECRB-LA#2 was tested twice, in May/June 2000 and October/November 2000. 
Humidity in the drift was not controlled or monitored during the earlier tests; these tests will 
therefore not be used for calibration, but for validation with an assumed relative humidity. 
During the second test period starting 10/23/2000, long-term liquid-release tests were conducted 
in zones 2 and 3 (Events 6164 of Table 11) with approximate release rates ranging between 33 
ml/min and 41 ml/min. The relative humidity in the testing area (partly protected from air 
circulation by curtains installed at the two ends of the V-shaped seepage capture curtains) varied 
between approximately 30% and 90% (BSC 2001 [158463], Figure 6.11.2-8). Data preparation is 
described in Finsterle (2002 [161043], p. 133) and Wang (2003 [161456], SN-LBNL-SCI-228- 
V1, pp. 1821). 
Borehole SYBT-ECRB-LA#3, Lower Lithophysal Zone 
DTN: LB0203ECRBLIQR.001 [158462] 
Test events 70 and 71 (see Table 11) were conducted in zone 1 of borehole SYBT-ECRB-LA#3, 
starting on 5/17/2001. Despite the higher release rate of approximately 36 ml/min during the first 
test, which lasted for about 4 days, no seepage was observed. A long-term test (26 days) at an 
average rate of approximately 25 ml/min produced somewhat erratic seepage, with seepage rates 
reaching approximately 10 ml/min, but decreasing during the last 10 days of the test. Relative 
humidity varied between 10% and 50%. Data preparation is described in Wang (2003 [161456], 
SN-LBNL-SCI-228-V1, pp. 1517). 
Niche 1620, Lower Lithophysal Zone 
DTN: LB0209NICH5LIQ.001 [160796] and DTN: LB0211NICH5LIQ.001 [160792] 
During test events 86 and 87 (see Table 11), water was released at an approximate rate of 26 
ml/min from interval 2829 ft of borehole #5; the tests started 7/15/2002 (Day 195 since 
01/01/2002) and continued until 8/5/2002 (Day 216). In concurrently conducted tests, water was 
released from interval 2122 ft of borehole #3 between 7/17/2002 (Day 197) and 7/19/2002 (Day 
199; Event 83), and again between 7/29/2002 (Day 208) and 8/9/2002 (Day 221; Event 84; 
shaded zones in Figure 17). It is apparent from Figure 17 that part of the water released in 
borehole #3 was captured in the trays intended to collect seepage from the liquid-release tests 
conducted in borehole #5. Because of this test interference, only the late-time data of Event 86 
up to 7/30/2002 (Day 209) are considered for calibration. During Event 89 (Table 11), water was 
released at an almost constant rate of approximately 9.9 ml/min from interval 1011 ft of 
April 2003 88 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
borehole #4; the test started 9/17/2002 and continued until 10/1/2002. Seepage started on 
9/19/2002 and increased gradually until it reached almost steady state on 9/24/2002. Data preparation 
is described in Wang (2003 [161456], SN-LBNL-SCI-223-V1, pp. 3034). 
40 
30 
20 
10 
195 
0
190 
70 
60 
50 
40 
30 
20 
10 
Release Rate 
200 
200 195 
0
190 
Time [day since 01/01/2002 00:00] 
Figure 17. Interference between concurrent liquid-release tests in borehole #3 (2122 ft) and 
borehole #5 (2829 ft). Note that 7/15/2002 is Day 195. Data from DTN: 
LB0209NICH5LIQ.001 [160796]. 
Niche 3107, Middle Nonlithophysal Zone 
DTN: LB0010NICH3LIQ.001 [153144] 
Two intervals were tested in Niche 3107. However, only test events in one interval (UM 4.88 
5.18) resulted in seepage (see Events 6, 812 in Table 11). The tests in the other interval (UL 
5.495.80) are not useable for calibration, as no seepage was observed (see Events 13), which 
would lead to an ill-posed inverse problem. Nevertheless, these data will be used for validation 
purposes. Of the nine tests performed in interval UM 4.885.18, three are selected for model 
calibration because of their variety in injection and seepage rates. The tests starting on 3/4/1999, 
4/27/1999, and 5/6/1999 are characteristic of all the tests performed in this interval. The 3/4/1999 
test (Event 4) was conducted at a low injection rate of approximately 0.9 ml/min, resulting in no 
seepage. The 4/27/1999 test (Event 6) used a medium rate of about 2.4 ml/min and resulted in a 
small amount of seepage. Finally, the 5/6/1999 test (Event 8) was performed with a higher rate of 
approximately 5.4 ml/min, which resulted in substantial seepage. The remaining tests (Events 7, 
912) in this interval are reserved for validation. Data preparation is described in Ahlers (2002 
[161045], pp. 41, 4748). 
89 MDL-NBS-HS-000004 REV02 
Flow Rate [ml/min] Flow Rate [ml/min] 
215 210 
Release Rate 
Seepage Rate 
205 
205 
Seepage Rate 
215 220 210 
Borehole#5 (28-29ft) 
235 230 225 220 
Borehole#3 (21-22ft) 
235 230 225 
U0080 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
Niche 4788, Middle Nonlithophysal Zone 
DTN: LB0010NICH4LIQ.001 [153145] 
Three intervals were tested in Niche 4788, all leading to seepage. Each test performed in a given 
interval was conducted with a different release rate (except in interval UM 6.106.40, where 
three low-rate tests were performed; only the test on 3/14/2000 was a long-term test). In each 
interval, the low- and medium-rate tests that resulted in seepage were selected for model calibration 
(Events 41, 43, 45, 48, 50, and 51 in Table 11). The highest-rate and lowest-rate seepage 
tests are reserved for validation (Events 40, 42, 44, 47, 49) to determine whether seepage model 
predictions can be successfully extrapolated to conditions beyond the calibration range. Data 
preparation is described in Ahlers (2002 [161045], pp. 2627, 3436). 
6.6.3.3 Calibration Results 
The software iTOUGH2 V4.0 (LBNL 1999 [139918]) for tests without significant evaporation 
effects, or iTOUGH2 V5.0 (LBNL 2002 [160106]) for tests with evaporation effects, is used to 
match the transient seepage-rate data (see Section 6.6.3.2) by automatically updating the parameters 
of interest (see Section 6.6.3.1). The inverse modeling approach follows the concept 
described by Carrera and Neuman (1986 [104368]) and Finsterle (1999 [104367]). The misfit 
between calculated and measured seepage is evaluated using the least-squares objective function 
(Equation (13)). The objective function is minimized using the Levenberg-Marquardt algorithm 
(Finsterle 1999 [104367], pp. 4445). 
The inversion results are presented as follows. First, the simulated system behavior obtained with 
the calibrated model is qualitatively described for selected tests and points in time. Second, the 
match between the simulated and observed seepage-rate data is shown. Third, the estimated 
parameters are discussed. Finally, the results from the individual inversions are combined and 
summarized (see Section 6.6.4) to obtain a parameter distribution for subsequent model validation. 
Input and output files from a representative inversion are discussed in Attachment VII. 
Borehole SYBT-ECRB-LA#1, Lower Lithophysal Zone 
The overall simulated system behavior during liquid-release tests from inclined boreholes drilled 
from the ECRB is qualitatively visualized in Figure 18 (and for other boreholes in Figure 21, 
Figure 26, Figure 28, and Figure 30). Figure 18a shows the flux distribution at the end of the 
testing period. The flow field above the injection point represents the natural background percolation 
flux, with flow channeling occurring as a result of explicitly modeled small-scale heterogeneity. 
It is apparent that flow channels are established within a short distance below the top 
boundary. The injection interval (zone 2 of borehole SYBT-ECRB-LA#1) is relatively close to 
the crown of the drift. Local flux below the water release point is very high. Water is partly 
diverted around the opening. The low relative humidity (less than 50%) leads to substantial 
evaporation, extracting most of the injected water from the formation before it reaches the spring 
line of the drift. Flow diversion around the drift and the removal of water that seeped into the 
capture system leads to reduced fluxes below the drift, an effect referred to as the shadow zone. 
The saturation distribution at the end of seepage testing (Event 69 of Table 11) shows that the 
fracture continuum is essentially dry (less than 10%) under natural percolation conditions (Figure 
90 MDL-NBS-HS-000004 REV02 April 2003 Seepage Calibration Model and Seepage Testing Data 
18b). Injecting at rates on the order of 40 ml/min increases saturation without completely saturating 
the pore space, i.e., the flow regime remains unsaturated. As a result of the capillary-barrier 
effect, saturations are highest in the immediate vicinity of the drift, which induces a capillarypressure 
gradient promoting flow diversion. Seepage and evaporation removes water from the 
formation as it flows around the drift, explaining why no significant saturation increase can be 
observed at the spring line. In contrast, during the liquid-release tests performed in the closed-off 
niches, where evaporation is significantly reduced, water reaches the spring line and drains to 
depth as shown, for example, in Figure 26a and Figure 28a, and evidenced by seepage into the 
horizontal slot excavated from the side of Niche 1620 (see also Section 6.7). Additional discussions 
of the flow and seepage behavior will be given below for tests in borehole SYBT-ECRBLA#
2. 
8
6
4
2
0 
0 1 
2 0 1 3 2 3 4 
X 
[m] 
Y 
[m] 
(a) 
t = 58 days 
Flux [mm/yr] 
Z [m] 
-2 
10000 
1000 
100 
10 
1 
(b) 
91 
Figure 18. (a) Flux and (b) saturation distribution at the end of liquid-release testing in zone 2 of 
borehole SYBT-ECRB-LA#1. Based on output DTN: LB0302SCMREV02.001. 
The match of the calculated seepage rates (red line) to the observed data (blue symbols) for this 
test is shown in Figure 19, along with the measured and modeled release rates (gray and black 
lines) and the relative-humidity data (green line). The model correctly replicates the initial, 34- 
day long no-seepage period. The increase in release rates induces seepage, the magnitude of 
which is well reproduced by the calibrated model. After each test interruption, seepage rates are 
reestablished more quickly in the model than observed in the field. The discrepancy between 
model and data is more pronounced after longer periods of inactivity (i.e., for the test events 
starting at 34 and 40 days, which followed interruptions of approximately 5  and 3  days, 
respectively) suggesting that a storage mechanism (e.g., storage in the injection lines and borehole 
intervals, imbibition into the dried-out matrix, filling of lithophysal cavities, and/or storage 
Z [m] 
Saturation 
0.5 
0.4 
0.3 
0.2 
0.1 
0.0 
MDL-NBS-HS-000004 REV02 
100000 
0 
1 2 3 3 4 
X 
[m] 
t = 58 days 
8
6
4
2
0
-2 
0 1 2 
Y 
[m] 
U0080 
April 2003 Seepage Calibration Model and Seepage Testing Data 
within the capture system, i.e., between the trays or capture curtain and the balance measuring 
cumulative seepage) is not appropriately accounted for. The discrepancies in these early-time 
data, however, are minor and are not expected to significantly bias the parameter estimate. 
Because transient system responses introduced by test interruptions and rate changes are reproduced 
by specifying time-varying boundary conditions, their potential impact on seepage is 
appropriately captured. 
A total of 17 inversions were performed, each with a different realization of the underlying, 
heterogeneous permeability field. The quality of the matches obtained with each inversion is 
consistent, as shown in Figure 20. 
The  / 1 estimate has a mean, standard deviation, and standard error of 534 Pa, 57 Pa, and 
14 Pa, respectively (see Table 14 below). (Note that the statistics are performed for  / 1 instead 
of log(  / 1 ). Using the backtransformed values is justified by the small standard deviation of the 
estimates.) The estimation uncertainty of an individual inversion (given by Equation (14)) is on 
the order of a few pascals. This estimation uncertainty accounts for the residual misfit of the 
calibrated model to the data and the sensitivity of the calculated seepage rates with respect to 
 / 1 . This uncertainty measure is not propagated through the suite of seepage models, because it 
is significantly less than the uncertainty stemming from small-scale heterogeneities (which is 
examined by performing multiple inversions with multiple realizations of the permeability field, 
amounting to 57 Pascals (Pa) in this case) and spatial variability (which is examined by inverting 
data from tests conducted at different locations, amounting to approximately 100 Pasee 
Section 6.6.4). 
50 
40 
30 
SYBT-ECRB-LA#1, Zone 2 
10 
Relative 
Humidity
20 
Release 
MDL-NBS-HS-000004 REV02 
Rate [ml/min] 
20 
10
0 
-10 0 
Time [days since 2/28/2001, 13:59] 
Figure 19. Calibration of seepage-rate data from liquid-release tests in zone 2 of borehole SYBTECRB-
LA#1. Blue symbols represent measured data; the red line is the calculated 
seepage rate. The measured release rates are shown in dark gray; the black solid line 
shows the injection rate used in the model. Relative-humidity data are shown as a green 
dashed line. All curves representing measured data derived from DTN: 
LB0110ECRBLIQR.002 [156879]; calculated seepage in DTN: LB0302SCMREV02.001. 
92 
60 
50 
40 
30 
20 
10 
Seepage Data 
50 0 60 
Relative Humidity [%] 
Calculated Seepage 
30 40 
U0080 
April 2003 Seepage Calibration Model and Seepage Testing Data 
15 
10
5
0
0 
Figure 20. Calibration of seepage-rate data from liquid-release tests in zone 2 of borehole SYBTECRB-
LA#1. Blue symbols represent measured seepage-rate data; the red lines are the 
results obtained with 17 calibrated models, each using a different realization of the 
underlying heterogeneous permeability field. Seepage-rate data derived from DTN: 
LB0110ECRBLIQR.002 [156879]; calculated seepage in DTN: LB0302SCMREV02.001. 
Time [days since 2/28/2001, 13:59] 
Borehole SYBT-ECRB-LA#2, Lower Lithophysal Zone 
Multiple liquid-release tests were performed in zones 2 and 3 of borehole SYBT-ECRB-LA#2. 
The propagation of the liquid plume from the tests in zone 2 is visualized in Figure 21. After 10 
days of injection (Figure 21b), water is diverted around the drift approximately to the elevation 
of the spring line. After 20 days (Figure 21c), however, the plume has shrunk significantly as a 
result of increased evaporation (see discussion of Figure 22 below). Increased relative humidity 
prior to the 30-day time mark reduces evaporation and thus enables water to flow around the 
drift. Figure 21d also highlights the shadow zone created by flow diversion around the drift. 
Figure 21 suggests that horizontal spreading of the liquid plume is partly restricted by the limited 
extension of the model domain in the Y-direction. This boundary effect increases seepage. The 
impact of the increased seepage on the estimated  / 1 value is minor compared to the parameters 
uncertainty (Wang 2003 [161456], SN-LBNL-SCI-228-V1, p. 32). 
Despite the SCM being a continuum model, seepage occurs at only a few discrete locations 
(indicated by triangles), consistent with qualitative observations of drip locations. Seepage 
locations are affected by heterogeneity. In the current realization, some seepage occurs near the 
crown of the drift; however, most water enters the drift from a location approximately halfway 
between the crown and the spring line (see Figure 21d). 
MDL-NBS-HS-000004 REV02 93 
Seepage Rate [ml/min] 
U0080 
SYBT-ECRB-LA#1, Zone 2 
30 
Calculated Seepage 
20 
Seepage Data 
10 60 50 40 
April 2003 Seepage Calibration Model and Seepage Testing Data 
0 
0 
8
6
4
2
0
-2 
1 
2 0 1 3 2 3 4 
X 
[m] 
Y 
[m] 
8
6
4
2
0
-2 
1 2 0 1 3 2 3 4 
X 
[m] 
Y 
[m] 
Figure 21. Saturation distribution simulated with model calibrated against seepage-rate data from 
liquid-release tests conducted in zone 2 of borehole SYBT-ECRB-LA#2; (a) initial distribution, 
(b) after 10 days, (c) 20 days, and (d) 30 days. Triangles indicate seep locations and 
Seepage Rate 
1 m3/yr 
Z [m] 
Saturation 
0.5 
0.4 
0.3 
0.2 
0.1 
0.0 
MDL-NBS-HS-000004 REV02 
Z [m] 
Saturation 
0.5 
0.4 
0.3 
0.2 
0.1 
0.0 
Seepage Rate 
1 m3/yr 
t = 20 days 
seepage amount. Based on output DTN: LB0302SCMREV02.001. 
Z [m] 
Saturation 
0.5 
0.4 
0.3 
0.2 
0.1 
0.0 
Seepage Rate 
1 m3/yr 
t = 0 days 
0 1 
2 3 3 4 
X 
[m] 
0 1 2 3 3 4 
X 
[m] 
94 
U0080 
t = 10 days 
8
6
4
2
0 
Seepage Rate 
1 m3/yr 
Z [m] 
Saturation 
0.5 
0.4 
0.3 
0.2 
0.1 
0.0 
-2 
0 1 2 
Y 
[m] 
t = 30 days 
8
6
4
2
0
-2 
0 1 2 
Y 
[m] 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
Comparisons between measured and calculated seepage rates for the tests in zones 2 and 3 are 
shown in Figure 22 and Figure 23, respectively. Fluctuations in both data sets can be correlated 
to the drastic changes in relative humidity, which drives evaporation. The model captures this 
evaporation effect reasonably well, tracking increases in measured seepage rates as relative 
humidity increases and vice versa. These results provide confidence that the conceptual model 
represents the key processes and their interactions appropriately, including: 
1. Unsaturated flow using a continuum representation of fracture flow based on Richards 
equation (see Section 6.6.1.1); 
2. Seepage into the opening, accounting for the capillary-barrier effect (see Section 6.6.1.2); 
3. Vaporization of water from the drift surface, using a simplified evaporation model (see 
Section 6.6.1.3). 
The rather complex system behavior, which includes expansion and shrinkage of the liquid 
plume along the drift surface, signifies the importance of handling unsaturated flow, seepage, 
and evaporation in a fully coupled manner. 
April 2003 95 MDL-NBS-HS-000004 REV02 SYBT-ECRB-LA#2, Zone 2 
Release 
Relative 
Humidity 
Seepage Data Calculated Seepage 
10 20 
Seepage Calibration Model and Seepage Testing Data 
Rate [ml/min] Rate [ml/min] 
45 
40 
35 
30 
25 
20 
15 
10
5
0 
-5 0 
40 
30 
20 
10
0
0 
Time [days since 10/23/2000, 15:38] 
Figure 22. Calibration of seepage-rate data from liquid-release tests conducted in zone 2 of borehole 
SYBT-ECRB-LA#2. Blue symbols represent measured data; the red line is the calculated 
seepage rate. The measured release rates are shown in dark gray; the black solid line 
shows the injection rate used in the model. Relative-humidity data are shown as a green 
dashed line. All curves representing measured data are derived from DTN: 
LB0110SYST0015.001 [160409]; calculated seepage in DTN: LB0302SCMREV02.001. 
30 
Seepage Data 
20 
SYBT-ECRB-LA#2, Zone 3 
Release 
Relative 
Humidity 
Calculated Seepage 
10 
Time [days since 10/23/2000, 15:37] 
Figure 23. Calibration of seepage-rate data from liquid-release tests conducted in zone 3 of borehole 
SYBT-ECRB-LA#2. Blue symbols represent measured data; the red line is the calculated 
seepage rate. The measured release rates are shown in dark gray; the black solid line 
shows the injection rate used in the model. Relative-humidity data are shown as a green 
dashed line. All curves representing measured data are derived from DTN: 
LB0110SYST0015.001 [160409]; calculated seepage in DTN: LB0302SCMREV02.001. 
MDL-NBS-HS-000004 REV02 
U0080 
100 
90 
80 
70 
60 
50 
40 
30 
20 
10 
0 40 30 
100 
90 
80 
70 
60 
50 
40 
30 
20 
10 
0 
April 2003 
Relative Humidity [%] Relative Humidity [%] 
96 Seepage Calibration Model and Seepage Testing Data 
The capillary-strength parameter  / 1 was determined based on 21 inversions of seepage-rate 
data from zone 2, and 19 inversions of data from zone 3. The means and standard deviations 
(557  56 Pa for zone 2 and 535  58 Pa for zone 3; see Table 14 below) are consistent with 
those obtained in borehole SYBT-ECRB-LA#1. 
Borehole SYBT-ECRB-LA#3, Lower Lithophysal Zone 
The calibration of liquid-release tests from zone 1 of borehole SYBT-ECRB-LA#3 revealed 
some systematic inconsistencies between the data and the model. As shown in Figure 24, the 
model produces considerable seepage during the simulation of the first test event, while no 
seepage was observed in the field despite the high release rate. Furthermore, the model predicts a 
more or less uniform seepage rate for the second test event, whereas the data show a continuous 
increase in seepage for approximately 10 days, followed by a decrease. Nevertheless, the 
inversion yields a reasonable reproduction of the average seepage rate. The mean  / 1 value of 
452  55 Pa (based on 23 inversions; see Table 14 below) is lower than the previous estimates. 
50 
SYBT-ECRB-LA#3, Zone 1 
Release 
40 
30 
20 
10
0 
-10 0 
Calculated Seepage 
10 20 
MDL-NBS-HS-000004 REV02 
Rate [ml/min] 
Time [days since 5/17/2001, 15:33] 
Figure 24. Calibration of seepage-rate data from liquid-release tests conducted in zone 1 of borehole 
SYBT-ECRB-LA#3. Blue symbols represent measured data; the red line is the calculated 
seepage rate. The measured release rates are shown in dark gray; the black solid line 
shows the injection rate used in the model. Relative-humidity data are shown as a green 
dashed line. All curves representing measured data are derived from DTN: 
LB0203ECRBLIQR.001 [158462]; calculated seepage in DTN: LB0302SCMREV02.001. 
97 
60 
50 Relative 
Humidity 
40 
30 
20 
10 
0 
Seepage Data 
30 
Relative Humidity [%] 
U0080 
April 2003 Seepage Calibration Model and Seepage Testing Data 
Niche 1620, Borehole #4, Interval 1011 ft, Lower Lithophysal Zone 
During Test Event 89, liquid was released at a fairly constant rate. Seepage was observed after 
two days and continued to increase for four days, reaching almost steady state on the sixth day. 
The test was simulated with a constant release rate of 9.9 ml/min and a constant relative humidity 
of 85%. The model produced seepage 12 hours after liquid release started, and reached a 
constant seepage rate after 36 hours (see Figure 25). The saturation and flux at the end of the test 
(see Figure 26) show that there is significant diversion of injected liquid around the niche. Thirty 
inversions with 30 different realizations of the underlying heterogeneous permeability field were 
performed, resulting in a calibrated capillary-strength parameter  1 of 671 223 Pa. The 
standard error of the mean is 41 Pa. 
10
8
6
4
2
00 
Calculated seepage 
2 
Seepage data 
4 
Time [day since 09/17/2002 16:20] 
98 
Figure 25. Calibration of seepage-rate data from liquid-release tests conducted in interval 1011 ft of 
borehole #4 in Niche 1620. Blue symbols represent measured data; the red line is the 
calculated seepage rate. The measured release rates are shown in dark gray; the black 
solid line shows the injection rate used in the model. All curves representing measured 
data are derived from DTN: LB0211NICH5LIQ.001 [160792]; calculated seepage in DTN: 
LB0302SCMREV02.001. Flow Rate [ml/min] 
8 
Release 
6 
Calibration 
Period 
10 12 
MDL-NBS-HS-000004 REV02 
U0080 
April 2003 Seepage Calibration Model and Seepage Testing Data 
6
5
4
3
2 
0 16 -1 
-2 17 
-3 
6
5
4
3
2 
0 16 -1 
-2 17 
-3 
Figure 26. Simulated (a) saturation and (b) flux distribution at the end of liquid-release testing (after 
13 days) in interval 1011 ft of borehole #4 in Niche 1620. Based on output DTN: 
Average Flux 
(mm/yr) 
100000 
10000 
1000 
100 
10 
1 
LB0302SCMREV02.001 
Niche 1620, Borehole #5, Interval 2829 ft, Lower Lithophysal Zone 
In Test Event 86, water was released at a rate of approximately 25.8 ml/min. The slight fluctuations 
in the release data that occurred during the first four days were reproduced in the seepage 
model. Seepage started on the second day and continued at an increasing rate, until it reached a 
constant rate on the tenth day (see Figure 27). The slight interference from Event 83 that 
occurred during the third day of Event 86 affected only the transient stage of the seepage data 
and was considered insignificant in the calibration process (see also discussion of Figure 17). 
The simulated relative humidity was kept constant at 85%, consistent with the averaged observed 
relative humidity during the test. The saturation and flux at the end of the test (see Figure 28) 
show that there is significant flow diversion of injected liquid around the niche towards the left 
slot. (See Section 6.7 for a detailed discussion on the significance of seepage into the slot in 
confirming the capillary-barrier concept.) Twenty-four inversions with different realizations of 
the underlying heterogeneous permeability field were performed, resulting in a calibrated 
MDL-NBS-HS-000004 REV02 99 
6
5
4
3
2 
16 
1 
17 2 
y 
[m] 
3 
6
5
4
3
2 
16 
17 2 
y 
[m] 
3 
x [m] 
1 
x [m] 
z [m] 
z [m] 
U0080 
Saturation 
0.9 
0.8 
0.7 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1 
0 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
capillary-strength parameter  1 of 740  339 Pa. The standard error of the mean is 69 Pa (see 
Table 14 below). 
Calibration 
Period 
Release 
8 
Seepage data 
12 10 
Time [day since 07/15/2002 12:45] 
Figure 27. Calibration of seepage-rate data from liquid-release tests conducted in interval 2829 ft of 
borehole #5 in Niche 1620. Blue symbols represent measured data; the red line is the 
calculated seepage rate. The measured release rates are shown in dark gray; the black 
solid line shows the injection rate used in the model. All curves representing measured 
data are derived from DTN: LB0209NICH5LIQ.001 [160796]; calculated seepage in DTN: 
LB0302SCMREV02.001. 
Flow Rate [ml/min] 
30 
25 
20 
15 
10
5
0 
14 2 0 
Calculated seepage 
4 6 
April 2003 100 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
7
6
5
4
3
2
21 
22 
-4 
7
6
5
4
3
2
21 
22 
-4 
Saturation 
0.9 
0.8 
0.7 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1 
0 
Average Flux 
(mm/yr) 
100000 
10000 
1000 
100 
10 
1 
Figure 28. Simulated (a) saturation and (b) flux distribution at the end of liquid-release testing (after 
13 days) in interval 2829 ft of borehole #5 in Niche 1620. Based on output DTN: 
LB0302SCMREV02.001. 
Niche 3107, Middle Nonlithophysal Zone 
Data from three liquid-release tests performed in the center borehole UM (see inset in Figure 4) 
were inverted simultaneously. The inversions are based on one realization of the underlying 
heterogeneous permeability field. The match between the measured and calculated seepage rates 
is shown in Figure 29. The first low-rate test did not yield seepage. The seepage-rate data of the 
test conducted with the intermediate rate were considered less reliable, and a smaller weight was 
assigned to these data for the inversion. As a result, the model slightly overpredicts these data, 
whereas the other two jointly inverted test events were well matched. A relatively high  / 1 
estimate of 741 Pa was obtained. The estimate will be combined with those obtained from Niche 
4788 to yield a single value for the middle nonlithophysal zone (see Section 6.6.4). 
MDL-NBS-HS-000004 REV02 
-1 
-2 0 
-3 1 
2 
3 
-2 0 
-3 1 
2 
3 
x [m] 
-1 
x [m] 
101 
U0080 
7
6
5
4
3
2 
21 
22 
y 
[m] 
7
6
5
4
3
2 
21 
22 
z [m] 
z [m] 
y 
[m] 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
Niche 3107 UM 4-27-99 Niche 3107 UM 3-4-99 Niche 3107 UM 5-6-99 
4.0 7.0 3.0 
Simulated 
Measured 6.0 Simulated 
Measured 2.5 
3.0 5.0 2.0 Simulated 
Measured 
2.0 
1.0 
1.5 
1.0 
0.5 
0.0 
12 
4.0 
3.0 
2.0 
1.0 
0.0 18 6 96 48 0 48 42 0.036 
Elapsed Test Time [hours] Elapsed Test Time [hours] Elapsed Test Time [hours] 
Figure 29. Comparison between simulated and measured seepage rates from three liquid-release 
tests conducted in interval UM 4.885.18 of Niche 3107. Measured data derived from 
DTN: LB0010NICH3LIQ.001 [153144]; calculated seepage in DTN: 
LB0010SCMREV01.001 [154292]. 
Niche 4788, Middle Nonlithophysal Zone 
Calibrated parameters are produced separately for each interval tested in Niche 4788. The 
horizontal separation distance between adjacent borehole intervals is greater than the vertical 
distance between the injection intervals and the ceiling of the niche. Since water flow is 
predominantly gravity driven, test interference is unlikely. Additionally, flow is diverted around 
the niche on different (albeit overlapping) paths. The water injected into the intervals on the side 
boreholes (UL and UR, see insert in Figure 4) is expected to be diverted to the respective sides of 
the niche, testing the flow system and capillary barrier on either side of the niche. The water 
injected into the center borehole (UM) encounters the flow system near the crown of the niche as 
well as on the sides. Figure 30 shows the simulated late-time saturations from liquid-release tests 
in each of the three boreholes above Niche 4788. The relative independence of the flow systems 
in Niche 4788 leads to a strategy of estimating a separate 1/  parameter for each interval 
(intervals UL 7.627.93, UM 6.106.40, and UR 5.185.48). 
The calibrated model matches the data reasonably well (see Figure 31) given that multiple test 
events performed with different injection rates were inverted simultaneously (note the different 
scales on the Y-axes). The model overpredicts the seepage rates from the test performed in 
borehole UM on 12-10-99. In this case, the minimization algorithm was likely trapped in a local 
minimum. The  / 1 estimates (based on one realization of the underlying heterogeneous permeability 
field) for the three boreholes UL, UM, and UR are 646 Pa, 603 Pa, and 427 Pa, 
respectively. These three estimates will be combined with that from Niche 3107 to yield an 
average value for the middle nonlithophysal zone (see Section 6.6.4). Additional information on 
calibrations of the tests conducted in the middle nonlithophysal zone can be found in Ahlers 
(2002 [161045], pp. 3839, 49). 
MDL-NBS-HS-000004 REV02 April 2003 102 Seepage Calibration Model and Seepage Testing Data 
Z(m) Z(m) Z(m) 
3.0 
2.0 
1.0 
0.0 
-1.0 
-2.0 
10.45 
Y(m) 
3.0 
2.0 
1.0 
0.0 
-1.0 
-2.0 
10.45 
Y(m) 
3.0 
2.0 
1.0 
0.0 
-1.0 
-2.0 
-3.0 
Figure 30. Simulated late-time saturation distribution for liquid-release tests in Niche 4788, intervals 
(a) UL 6.727.93 (11/03/1999), (b) UM 6.106.40 (11/16/1999), and (c) UR 5.185.48 
(12/07/1999). The step in the displayed grid contains the injection interval. Figure based 
on DTN: LB0010SCMREV01.001 [154292]. 
-1.0 
-2.0 12.45 
-1.0 
-2.0 12.45 
-2.0 
-1.0
X(m) 
0.0 
1.0 
2.0 
3.0 
MDL-NBS-HS-000004 REV02 
0.0
X(m) 
1.0 
0.0
X(m) 
1.0 
103 
U0080 
Saturation 
0.70 
0.57 
0.44 
0.31 
0.18 
0.05 
3.0 
2.0 
Saturation 
0.70 
0.57 
0.44 
0.31 
0.18 
0.05 
3.0 
2.0 
Saturation 
0.70 
0.57 
0.44 
0.31 
0.18 
0.05 
10.45 
Y(m) 
12.45 
April 2003 Seepage Calibration Model and Seepage Testing Data 
2.0 
1.5 
1.0 
0.5 
36 0.0 18 
3.0 
2.5 
2.0 
1.5 
1.0 
0.5 
120 0.0 72 
2.0 
1.5 
1.0 
0.5 
0.0 
Figure 31. Comparison between simulated and measured seepage rates from six liquid-release tests 
conducted in three different borehole intervals of Niche 4788. Data from a given interval 
are inverted simultaneously. Measured data derived from DTN: LB0010NICH4LIQ.001 
[153145]; calculated seepage in DTN: LB0010SCMREV01.001 [154292]. 
6.6.4 Summary and Compilation of Results 
Multiple three-dimensional, heterogeneous models representing niche locations and sections of 
the ECRB Cross Drift were developed. The permeability fields were constructed and conditioned 
on local air-permeability data (see Section 6.6.2.1). Seepage-rate data from multiple test events, 
using different liquid-release rates, were inverted simultaneously. Inversions for the lower 
lithophysal zone were repeated for multiple realizations of the underlying stochastic permeability 
field to capture the uncertainty induced by local heterogeneity. A total of 22 test events were 
used for model calibration (13 from tests conducted in the lower lithophysal zone and 9 in the 
middle nonlithophysal zone). Seepage-relevant capillary-strength values (parameter  / 1 of the 
van Genuchten capillary pressure-saturation relationshipsee Equation (5)) were estimated for 
each location. 
A summary is provided in Table 14 and visualized in Figure 32 (see also Wang (2003 [161456], 
SN-LBNL-SCI-223-V1, p. 37) and Wang (2003 [161456], SN-LBNL-SCI-228-V1, p. 31)). 
MDL-NBS-HS-000004 REV02 104 
Niche 4788 UL 11-30-99 
Simulated 
Measured 
42 30 24 
Elapsed Test Time [hours] 
Niche 4788 UM 12-10-99 
Simulated 
Measured 
96 
Elapsed Test Time [hours] 
Niche 4788 UR 1-5-00 
Simulated 
Measured 
144 96 
Elapsed Test Time [hours] 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 48 
1.6 
1.2 
0.8 
0.4 
0.0 144 
0.2 
0.1 
0.0 192 72 
Niche 4788 UL 6-26-00 
Simulated 
Measured 
504 432 360 288 
Elapsed Test Time [hours] 
Niche 4788 UM 6-8-00 
Simulated 
Measured 
144 120 
Elapsed Test Time [hours] 
Niche 4788 UR 2-14-00 
Simulated 
Measured 
144 216 288 360 432 504 576 
Elapsed Test Time [hours] 
U0080 
168 
April 2003 Seepage Calibration Model and Seepage Testing Data 
Since multiple inversions with different realizations of the underlying heterogeneous permeability 
field were performed for test locations in the lower lithophysal zone, the capillary-strength 
parameter  / 1 is calculated as the average for all inverse modeling results at that location, and a 
standard deviation  representing the related uncertainty is given. The standard error of the 
 = 
0.005 
0.004 
0.003 
0.002 
0.001 
400 
0
200 
(a) (b) 
Figure 32. Histograms and related Normal distributions of van Genuchten capillary-strength parameter 
1/  for (a) the middle nonlithophysal zone, and (b) the lower lithophysal zone. These 
distributions represent spatial variability. The squares indicate the values obtained at 
individual locations. For the lower lithophysal zone, the squares represent means from 
multiple inversions, which are plotted along with the standard error of the mean. (The 
vertical position of the symbols is of no significance.) Parameters in output DTN: 
LB0302SCMREV02.002. 
1/ [Pa] 
mean is calculated as , where i is the number of inversions performed. The estimates 
for the middle nonlithophysal zone are based on a single inversion, i.e., no estimation uncertainty 
as a result of uncertainty in small-scale heterogeneity can be given. The estimation uncertainty 
stemming from the misfit between the calibrated model and the data and the sensitivity of the 
calculated seepage rates with respect to  / 1 (see Equation (15)) is on the order of a few pascals, 
i.e., significantly less than the uncertainty from small-scale heterogeneity (which is greater than 
50 Pa) or spatial variability (which is on the order of 100 Pa); this contribution to the estimation 
uncertainty is therefore ignored. 
An average capillary-strength parameter for each of the two units is calculated from the estimates 
at the different locations within a given unit. The related standard deviation is considered to be a 
measure of spatial variability in  / 1 . In summary, the  / 1 parameter of the lower lithophysal 
zone is about 580 Pa with a variability of approximately 100 Pa; the middle nonlithophysal zone 
has slightly a higher  / 1 value of about 600 Pa and a variability of approximately 130 Pa. These 
values can be used to derive a probability distribution for the capillary-strength parameter for 
each unit (see Figure 32); they will be used as a basis for probabilistic predictions during model 
validation (see Section 7.2). Note that such a distribution reflects spatial variability only. 
Multiple realizations of the underlying permeability field must be created to capture the 
uncertainty in predicted seepage rates, on account of uncertainty in stochastic small-scale heterogeneity. 
600 
1/ [Pa] 
MDL-NBS-HS-000004 REV02 
i /  
Probability 
April 2003 
Probability 
U0080 
0.005 
0.004 
0.003 
0.002 
0.001 
1000 800 600 400 1000 800 
0
200 
105 Seepage Calibration Model and Seepage Testing Data 
Table 14. Summary Statistics of Estimated Capillary-Strength Parameter for Lower Lithophysal Zone and 
Middle Nonlithophysal Zone (DTN: LB0302SCMREV02.002) 
Lower Lithophysal Zone (Tptpll) 
6569 SYBT-ECRB-LA#1 zone 2 17 534.3 56.8 13.8 447.7 674.1 
BH #4 30 671.2 223.2 40.8 356.0 1197.0 
BH #5 24 740.5 339.0 69.2 231.1 1840.8 
Std. 
Error(4) 
12.3 
13.3 
11.4 
Location Interval Number of 
Inversions(2) 
21 
19 
23 
Mean(5) = 
Std. Dev.(6) = 
Test 
Event(1) 
61, 62 SYBT-ECRB-LA#2 zone 2 
63, 64 SYBT-ECRB-LA#2 zone 3 
70, 71 SYBT-ECRB-LA#3 zone 1 
80 Niche 1620 
83 Niche 1620 
4, 6, 8 Niche 3107 
41, 43 Niche 4788 
45, 48 Niche 4788 
50, 51 Niche 4788 
Middle Nonlithophysal Zone (Tptpmn) 
UM 1 741     
UL 1 646     
UM 1 603     
UR 1 427     
Mean(5) = 
Std. Dev.(6) = 
(1) See Table 11 on Page 62. Data from all indicated test events were jointly inverted. 
(2) Each inversion is based on a different realization of the heterogeneous permeability field. 
(3) Represents estimation uncertainty on account of small-scale heterogeneity (not available for 
estimates for the middle nonlithophysal zone). 
(4) Standard error of mean. 
(5) Represents average for given hydrogeologic unit. 
(6) Represents spatial variability. 
131.5 
MDL-NBS-HS-000004 REV02 
U0080 
Min. Max. 
676.1 457.1 
645.7 443.1 
616.6 382.8 
Mean 
557.1 
534.8 
452.0 
Std. 
Dev.(3) 
56.4 
57.8 
54.7 
581.6 
105.0 
604.3 
Estimate 1/  [Pa] 
April 2003 106 U0080 Seepage Calibration Model and Seepage Testing Data 
6.7 IMPACT OF RELATIVE HUMIDITY ON SEEPAGE 
As outlined in Section 6.3.3.4, evaporation losses during the seepage experiments conducted in 
closed-off niches are expected to be insignificant and are thus neglected in the analyses of 
seepage data from Niches 3107 and 4788. If evaporation were significant during liquid-release 
tests, measured seepage rates would be lower than those expected in a niche with 100% relative 
humidity. Analyzing these lower seepage rates with a model that assumes 100% relative 
humidity in the opening would lead to biased estimates, i.e., the estimated capillary-strength 
parameter  / 1 would be increased to match the lower rates, compensating for the systematic 
modeling error, which is a result of a conceptual difference. Neglecting evaporation effects in an 
inverse model is thus nonconservative and requires justification. (Note, however, that assuming 
100% relative humidity in the drift in a prediction model always yields seepage rates that are 
higher than those calculated with a model that includes evaporation effects; neglecting evaporation 
in a prediction model is thus conservative.) 
The SCM developed for the analysis of seepage data from liquid-release tests conducted in 
interval 1011 ft of borehole #4 in Niche 1620 includes evaporation effects. This model is 
therefore suitable for examining the impact of evaporation on calculated seepage rates as relative 
humidity is reduced from near 100% to 85% (the value used in the inversions). 
Figure 33 shows the calculated seepage and evaporation rates as a function of the relativehumidity 
boundary condition in the niche. Evaporation from the entire niche wall surface is 
relatively high and comparable to the amount of seepage. Evaporation decreases almost linearly 
as relative humidity increases, as expected. Nevertheless, the impact of evaporation on the 
calculated seepage rate is small for these high relative humidity values. Neglecting evaporation 
effects for the analysis of seepage-rate data from Niches 3107 and 4788, where relative humidity 
was close to 100%, is thus acceptable. Note that evaporation in the open, ventilated ECRB Cross 
Drift is considered substantial and is thus incorporated into the respective seepage models. 
107 MDL-NBS-HS-000004 REV02 April 2003 Seepage Calibration Model and Seepage Testing Data 
20 
15 
10
5
0 
85 80 
Figure 33. Effect of relative humidity on seepage and evaporation percentages, based on the simulation 
of a liquid-release test in interval 1011 ft of borehole #4 in Niche 1620. Flow 
percentages are plotted 13 days after the start of liquid release. See Figure 34 for the 
seepage and evaporation rates as a function of time with relative humidity of 85%. Note 
that flow percentage is calculated relative to liquid-release rate. Simulation results in 
output DTN: LB0302SCMREV02.001. 
Relative Humidity [%] 
6.8 DESCRIPTION OF BARRIER CAPABILITY 
In the unsaturated zone, percolation water encountering a waste emplacement drift is partly 
diverted around the opening on account of the capillary barrier effect. This effect is referred to as 
the seepage exclusion phenomenon (Philip et al. 1989 [105743]). Seepage exclusion reduces the 
amount of water entering the waste emplacement drift or prevents dripping altogether, i.e., the 
seepage flux is always smaller than the percolation flux (see also discussion in Section 6.3.1). 
This barrier effect is an attribute of the natural system at Yucca Mountain, where unsaturated 
conditions prevail. 
The seepage-exclusion phenomenon has been extensively described in the literature (see Philip et 
al. 1989 [105743] and references therein). The related water diversion capability is exploited in 
practical applications for the protection of landfills and hazardous waste sites (the corresponding 
engineering designs are sometimes referred to as Richards Barriers). These standard engineering 
applications consider porous materials rather than fractured rocks. However, since the key 
factors affecting a capillary barrier are permeability and capillarity (see Section 6.3.3), which are 
properties of fractured rock, the same barrier effect can also be expected to apply at Yucca 
Mountain. 
MDL-NBS-HS-000004 REV02 108 
Flow Percentage 
U0080 
Seepage 
Evaporation
95 100 90 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
This hypothesis has been extensively tested through the in situ seepage experiments described in 
BSC (2001 [158463], Sections 6.2 and 6.11), Trautz and Wang (2002 [160335]) and Section 6.5 
above. All experiments show that the seepage rate is less than the injection rate. Because of 
storage effects and evaporation, the reduced seepage rate by itself does not conclusively prove 
that water is diverted around the opening, which would assess the barrier capability of the natural 
system at Yucca Mountain. Evidence that seepage exclusion and flow diversion occurs is 
provided by the numerical model, which accounts for storage and evaporation effects, and which 
is capable of reproducing the observed seepage data. The following mass balance can be 
formulated: 
+ + + = M M M (18) diversion release seepage storage evaporation 
n 
8
6
4
2
0 
-2 
-4 
-6 
-8 
M 
Injection Data 
Seepage Data 
Calc. Injection 
Calc. Seepage 
Calc. Deep Flow 
Calc. Evaporation 
Calc. Storage 
50 40 30 20 10 0 
detailed rate balance on Day 10 (denoted by Example Time) is given in Table 15. 
Seepage-rate data from DTN: LB0211NICH5LIQ.001 [160792]; simulation results in 
output DTN: LB0302SCMREV02.001. 
10 
Flow Rate [ml/min] 
M 
The cumulative amount of water that was released (Mrelease ) and that seeped into the capture 
system (Mseepage ) are known from measurements. Cumulative evaporation (Mevaporatio ) is 
calculated by the model. The rest of the water is either stored in the formation above the opening 
(Mstorage ) or was diverted around the drift and percolated to depth (Mdiversion ). Both terms can be 
inferred from the calibrated model. A similar balance can be written for steady-state rates (where 
the storage term drops out) instead of cumulative amounts of water. The rate balance for the 
simulation of a typical liquid-release test in Niche 1620 is shown in Figure 34. 
MDL-NBS-HS-000004 REV02 
Time [day since 09/17/2002 16:20] 
Figure 34. Rates of water released, evaporated, diverted around the niche, stored in the formation 
above the niche, and captured in the seepage collection system as a function of time. A 
109 
Example Time 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
Measured and calculated flow rates for typical liquid-release test in borehole #4 of Niche 1620, 
on Day 10 (since 9/27/2002 16:20) are summarized in Table 15. 
Table 15. Mass Balance for Typical Seepage Test in Borehole #4 of Niche 1620, on 
9/27/2002 at 16:20 (Day 10). Note that the model release includes an 
ambient infiltration rate of 2.20 mm/year (0.067 ml/min). Measured data 
derived from DTN: LB0211NICH5LIQ.001 [160792]; simulation results in 
output DTN: LB0302SCMREV02.001. 
Yucca Mountain. 
Calculated Flow Rate (ml/min) 
Release 9.915 (100.00%) 9.967 (100.00%) 
Seepage 1.130 (11.40%) 1.132 (11.36%) 
Diversion  6.707 (67.30%) 
Evaporation  1.798 (18.04%) 
Storage  0.329 (3.30%) 
The mass balance indicates that a substantial amount of water is diverted around the opening, 
confirming the seepage exclusion phenomena and barrier potential of the unsaturated zone at 
The mass-balance calculation presented above includes measured values and quantities inferred 
from the calibrated model. The key quantity of interest demonstrating the barrier capability of 
the natural system (Mdiversion ) was obtained from the model. To obtain direct evidence that flow 
diversion occurs during liquid-release tests, a horizontal slot (also referred to as batwing; see 
schematic in Figure 4) was excavated from the side of Niche 1620. Water released near the 
center above the niche and eventually collected in the slot at the spring line (Figure 35) must 
have been diverted around the opening, corroborating the barrier capability of the seepageexclusion 
effect known to exist in unsaturated formations. 
In summary, partial or complete diversion of water around underground openings on account of 
the capillary barrier effect reduces seepage or even prevents water from dripping into a waste 
emplacement drift. This effective barrier at the interface between the natural and engineered 
system has the potential to significantly reduce corrosion, waste dissolution, mobilization of 
radionuclides and their transport from the invert of the waste emplacement drift to the accessible 
environment. In addition, the extent of the shadow zone beneath the drift and its effectiveness 
in delaying radionuclide transport is strongly related to the seepage-exclusion phenomenon. (For 
a discussion of the shadow zone, see also Philip et al. (1989 [105743])). The barrier capability of 
flow diversion around underground openings in unsaturated fractured formations has been 
established theoretically, through modeling and extensive field testing at Yucca Mountain. The 
Seepage Model for Performance Assessment (SMPA) examines the effectiveness of the seepage 
barrier for a multitude of conditions. Uncertainty and spatial variability in the seepage-relevant 
model parameters have been quantified and will be propagated through the downstream seepage 
models. 
Measured Flow Rate (ml/min) 
110 
MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
Flow Rate [ml/min] 
12 
11 
10
9
8 Seepage data 
in main niche Calc. seepage 
in main niche 
7
6
5
4
3
2
1
0 
Seepage data 
in left batwing 
30 
Calc. seepage 
in left batwing 
10 40 20 0 
Time [day since 07/15/2002 12:45] 
Figure 35. Water collected in the slot on the side of Niche 1620 proving flow diversion around the 
opening. Liquid was released in interval 2829 ft of borehole #5. All curves representing 
measured data are derived from DTN: LB0209NICH5LIQ.001 [160796]; simulation results 
in output DTN: LB0302SCMREV02.001. 
April 2003 111 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
MDL-NBS-HS-000004 REV02 
INTENTIONALLY LEFT BLANK 
112 
U0080 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
7. VALIDATION 
7.1 LEVEL OF RELATIVE MODEL IMPORTANCE 
According to AP-SIII.10Q, Models, Section 3.16, model validation is a process used to establish 
confidence that a mathematical model and its underlying conceptual model adequately represent 
with sufficient accuracy the system, process, or phenomenon in question. 
While rigorous model testing is fundamentally not possible (Oreskes et al. 1994 [152512]), 
confidence can be gained that the Seepage Calibration Model (SCM) is adequate for its intended 
purpose to the level of confidence required by the models relative importance to the potential 
performance of the repository system. 
The primary purpose of the SCM is to provide a general modeling framework for the development 
of the Seepage Model for Performance Assessment (SMPA). The purpose of the SMPA is 
to provide predicted seepage rates over a large range of conditions. These seepage rates will be 
further abstracted and used in a probabilistic performance assessment (PA) calculation. 
The secondary purpose of the SCM is to provide seepage-relevant 1/  estimates. This information 
will be used in the seepage abstraction process for the development of probabilistic parameter 
distributions. However, additional data and assumptions enter the development of these 
distributions: the PA calculations do not rely solely on the 1/  values provided by the SCM, but 
may use broader sampling distributions to reflect additional uncertainties and variabilities. 
The relative importance of the SCM to the potential performance of the repository system has 
been evaluated based on sensitivity analyses as documented in Risk Information to Support 
Prioritization of Performance Assessment Models (BSC 2002 [160780]). These sensitivity 
analyses indicate that seepage rate does not significantly change the mean annual dose estimate 
for the nominal scenario (BSC 2002 [160780], Section 3.3.2). For the igneous activity groundwater 
release scenario, which is dominated by the solubility-limited radionuclides 239Pu and 
240Pu, the annual dose is affected by the amount of flow contacting the waste. Nevertheless, it 
was concluded that the details of the seepage model do not play a significant role in the estimate 
of mean annual dose. Consequently, the lowest level of validation (Level I) for the TSPA 
seepage model and the process models supporting it (such as the SCM) was considered appropriate 
(BSC 2002 [160780], Section 4.3), requiring a demonstration that basic physical principles 
are appropriately represented. 
The guidance of BSC (2002 [160313], p. B-1) refers to the minimum level of model validation. 
However, the SCM is evaluated against the stricter acceptance criteria as defined in the TWP for 
this Model Report (BSC 2002 [160819], Attachment I, Section I-4-1). 
7.2 VALIDATION ACTIVITIES AND CONFIDENCE EVALUATION CRITERIA 
The model validation activities and acceptance criteria presented in the remainder of this section 
follow those of the TWP for this Model Report (BSC 2002 [160819], Attachment I, Section I-4- 
1); they exceed the Level I validation activities outlined in BSC (2002 [160780], Section 4.3) 
April 2003 113 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
and BSC (2002 [160313], p. B-1). Confidence in the adequacy of the SCM for its intended 
purpose has been gained during the model development process as well as through pre-test 
predictions of seepage experiments and rigorous post-development model testing as outlined in 
the TWP for this Model Report (BSC 2002 [160819], Attachment I, Section I-4-1). 
7.2.1 Confidence Building during Model Development 
During model development, input data and parameters have been carefully selected (1) to best 
represent the conditions encountered at the liquid-release test sites, (2) to be compatible with the 
general modeling approach and parameters from upstream models, and (3) to provide a useful 
conceptual basis and mathematical model for the downstream modeling activities. Seepage-rate 
data used for calibration have been selected to minimize the potential estimation bias (see 
Section 6.6.3.2). Moreover, the model is calibrated using a minimum number of adjustable 
parameters (see Section 6.6.3.1). Being able to match seepage-rate data by adjusting only one or 
two parameters provides confidence that the model appropriately represents the relevant physical 
processes and features at the experimental site. Sensitivity analyses have been performed in 
support of the parameter selection process and to test the appropriateness of certain model 
simplifications. 
The simulations are carried out using a well-established numerical simulator, which ensures 
mass conservation at each time step. Nevertheless, an explicit mass-balance calculation has been 
performed (see Section 6.8) to demonstrate that basic physical principles such as conservation 
of mass (BSC 2002 [160780], p. 4-2) are appropriately represented. 
The main activity presented in this Model Report is the calibration of the SCM against seepagerate 
data from liquid-release tests conducted at Yucca Mountain. Development of the SCM is 
closely coupled with seepage testing in niches and along boreholes of the systematic hydrologic 
characterization program. The iteration between testing and modeling lead to improvements in 
test design and confidence in the modeling approach. As outlined in Section 6.3.4, the approach 
ensures that the estimated drift-scale parameters are site-specific, seepage-relevant, and modelrelated, 
and therefore suitable for the prediction of seepage into waste emplacement drifts using 
the conceptually compatible Seepage Model for Performance Assessment. 
The uncertainty and spatial variability of seepage is evaluated and described by means of a 
parameter distribution (see Section 6.6.4), which is provided as input to the seepage abstraction 
process. 
Natural analogues as those reported in TDR-NBS-GS-000027 REV 00 ICN 02, Natural 
Analogue Synthesis Report (BSC 2002 [160405], Section 8) provide evidence that the concept of 
seepage exclusion describes a process that actually occurs in caves, lava tubes, rock shelters and 
buildings. The qualitative evidence for seepage exclusion and flow diversion was substantiated 
by quantitative seepage measurements in limestone caves. These studies show that seepage is 
considerably smaller than the pertinent percolation flux (BSC 2002 [160405], Section 8.2), 
corroborating the seepage testing and modeling results at Yucca Mountain. Calcite-deposition 
data in lithophysal cavities (see Section 6.4.3) further corroborate the seepage exclusion concept. 
114 MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
7.2.2 Post-Development Activities 
7.2.2.1 Corroboration with Data from Field Experiments 
Blind predictions of seepage rates were performed with the calibrated SCM, simulating tests that 
were not used for model calibration, and that involve a different portion of the fracture system 
and a different section of the drift or niche. If seepage rates are successfully predicted (according 
to an acceptance criterion discussed below), confidence is gained that the seepage process is 
adequately conceptualized in the SCM. The proposed modeling approach is therefore reasonable 
and can be used as the basis for the development of the predictive SMPA. This addresses the 
primary purpose of the SCM. 
Given the probabilistic nature of the TSPA calculations, a probabilistic acceptance criterion is 
adopted to ensure that prediction uncertainty is included in the validation process as well as in 
future model predictions. This addresses the secondary purpose of the SCM. The acceptance 
criteria were defined in the TWP (BSC 2002 [160819], Attachment I, Section I-4-1). The SCM 
will be considered validated if one of the following is met: 
(1) 95% of the measured late-time seepage-rate data fall within the 95% confidence region 
predicted by the model. A poor prediction of early-time seepage data is considered 
acceptable, because the intended use of the model does not include the accurate simulation 
of short-term, transient seepage events. Seepage will be calculated in response to 
steady percolation flux predictions. 
(2) The model overpredicts seepage. 
(3) An explanation can be found for why the observed and predicted seepage rates deviate 
significantly for a residual that fails to meet criteria (1) and (2) above, and this explanation 
does not concern and thus invalidate the general approach. 
The combination of Criteria (1) and (2) implies that the 95% confidence region should be 
regarded as one-sided, i.e., 95% of the measured seepage-rate data should be less than the upper 
bound of the uncertainty band. Figure 36 through Figure 44 show a two-sided error band where 
90% of the Monte Carlo simulations fall within that band, and 95% are between zero seepage 
(the physical minimum) and the upper bound. 
Note that these acceptance criteria are more strict than the general acceptance criterion of BSC 
(2002 [160780], p. 4-2) which only requires a demonstration that basic physical principles such 
as conservation of mass are appropriately represented. 
If the acceptance criteria are met, the SCM can be considered validated for its primary and 
secondary purpose, according to the definition in Section 3.16 of AP-SIII.10Q, Models. 
Several methods can be employed to assess the uncertainty of model predictions as a result of 
input parameter uncertainty. When computationally feasible, Monte Carlo simulations (Finsterle 
1999 [104367], pp. 7679) are the method of choice because they automatically account for 
nonlinearities in the model. A simplified linear uncertainty-propagation analysis can be chosen in 
cases where running many simulations is prohibitive. The first-order-second-moment (FOSM) 
115 MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
uncertainty propagation analysis (see Equation (16)) is valid for predicting uncertainties that can 
be approximated by a normal distribution (Finsterle 1999 [104367], pp. 7476). 
Both methods require that probability distributions be determined for each input parameter 
considered variable or uncertain. Since the seepage experiments used for validation were 
conducted at locations different from those used for calibration, input parameters other than the 
ones estimated during calibration can be considered variable or uncertain. Selecting  / 1 as the 
only parameter reduces the prediction uncertainty, i.e., it is more difficult for the SCM to pass 
the validation acceptance criteria. The approach followed here is therefore conservative. 
The van Genuchten parameter  / 1 is both spatially variable and uncertain. A measure of spatial 
variability was obtained by analyzing data from liquid-release tests performed at multiple 
locations. The resulting distribution is discussed in Section 6.6.4 and visualized in Figure 32. 
Small-scale heterogeneity has been identified as the key source of estimation uncertainty. For the 
validation of the model and parameters for the lower lithophysal zone, the combined impact of 
spatial variability and uncertainty was propagated through the prediction models by means of 
Monte Carlo simulations, in which the van Genuchten parameter  / 1 was sampled from a 
Normal distribution (with a mean of 580 Pa, a standard deviation of 100 Pa, and an admissible 
parameter range from 280 Pa to 880 Pa), and a new realization of the random permeability field 
was generated for each simulation. For the prediction of seepage rates (and their uncertainty 
bands) from liquid-release tests conducted in Niches 3107 and 4788 (middle nonlithophysal 
zone), linear uncertainty-propagation analysis was used. These FOSM analyses only consider 
spatial variability in the input parameters (standard deviations for log(  / 1 ) and log(k) were set 
to reasonable values of 0.1, and for log( .) to 0.3); uncertainty as a result of small-scale 
heterogeneity is not included. (Note that while the model itself is heterogeneous, only one 
realization can be considered in a FOSM analysis.) This approach is conservative because it 
reduces the range of predicted seepage rates, making it more difficult for the SCM to meet the 
stringent validation criteria outlined above. 
7.2.2.2 Corroboration through Comparison of Data with Pre-Test Model Predictions 
A representative seepage test conducted in Niche 1620 as planned in SITP-02-UZ-002 (BSC 
2001 [158200]) was predicted based on the proposed conceptual model, but using preliminary 
parameters, which were derived from testing in a single systematic testing borehole (SYBTECRB-
LA#2) in the Tptpll unit (see previous revision of Seepage Calibration Model and 
Seepage Testing Data, CRWMS M&O 2001 [153045]). The pre-test predictions were submitted 
to the TDMS under DTN: LB0207PRESCMN5.001 [160410] and DTN: 
LB0207PRESCMN5.002 [161192]. These predictions are qualitatively compared with seepage 
data collected in Niche 1620. It is important to realize that these pre-test predictions were made 
based on a preliminary understanding of seepage behavior in the Tptpll unit. 
The Seepage Calibration Model will be considered corroborated by pre-test predictions if (1) 
95% of the measured data fall within the 95% confidence region predicted by the model using 
linear uncertainty-propagation analysis, (2) if the model overpredicts seepage, or (3) if an 
explanation can be found for why the observed and predicted seepage rates deviate significantly. 
April 2003 116 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
7.2.2.3 Corroboration Through Technical Review by Publication in Refereed Journals 
The general modeling approach has been reviewed and published in a number of scientific 
journals (Birkholzer et al. 1999 [105170]; Finsterle 2000 [151875]; Salve et al. 2002 [161318]; 
Doughty et al. 2002 [161320]; Finsterle and Trautz 2001 [161148]; Trautz and Wang 2002 
[160335]). 
April 2003 
7.3 RESULTS OF MODEL VALIDATION ACTIVITIES 
In this section, the range of predicted seepage rates is compared to seepage-rate data collected 
from liquid-release tests that were not used for model calibration. The range was evaluated by 
means of Monte Carlo simulations (all tests in lower lithophysal zone and short-term tests in 
Niche 3650) and using first-order-second-moment (FOSM) error propagation analyses (tests in 
Niches 3107 and 4788, middle nonlithophysal zone). The indicated range contains 90% of the 
Monte Carlo simulation results, orif FOSM error propagation analysis is usedrepresents the 
90% confidence band. Note that the linearity and normality assumption inherent in FOSM breaks 
down for large standard deviations and for experiments near or below the seepage threshold, 
where nonlinearities prevail. If no seepage is predicted with the mean parameter set, the 
uncertainty band vanishes. Furthermore, FOSM may assign a certain probability to negative 
seepage rates. This specific artifact of the normality assumption inherent in FOSM is of no 
concern because it only affects the lower bound of the predicted seepage rates. 
117 
SYBT-ECRB-LA#2, Lower Lithophysal Zone 
Three liquid-release tests (Events 5254 of Table 11) were performed in zone 1 of borehole 
SYBT-ECRB-LA#2. No data from this zone have been used for model calibration. Starting 
5/11/2000, 09:30, approximately 652 liters of water were released at a very high average rate of 
approximately 464 ml/min. A second test was conducted starting 5/17/2000, 11:39, in which 
about 20 liters of water were released at an approximate rate of 35 ml/min. The final, long-term 
seepage test started on 5/23/2000, 14:22, releasing approximately 334 liters of water at an 
average rate of 26 ml/min (Finsterle 2002 [161043], p. 74). Input files for simulating this test 
sequence are created analogous to the procedure described in Section 6.6.2 (Finsterle 2002 
[161043], pp. 8283). The software iTOUGH2 V5.0 (LBNL 2002 [160106]) is used to perform 
100 Monte Carlo simulations. The resulting predictions of seepage rates into the drift are shown 
in Figure 36. 
The calibrated SCM predicts seepage rates for the first test event that are higher than the 
observed data (Figure 36a). This result is expected because the high release rate caused an 
unknown amount of the seepage water to bypass the capture system, i.e., the measured seepage 
rates are known to be too low. This test event therefore cannot be used for rigorous model 
validation, but it does serve to qualitatively corroborate the SCM predictions. 
As shown in Figure 36b and Figure 36c, the measured seepage-rate data for the lower-rate test 
events lie within the band containing 90% of the Monte Carlo simulations. Thus, an interpretation 
of probabilistic seepage predictions made with the calibrated SCM would not lead to erroneous 
statements about seepage, meeting the validation acceptance criterion. 
MDL-NBS-HS-000004 REV02 Measured Seepage 
6.2 6.4 
Seepage Calibration Model and Seepage Testing Data 
600 
500 
400 
300 
200 
100
0 
-1000 
(a) 
Rate [ml/min] Rate [ml/min] 
0 
-10 
-20 
(b) 
50 
40 
30 
20 
10
0 
-1012 
(c) 
Rate [ml/min] 
60 
50 
40 
30 
20 
10 
Figure 36. Liquid-release rates, measured seepage rates, and range of predicted seepage rates 
containing 90% of the 100 Monte Carlo simulations of the experiment conducted in zone 1 
of borehole SYBT-ECRB-LA#2; (a) Event 52, (b) Event 53, and (c) Event 54. All curves 
representing measured data are derived from DTN: LB00090012213U.002 [153154]; 
simulation results in output DTN: LB0302SCMREV02.001. 
Predicted Range of Seepage 
18 
Time [days since 5/11/2000, 09:30] 
20 
MDL-NBS-HS-000004 REV02 
Liquid Release 
Predicted Range of Seepage 
0.75 
Measured Seepage 
(Actual Seepage Higher) 
0.5 0.25 
Time [days since 5/11/2000, 09:30] 
Liquid Release 
Predicted Range of Seepage 
6.8 6.6
Measured Seepage 
Time [days since 5/11/2000, 09:30] 
Liquid Release 
16 14 
118 
U0080 
1 
7 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
A long-term liquid-release test was conducted in zone 2 of borehole SYBT-ECRB-LA#2, 
starting 5/11/2000, 05:20 (Events 55 and 56 of Table 11). Figure 37 shows the liquid-release 
rate, the measured seepage rate, and the range of predicted seepage rates containing 95% of 100 
Monte Carlo simulations. Water release occurs at a rate of approximately 30 ml/min for more 
than two weeks. (The noise seen in the release and seepage-rate data changes with time as the 
water tank is emptied or filled, respectively.) It takes about 10 days for the water to migrate to 
the drift ceiling and to build up sufficient saturation for seepage to occur. The fluctuations in the 
observed seepage rates reflect the change in ventilation conditions during daytime (ventilation is 
on) and nighttime and weekends (ventilation is off), which is approximately implemented in the 
model by changing the water potential in the drift, accounting for both the reduction in relative 
humidity and the reduction in the evaporative boundary-layer thickness during active ventilation 
(for details, see Finsterle (2002 [161043], pp. 134135)). The data fall within the uncertainty 
band of the model prediction, meeting the validation acceptance criterion. 
40 
35 
30 
25 
Liquid Release 
20 
15 
10
0 
15 5 -50 
Rate [ml/min] 
5 
Measured Seepage 
10 
Time [days since 5/23/2000, 05:20] 
Figure 37. Liquid-release rates, measured seepage rates, and range of predicted seepage rates 
containing 90% of the 100 Monte Carlo simulations of the experiment conducted in zone 2 
of borehole SYBT-ECRB-LA#2. All curves representing measured data are derived from 
DTN: LB00090012213U.002 [153154]; simulation results in output DTN: 
LB0302SCMREV02.001. 
Four consecutive liquid-release tests (Events 5760 of Table 11) were performed in zone 3 of 
borehole SYBT-ECRB-LA#2. Starting 5/17/2000, 11:39, more than 1000 liters of water were 
released during the 41-day testing period. However, seepage occurred only during the last 1  
days of testing (see Figure 38), i.e., shortly before operational constraints terminated the test on 
6/27/2000, 09:37. Only about 1 liter seeped into the drift. Furthermore, the early-time seepage 
rate is highly dependent on the formation storage capacity, which again is of no relevance for the 
ultimate purpose of the SCM. The calibrated SCM predicts early seepage initiation and a seepage 
rate that is somewhat higher than the observed values. Nevertheless, the data lie within the 
simulation uncertainty band, i.e., the acceptance criterion for model validation is met. 
Predicted Range of Seepage 
119 April 2003 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
Rate [ml/min] 
55 
50 
45 
40 
35 
30 
25 
20 
15 
10
5
0 
-5 
39.5 -1039 
Predicted Range of Seepage 
40 
Time [days since 5/17/2000, 11:39] 
Figure 38. Liquid-release rates, measured seepage rates, and range of predicted seepage rates 
containing 90% of the 100 Monte Carlo simulations of the experiment conducted in zone 3 
of borehole SYBT-ECRB-LA#2. All curves representing measured data are derived from 
DTN: LB00090012213U.002 [153154]; simulation results in output DTN: 
LB0302SCMREV02.001. 
SYBT-ECRB-LA#3, Lower Lithophysal Zone 
Water was released from zone 2 of borehole SYBT-ECRB-LA#3 at various rates over a period 
of 2 months (Events 7276 of Table 11) without inducing any observable seepage. No data from 
this zone have been used for model calibration. While most of the 100 Monte Carlo simulations 
resulted in zero seepage, the upper bound of the confidence band is determined by the few 
realizations that promote seepage (see Figure 39). The validation test obviously meets the 
acceptance criteria. 
Rate [ml/min] 
100 
90 
80 
70 
60 
50 
40 
30 
20 
10
0 
-10 
-200 
Predicted Range of Seepage 
20 40 
Liquid Release 
Time [days since 5/17/2001, 15:33] 
Figure 39. Liquid-release rates, measured seepage rates, and range of predicted seepage rates 
containing 90% of the 100 Monte Carlo simulations of the experiment conducted in zone 2 
of borehole SYBT-ECRB-LA#3. All curves representing measured data are derived from 
DTN: LB0203ECRBLIQR.001 [158462]; simulation results in output DTN: 
LB0302SCMREV02.001. 
Measured Seepage 
60 
120 MDL-NBS-HS-000004 REV02 
U0080 
Liquid Release 
Measured Seepage 
40.5 41 
April 2003 Seepage Calibration Model and Seepage Testing Data 
Niche 1620, Borehole #5, Interval 2829 ft, 05/06/2002, Lower Lithophysal Zone 
Water was released from interval 2829 ft of borehole #5 in Niche 1620 starting on 5/6/2002 at 
different rates for 4 days (Event 78 of Table 11). Testing resumed again on 5/16/2002 at a rate of 
approximately 60 ml/min for 5 days, resulting in observable seepage (Event 81) as shown in 
Figure 40. These test data were not used for calibration. During the first 4 days, the release rate 
fluctuated significantly, and the test was terminated due to data-logger problems while the 
seepage rate was still increasing (before it reached near-steady-state conditions). Because the 
calibrations were performed to match the late-time response (see Section 6.6.3.2), the model 
prediction during this initial 4 days overestimated the observed seepage rates, meeting the 
validation acceptance criteria. The release rate during the second period (after 5/16/2002) was 
relatively constant and allowed enough time for the seepage rate to reach an approximately 
constant rate. The late-time seepage-rate data in this period fall within the uncertainty band of the 
model prediction, meeting the validation acceptance criteria. 
140 
120 
100 
80 
60 
40 
20
0 
0 
Predicted Seepage 
Range 
5 
Time [day since 05/06/2002 09:45] 
Figure 40. Liquid-release rates, measured seepage rates, and range of predicted seepage rates 
containing 90% of the 100 Monte Carlo simulations of the experiment conducted in 
interval 2829 ft of borehole #5 in Niche 1620, starting on 05/06/2002. All curves 
representing measured data are derived from DTN: LB0207NICH5LIQ.001 [160408]; 
simulation results in output DTN: LB0302SCMREV02.001. 
Flow Rate [ml/min] 
Liquid Release 
Measured 
Seepage 
15 10 
Niche 1620, Borehole #5, Interval 2829 ft, 07/15/2002, Lower Lithophysal Zone 
Water was released from interval 2829 ft of borehole #5 in Niche 1620 starting on 7/15/2002 at 
different rates for 34 days, resulting in observable seepage (Events 8688 of Table 11). The 
seepage data of the first 14 days was used for calibration (see Figure 27). Water released from 
interval 2122 ft of borehole #3 between 7/31/2002 (Day 15) and 8/14/2002 (Day 25) was 
partially collected by the capture system intended for borehole #5 (see Figure 17, Days 210 
through 221). Therefore, only data between Day 25 and Day 35 is used for validation. Most of 
the 100 Monte Carlo simulations resulted in zero seepage during this validation period. The 
MDL-NBS-HS-000004 REV02 121 
U0080 
April 2003 Seepage Calibration Model and Seepage Testing Data 
observed seepage rate falls within the 90% confidence interval and thus meets the acceptance 
criteria (see Figure 41). 
30 
25 
20 
15 
10
5
0 
-5 
Liquid Release 
15 20 
Predicted Seepage 
Range 
10 0 
Measured 
Seepage 
5 
Time [day since 07/15/2002 12:45] 
Figure 41. Liquid-release rates, measured seepage rates, and range of predicted seepage rates 
containing 90% of the 100 Monte Carlo simulations of the experiment conducted in 
interval 2829 ft of borehole #5 in Niche 1620, starting 07/15/2002. Effective validation 
period is between Day 25 and Day 35. All curves representing measured data are derived 
from DTN: LB0209NICH5LIQ.001 [160796]; simulation results in output DTN: 
LB0302SCMREV02.001. 
Niche 1620, Borehole #4, Interval 1011 ft, Lower Lithophysal Zone 
Water was released from interval 1011 ft of Borehole #4 in Niche 1620 starting on 9/17/2002 
and lasting for approximately one month. Two rates were applied; Event 89 (see Table 11) (Day 
0 to Day 13) resulted in observable seepage and was used for calibration (see Figure 25). Event 
90 (Day 14 to Day 31) did not result in observable seepage and is used for validation. While 
most of the 100 Monte Carlo simulations resulted in zero seepage during this validation period, a 
few simulations yielded seepage and thus a non-zero upper bound of the confidence region. The 
validation meets the acceptance criteria (see Figure 42). 
122 
Flow Rate [ml/min] 
MDL-NBS-HS-000004 REV02 
U0080 
40 35 30 25 
April 2003 Flow Rate [ml/min] 
U0080 Seepage Calibration Model and Seepage Testing Data 
11 
10
9
8
7
6
5
4
3
2
1
0 
-1 
Predicted Seepage 
Range 
10 30 25 0 
Measured 
Seepage 
5
Time [day since 09/17/2002 16:20] 
Figure 42. Liquid-release rates, measured seepage rates, and range of predicted seepage rates 
containing 90% of the 100 Monte Carlo simulations of the experiment conducted in 
interval 1011 ft of borehole #4 Niche 1620. Data for Days 1 through 13 were used for 
calibration; validation period is between Day 14 and Day 31. All curves representing 
measured data are derived from DTN: LB0211NICH5LIQ.001 [160792]; simulation results 
in output DTN: LB0302SCMREV02.001. 
Liquid Release 
20 15 
123 
Niche 3107, Middle Nonlithophysal Zone 
Predictions of seepage rates from eight liquid-release tests performed in Niche 3107 were 
performed. The prediction uncertainty as a result of spatial variability in the input parameters is 
evaluated using FOSM uncertainty-propagation analysis. 
Figure 43 shows the observed seepage-rate data, the predicted seepage rates, and the simulation 
uncertainty bands for the eight liquid-release tests performed in interval UM 4.885.18 and 
interval UL 5.495.80 of Niche 3107. Based on the acceptance criteria outlined in Section 7.2, 
seven of the eight tests are considered acceptable. In Test UM 4.885.18 (Event 12 of Table 11), 
which started 10/11/1999, the observed late-time seepage rates are slightly larger than the 
relatively narrow uncertainty band. The tests would be considered acceptable if the chosen 
uncertainty in the input parameters were marginally increased (e.g., to account for uncertainty as 
a result of the stochastic nature of the underlying heterogeneous permeability field). Such an 
increase is likely to occur during seepage abstraction (see upcoming Model Report MDL-NBSHS-
000019 REV 00, which supercedes (CRWMS M&O 2001 [154291])). 
MDL-NBS-HS-000004 REV02 April 2003 42 
Seepage Calibration Model and Seepage Testing Data 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1 
0.0 
-0.10 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1 
0.0 
-0.10 
10.0 
9.0 
8.0 
7.0 
6.0 
5.0 
4.0 
3.0 
2.0 
1.0 
0.0 6 
7.0 
6.0 
5.0 
4.0 
3.0 
2.0 
1.0 
0.0 12 
Figure 43. Validation of Seepage Calibration Model and Tptpmn seepage-relevant parameters using 
data from Niche 3107 (Events 1, 2, 3, 4, 7, 9, 10, 11, 12 of Table 11). Linear uncertainty 
propagation analysis was used to calculate the uncertainty band of the model predictions. 
All curves representing measured data derived from DTN: LB0010NICH3LIQ.001 
[153144]; simulation results in DTN: LB0010SCMREV01.001 [154292]. 
Niche 3107 UL 3-10-99 
Simulated 
Simulation Uncertainty 
Measured 
36 24 12 
Elapsed Test Time [hours] 
Niche 3107 UL 9-17-99 
Simulated 
Simulation Uncertainty 
Measured 
48 
Elapsed Test Time [hours] 
Niche 3107 UM 9-21-99 
Simulated 
Simulation Uncertainty 
Measured 
36 30 24 18 12
Elapsed Test Time [hours] 
Niche 3107 UM 9-27-99 
Simulated 
Simulation Uncertainty 
Measured
60 48 36 24 
Elapsed Test Time [hours] 
MDL-NBS-HS-000004 REV02 
0.6 
0.5 
0.4 
0.3 
0.2 
0.1 
0.0 
-0.10 
3.0 
2.5 
2.0 
1.5 
1.0 
0.5 
0.0
0 
4.0 
3.0 
2.0 
1.0 
0.0 6 
9.0 
8.0 
7.0 
6.0 
5.0 
4.0 
3.0 
2.0 
1.0 
0.0 72 
124 
U0080 
Niche 3107 UL 3-30-99 
Simulated 
Simulation Uncertainty 
Measured 
144 96 48 
Elapsed Test Time [hours] 
Niche 3107 UM 4-30-99 
Simulated 
Simulation Uncertainty 
Measured 
96 48 
Elapsed Test Time [hours] 
Niche 3107 UM 9-23-99 
Simulated 
Simulation Uncertainty 
Measured 
24 18 12 
Elapsed Test Time [hours] 
Niche 3107 UM 10-11-99 
Simulated 
Simulation Uncertainty 
Measured 
72 60 48 36 24
Elapsed Test Time [hours] 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
Niche 4788, Middle Nonlithophysal Zone 
Predictions of seepage rates from five liquid-release tests performed in Niche 4788 were 
conducted. The prediction uncertainty as a result of uncertainty in the input parameters is evaluated 
using FOSM error propagation analysis. 
Figure 44 shows the observed seepage-rate data, the predicted seepage rates, and the simulation 
uncertainty bands for the five liquid-release tests performed in interval UL 7.627.93, interval 
UM 6.106.40, and interval UR 5.185.48 of Niche 4788. Based on the acceptance criteria 
outlined in Section 7.2, four of the five tests are considered acceptable. In Test UL 7.627.93 
(Event 40 of Table 11), which started 11/03/1999, the observed late-time seepage rates are 
slightly larger than the relatively narrow uncertainty band. The tests would be considered acceptable 
if the chosen uncertainty in the input parameters were somewhat increased, e.g., to account 
for aleatory uncertainty. 
The seepage-rate data from the test in interval UL 7.627.93, starting 11/3/1999, show some 
outliers that appear to be random, possibly caused by a disturbance of the balance measuring 
cumulative seepage mass. The seepage-rate data from the test in interval UR 5.185.48, starting 
12/7/1999, shows a spike approximately 60 hours after water release. The cause for this erratic 
behavior is unknown. Note, however, that despite these outliers, 95% of the observed data is 
within the predicted range. 
MDL-NBS-HS-000004 REV02 April 2003 125 Seepage Calibration Model and Seepage Testing Data 
3.0 
2.0 
1.0 
0.0 
-1.0 
-2.0 
-3.00 
2.0 
1.0 
0.0 
-1.0 
-2.00 
Niche 4788 UL 11-3-99 
6.0 
5.0 
4.0 
3.0 
2.0 
1.0 
0.0 18 
Elapsed Test Time [hours] 
Niche 4788 UL 1-24-00 
Simulated 
Simulation Uncertainty 
Measured 
288 216 144 72
Elapsed Test Time [hours] 
Niche 4788 UM 3-14-00 
Simulated 
Simulation Uncertainty 
Measured 
432 360 288 216 144 72 
Elapsed Test Time [hours] 
7.0 
Figure 44. Validation of Seepage Calibration Model and Tptpmn seepage-relevant parameters using 
data from Niche 4788 (Events 40, 42, 44, 47, and 49 of Table 11). Linear uncertainty 
propagation analysis was used to calculate the uncertainty band of the model predictions. 
All curves representing measured data derived from DTN: LB0010NICH4LIQ.001 
[153145]; simulation results in DTN: LB0010SCMREV01.001 [154292]. 
Niche 4788 UM 11-16-99 
Elapsed Test Time [hours] 
Niche 4788 UR 12-7-99 
Simulated 
Simulation Uncertainty 
Elapsed Test Time [hours] 
MDL-NBS-HS-000004 REV02 
Simulated 
Simulation Uncertainty 
Measured 
24 
5.0 
4.0 
3.0 
2.0 
1.0 
0.0 48 36 360 
6.0 
Measured 
5.0 
4.0 
3.0 
2.0 
1.0 
24 0.012 
126 
U0080 
Simulated 
Simulation Uncertainty 
Measured 
72 60 
72 60 48 36 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
Niche 3650, Middle Nonlithophysal Zone 
Twenty-seven liquid-release tests were performed in Niche 3650 (DTN: LB980001233124.004 
[136583]), thirteen resulting in seepage (see Table 11, Events 1339). The short-term tests are 
very sensitive to storage effects and the properties of a few fractures connecting the injection 
interval to the niche opening. Therefore, information derived from these tests is considered much 
less reliable than the long-term tests discussed before. Unlike in all the other tests, only the total 
seepage amount at the end of the experiment was recorded. 
These tests, while providing qualitative seepage information, were not used for calibration 
purposes to avoid a potential bias in the estimates. A similar bias renders them unsuitable for 
stringent model validation; the data and model predictions are shown here for completeness only. 
Their weight in the overall evaluation of the model validation activities should be considered 
minimal. 
Fifty Monte Carlo simulations were performed for the prediction of seepage rates in Niche 3650 
(Ahlers 2002 [161045], p. 57). Figure 45 shows the results of the Monte Carlo simulations. 
The data fall outside the range defined by the Monte Carlo simulations in only three of the 27 
test events. All three cases (Events 19, 20, and 22) concern data from interval UM 4.274.57. In 
a fourth test event conducted in the same interval (Event 21), the observed data point is near the 
upper bound of the predicted seepage range. Conditions in this interval seem to be specific and 
significantly different from those encountered elsewhere in Niche 3650 and the other two niches 
in the middle nonlithophysal zone. In several other intervals, the simulations show (minor) 
seepage where no seepage was observed. 
MDL-NBS-HS-000004 REV02 April 2003 127 U0080 Seepage Calibration Model and Seepage Testing Data 
Data 
Tptpmn Parameters 
MC Realizations 
Figure 45. Validation of Seepage Calibration Model and Tptpmn seepage-relevant parameters using 
data from Niche 3650. Monte Carlo simulations were performed to estimate the prediction 
range. Measured data are derived from DTN: LB980001233124.004 [136583]; simulation 
results in DTN: LB0010SCMREV01.001 [154292]. 
Pre-Test Prediction 
A blind pre-test prediction of a representative liquid-release test with a rate of 30 ml/min was 
performed prior to actual testing in Niche 1620. The predicted range of seepage rates (DTN: 
LB0207PRESCMN5.002 [161192], Figure 1) is shown in Figure 46, along with the measured 
seepage-rate data from a liquid-release test in borehole #5 of Niche 1620 (using a rate of 
approximately 25 ml/min). 
The prediction cannot be directly compared to the data because of the different release rates. 
However, it is evident that the predicted rates are consistent with the seepage amounts actually 
observed during the test. The model overpredicted the seepage rates by a small amount, which 
was expected because of conservative assumptions made in that model. (Note that the seepage 
percentagethe ratio between the seepage and release ratesis not expected to be constant; it 
increases with the release rate). In summary, the pre-test prediction of seepage rates performed 
with the preliminary Seepage Calibration Model meet the acceptance criteria outlined in Section 
7.2 and thus provides confidence in the appropriateness of the general modeling approach. 
MDL-NBS-HS-000004 REV02 April 2003 128 U0080 Seepage Calibration Model and Seepage Testing Data 
Flow Rate [ml/min] 
35 
Assumed Release Rate 
30 
25 
20 
15 
10 
Actual Release Rate 
mean + 2 Std. Dev. 
mean - 2 Std. Dev. 
5 
Range of Predicted Seepage
6 4 2 
Actual Seepage Rate
12 10 8 00 
Time [day since 07/15/2002 12:45] 
Figure 46. Comparison between pre-test seepage-rate prediction with preliminary Seepage 
Calibration Model and observed seepage-rate data. The range of predicted seepage 
covers the uncertainty band approximately on the 95% confidence level. The pre-test 
prediction results from DTN: LB0207PRESCMN5.002 [161192]; the seepage data from 
DTN: LB0209NICH5LIQ.001 [160796]. 
7.4 SUMMARY OF MODEL VALIDATION 
Estimates of the seepage-relevant van Genuchten parameter  / 1 for the lower lithophysal zone 
and the middle nonlithophysal zone of the Topopah Spring welded unit were obtained by 
calibration of a process model against seepage-rate data collected in the ECRB Cross Drift and in 
Niches 1620, 3107 and 4788. As outlined in Section 7.2.1, the development and calibration of 
the models is fully documented (see specifically Section 6 and the supporting references and 
scientific notebooks), generating confidence in the conceptual and mathematical model used as a 
basis for the analysis of seepage data. A preliminary version of the model was used for a pre-test 
prediction of a representative liquid-release test planned for Niche 1620. The predicted seepage 
rates were consistent with the associated test observations, corroborating the appropriateness of 
the conceptual model. 
The calibrated parameter values obtained at different locations were compiled and described by 
means of a statistical distribution to represent spatial variability within a given hydrogeologic 
unit (see Section 6.6.4). Small-scale heterogeneity was identified as the main source of estimation 
uncertainty. The combined impact of spatial variability and uncertainty was propagated 
through the prediction models during model validation by means of Monte Carlo simulations, in 
which the van Genuchten parameter  / 1 was sampled from the respective statistical distribution, 
and a new realization of the random permeability field was generated for each simulation. 
(Note that this approach is identical to that used in the downstream seepage modelsthe 
Seepage Model for Performance Assessment, which uses multiple realizations of the underlying 
129 MDL-NBS-HS-000004 REV02 April 2003 Seepage Calibration Model and Seepage Testing Data 
heterogeneous permeability field to account for uncertainty, and the sampling strategy employed 
during TSPA calculations, which makes use of an abstracted statistical distribution representing 
spatial variability.) 
The observed late-time seepage-rate data (1) fell within the range of predicted seepage rates in 
all test cases for the lower lithophysal zone, and in almost all test cases for the middle nonlithophysal 
zone, or (2) were lower than the predicted seepage rates in a few cases, i.e., the model 
prediction was conservative. The data were marginally higher in two longer-term tests (Events 
12 and 40) and in three short-term tests in Niche 3650 (Events 19, 20, and 22), which are considered 
of minor relevance. 
The conceptual basis and mathematical model of the Seepage Calibration Model has been 
presented to the technical community through publication in refereed scientific journals, passing 
the review process. 
Based on the evidence presented in Section 7.3, the conceptual and mathematical basis of the 
Seepage Calibration Model and the parameters derived from calibrating the model against 
seepage-rate data are considered adequate for the intended purpose and to the level of confidence 
required by the models relative importance to the postclosure performance of the proposed 
repository system. No further activities are needed to complete the validation of the SCM for its 
intended use. 
130 MDL-NBS-HS-000004 REV02 
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8. CONCLUSIONS 
8.1 SUMMARY AND CONCLUSIONS 
Seepage into waste emplacement drifts affects the performance of the proposed high-level 
nuclear waste repository at Yucca Mountain, Nevada. Theoretical analyses, numerical modeling 
studies, and field experiments suggest that seepage into underground openings excavated in 
unsaturated formations is smaller than the percolation flux at the given location. This is mainly a 
result of capillary pressures holding water in the formation, diverting it around the cavity, and 
preventing it from entering the underground opening. The effectiveness of this capillary barrier 
depends on the percolation flux, the hydrogeologic properties of the formation, the geometry of 
the drift, the properties of the drift surface, and the in-drift conditions determining the evaporation 
potential. 
This Model Report describes the development, calibration, and validation of the Seepage 
Calibration Model (SCM). The purpose of the SCM is to provide the conceptual basis for the 
Seepage Model for Performance Assessment (SMPA), which calculates seepage into waste 
emplacement drifts for a variety of hydrogeologic conditions. The SCM was calibrated against in 
situ seepage-rate data to provide seepage-relevant, model-related parameters appropriate for use 
in a drift-scale process model with a comparable model structure (such as the SMPA). These 
parameters will be used as base-case parameters for certain SMPA sensitivity analyses and will 
contribute to the development of parameter probability distributions for subsequent Performance 
Assessment calculations. 
Three-dimensional process models were developed, representing niche locations in the middle 
nonlithophysal zone of the Topopah Spring Tuff (Tptpmn) and one niche and three boreholes in 
the ECRB Cross Drift, which are located in the lower lithophysal zone of the Topopah Spring 
Tuff (Tptpll). Air-permeability data were geostatistically analyzed to provide the basis for 
generating heterogeneous, spatially correlated permeability fields. 
A total of 90 experiments using different release rates were performed (Table 11). Eighty-one of 
these test events were simulated with the SCM, a numerical process model that captures transient 
unsaturated flow through a heterogeneous fracture continuum and seepage into the underground 
openings. In addition, evaporation effects were accounted for when deemed significant. 
Measured seepage-rate data from 22 liquid-release tests were used to calibrate the SCM and to 
estimate the seepage-relevant van Genuchten capillary-strength parameter  / 1 (see Section 
6.6.3). The remainder of the seepage-rate data were used to validate the SCM, that is, to determine 
whether it is appropriate and adequate for its intended use (see Section 7.3). 
The capillary-strength parameter was determined by calibrating the model against multiple tests 
using different liquid-release rates. Some of these release rates induced a local percolation flux 
above the seepage threshold, i.e., water dripped into the opening and yielded seepage-rate data 
valuable for calibration. However, the joint inversion of multiple data sets also included data 
from tests performed below the seepage threshold. Moreover, the model was validated against 
tests conducted above and below the seepage threshold. That is, the system was probed and the 
model was validated for the critical range of percolation rates about the seepage threshold. 
131 MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
Seepage predictions for natural percolation fluxes that are even lower than the low fluxes (below 
the seepage threshold) induced during the low-rate tests will yield the correct result, namely zero 
seepage. As a result of a high-infiltration climate or strong flow focusing, the natural percolation 
flux may be high and exceed the seepage threshold. These would be the critical scenario for 
performance. Obviously, the parameters estimated from the liquid-release tests would be most 
suitable for those critical circumstances, because they were determined under similar high-rate 
conditions. In summary, the parameters determined from relatively high-rate liquid-release tests 
are appropriate and provide a solid basis for seepage predictions under low and higher natural 
percolation fluxes. 
The insignificant impact of reduced relative humidity on calculated seepage into closed-off 
niches in the middle nonlithophysal zone has been confirmed (see Section 6.7 and discussion in 
Section 6.3.3.4). Significant evaporation effects in the ventilated ECRB Cross Drift have been 
addressed through moisture control, monitoring of relative humidity, and inclusion of evaporation 
in the numerical model. 
The following general conclusions are drawn: 
 The testing and modeling approach documented in this Model Report is adequate for 
providing the conceptual basis and parameters for the TSPA seepage model. The 
approach consists of analyzing seepage by means of a numerical process model that is 
calibrated against seepage-rate data from liquid-release tests conducted within the 
repository host units. 
 The estimation of seepage-relevant, model-related, effective parameters on the 
appropriate scale is a methodology that reduces the risk of introducing significant 
systematic errors, provided that the structure of the prediction model (such as the 
SMPA) is consistent with the model used for calibration (the SCM). 
 Seepage properties are spatially variable. The variability has been examined by 
performing liquid-release tests at various sites along the ESF and the ECRB Cross 
Drift. Spatial variability in the estimated van Genuchten capillary-strength parameter 
 / 1 is relatively strong compared to the estimation uncertainty at a given location. The 
main contribution to the estimation uncertainty is small-scale heterogeneity that can 
only be described stochastically. Random fluctuations in seepage-rate data leads to 
insignificant uncertainty in the parameter estimates. 
 The seepage-relevant van Genuchten capillary-strength parameter  / 1 in the lower 
lithophysal zone is on the order of 580 Pa, with a standard deviation, representing 
spatial variability, of approximately 100 Pa. The corresponding values for the middle 
nonlithophysal zone are 600 Pa and 130 Pa. 
The general conclusions listed above must be viewed considering the caveats and limitations 
discussed throughout this Model Report and summarized in Section 8.2. Further justification for 
the modeling and analysis approach can be found in Section 8.3 below. 
April 2003 132 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
8.2 MODEL OUTPUT, UNCERTAINTIES, AND LIMITATIONS 
As outlined in Sections 1 and 6.1.1, this Model Report produces (1) a methodological and 
conceptual basis for the subsequent development of the Seepage Model for Performance 
Assessment (SMPA), and (2) seepage-relevant parameters that will be used for drift seepage 
abstraction. The parameter distribution developed as a result of the abstraction process will then 
be usedin combination with the results from the SMPAas input to the seepage TSPA model. 
The Seepage Calibration Model (SCM) is intended to be used only within this Model Report for 
parameter estimation purposes. 
The two products from this Model Reportconceptual model and model-related parameters 
are described below. 
Conceptual Basis for Seepage Prediction Models 
The conceptual basis to be used for the SMPA or similar modeling efforts to predict seepage has 
been described in Section 6.3; recommendations for downstream users are summarized in 
Section 8.4. The SCM must be viewed as an integral element of a consistent approach involving 
data analysis, parameter estimation, model prediction, and abstraction. The adequacy of the 
approach is further discussed in Section 8.3. Alternative approaches were described in Section 
6.4. 
Seepage-Relevant van Genuchten Capillary-Strength Parameter 
The second output from this Model Report consists of model-related estimates of the van 
Genuchten capillary-strength parameter  / 1 . The estimates were obtained through calibration of 
the SCM against seepage-rate data from liquid-release tests; they are summarized in Table 16. 
The estimates from the different locations are combined to obtain seepage characteristics for the 
two hydrogeologic units Tptpll and Tptpmn. The standard deviations reported in Table 16 reflect 
spatial variability. 
The estimates are uncertain because they are derived from limited data, which exhibit random 
and potentially systematic measurement errors, and because the model is a simplification of the 
real system, which introduces systematic and random modeling errors. Estimating model-related 
parameters mitigates the impact of some of the residual systematic errors. The following uncertainties 
have been evaluated: 
 The uncertainty as a result of undetermined details of small-scale heterogeneity was 
quantified for the  / 1 estimates in the Tptpll (see Table 14) by performing multiple 
inversions with different realizations of the underlying heterogeneous permeability 
field. Note, that the impact of this uncertainty on seepage predictions can be directly 
evaluated using the Seepage Model for Performance Assessment (SMPA; see 
upcoming REV 02 of CRWMS M&O 2000 [153314]), i.e., this uncertainty does not 
need to be incorporated in the parameter distribution used for sampling in TSPA 
calculations (see upcoming Model Report MDL-NBS-HS-000019 REV 00 (CRWMS 
M&O 2001 [154291])). 
133 MDL-NBS-HS-000004 REV02 April 2003 Seepage Calibration Model and Seepage Testing Data 
 Estimation uncertainty resulting from unexplained fluctuations in the seepage-rate data 
is propagated through the model and evaluated using Equation (14); its contribution to 
the overall parameter uncertainty is negligible (see Section 6.6.3.3). 
 A potential bias in the estimated parameters as a result of evaporation effects is 
minimized by an appropriate test design, moisture monitoring, and inclusion of evaporation 
effects into the model using site-specific relative humidity and evaporation-rate 
data. Sensitivity analyses were performed, demonstrating that residual uncertainty 
resulting from incomplete knowledge about the evaporative boundary-layer thickness 
in a ventilated drift and uncertainty in the relative humidity data is minor (see Sections 
6.6.3.1 and 6.7). The chosen values are cautiously realistic. 
 Sensitivity analyses were performed to examine the potential impact of selected, 
uncertain parameters on the estimation of seepage-relevant parameters (see Section 
6.6.3.1). These synthetic inversions also provided the correlation structure, indicating 
that a potential error in one (relatively insensitive) parameter can be partly compensated 
for by the estimation of the model-related parameters that are most sensitive. 
Table 16. Mean and Standard Deviation of Capillary-Strength Parameter  / 1 for Lower Lithophysal 
Zone and Middle Nonlithophysal Zone (DTN: LB0302SCMREV02.002) 
Unit Location Interval 1/  [Pa] 
SYBT-ECRB-LA#1 zone 1 Tptpll 
SYBT-ECRB-LA#2 zone 2 
zone 3 
SYBT-ECRB-LA#3 zone 1 
Niche 1620 borehole #4 
borehole #5 
UM Niche 3107 
UL 646 Niche 4788 
UM 603 
UR 427 
134 
534 
557 
535 
452 
671 
741 
741 Tptpmn 
# Characterizes spatial variability; the impact of uncertainty from undetermined details of smallscale 
heterogeneity on seepage predictions is directly evaluated in the Seepage Model for 
Performance Assessment. Other epistemic uncertainties are comparatively small. 
The primary caveats and limitations for usage of the results from the SCM are as follows: 
 The seepage models described in this Model Report provide estimates of the seepage 
flux averaged over a drift segment of a certain length. The seepage models are not 
expected to accurately predict individual seepage events or the precise spatial seepage 
distribution along a waste emplacement drift. By definition, the derived parameters (see 
Table 16) are related to the specific model structure used, i.e., these parameters are only 
applicable to a conceptual and numerical model similar to the SCM. (Note that the 
MDL-NBS-HS-000004 REV02 
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Mean 1/  [Pa] 
582 105 
604 131 
Std. Dev. [Pa]# 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
SCM and the SMPA are compatible in this sense.) The parameters are also process 
specific and scale dependent, i.e., while they can be considered optimal for seepage 
calculations on the drift scale, they are not necessarily applicable to other processes on 
different scales. If the downstream models cannot be developed to be fully compatible 
with the SCM, appropriate adjustments to the parameter values should be made. 
 The effective parameters derived in this Model Report capture many processes and 
features leading to dripping of formation water into a large underground opening. 
However, this does not include water dripping as a result of condensate accumulation 
on the drift surface or other in-drift moisture redistribution processes. 
 Seepage during the thermal period is examined separately in the TH Seepage Model 
(see BSC 2003 [161530]). 
8.3 ADEQUACY OF INPUT DATA AND MODELING APPROACH 
The two key elements of the overall approach described in this Model Report are (1) the use of a 
physically based, numerical process model as the basis for predicting seepage into large underground 
openings and (2) the calibration of this model against data from in situ liquid-release 
experiments. This approach is considered appropriate for the following reasons: 
 Unsaturated flow and seepage into drifts are complex, highly nonlinear phenomena. 
Hydrological process modeling is the preferred means for predicting seepage, because 
(1) the key process relevant to seepage (i.e., flow of water under unsaturated 
conditions) is directly modeled based on established physical laws, (2) only a few 
presumptions need to be made, because the model directly simulates the seepage 
process of interest, (3) the approach has the potential to simulate conditions that cannot 
be observed in the field, (4) numerical models are flexible enough to accommodate the 
nonideal initial and boundary conditions as they occur during seepage experiments. 
 The SCM is based on a process model that is consistent and compatible with the 
conceptual and numerical models used for calculating flow and transport in the unsaturated 
zone at Yucca Mountain. 
 Seepage experiments provide calibration data that reflect the process of interest. The 
measured data automatically reflect the factors and features pertinent to seepage. The 
effective parameters are capable of reproducing observed seepage data and are thus 
likely to yield reasonable seepage predictions. 
 The experiments test the capillary-barrier effect on the scale of interest, i.e., no upscaling 
is required. The water encountering the niche or drift is partly diverted around the 
opening, engaging the relevant portion of the fracture network on the appropriate scale. 
 Water is released from a localized point or line source, simulating the arrival of focused 
percolation water. Since the injection point lies outside the region of saturation buildup 
135 MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
caused by the capillary barrier effect, the (relatively short) flow distance from the 
release point to the opening does not significantly affect the seepage behavior. 
 The seepage experiments are conducted in the excavation-disturbed zone. The 
estimated parameters therefore reflect the seepage-relevant properties and conditions to 
be expected in the vicinity of a waste emplacement drift. 
Confidence into the appropriateness of the proposed approach was obtained by meeting 
acceptance criteria during the validation exercises (Section 7). While alternative approaches are 
viable (see Section 6.4), they often require currently unavailable characterization data, additional 
model assumptions, or extensive computational resources. Moreover, they usually need a 
calibration step similar to that described in this Model Reportthey suffer from the same 
potential limitations and caveats. The approach outlined in this Model Report is considered 
adequate for the intended purpose and for the use of the SCM and its results. 
8.4 RECOMMENDATIONS 
The modeling and data-analysis approach outlined in this Model Report are considered suitable 
for providing a solid basis and sufficient characterization data for predicting seepage into waste 
emplacement drifts in the repository host rock. The Seepage Calibration Model has been 
validated applying acceptance criteria that are stricter than those required based on an evaluation 
of the models relative importance to the potential performance of the repository system. The 
recommendations provided below concern the use of the conceptual model for further seepagerelated 
studies. 
 Seepage predictions should make use of a physically based process model capable of 
simulating unsaturated flow under viscous, capillary pressure, and gravitational forces. 
 A heterogeneous continuum model should be developed. The computational grid 
should capture the overall shape of the drift; small-scale surface roughness should not 
be explicitly discretized; lithophysal cavities should not be explicitly discretized; the 
nodal distance between the formation and the drift element should be 0.05 m; and 
gravity must be acting along those vertical connections. 
 Seepage-relevant input parameters should be used that are specifically determined for 
this conceptual model, based on data that represent the key mechanism affecting drift 
seepage. 
 Multiple prediction runs with different realizations of the underlying heterogeneous 
permeability field should be performed and appropriately averaged. 
MDL-NBS-HS-000004 REV02 April 2003 136 U0080 Seepage Calibration Model and Seepage Testing Data 
Table 17. Output DTNs 
8.5 OUTPUT DTNs 
All computer files needed to reproduce the model results discussed in this Model Report were 
submitted to the Technical Data Management System (TDMS). As mentioned in Section 1, the 
analyses of seepage-rate data from liquid-release tests performed in the middle nonlithophysal 
zone were fully documented in the previous revision of this report (CRWMS M&O 2001 
[153045]), and all related files were previously submitted to the TDMS under output DTN: 
LB0010SCMREV01.001 [154292]. The files supporting the analyses of data from the lower 
lithophysal zone are listed in Attachment I and are submitted with this Model Report under 
DTN: LB0302SCMREV02.001. Reproducibility by an appropriately qualified individual is 
possible by consulting this Model Report and the pertinent scientific notebook pages as listed in 
Table 7. Air-permeability data developed in the Model Report (see Table 10) and the 1/  estimates (see Table 16) are submitted to the TDMS under output 
DTN: LB0302SCMREV02.002. All data submittals described in this section and summarized in 
Table 17 are considered Technical Product Outputs (TPOs). 
DTN Description 
LB0302SCMREV02.001 Files supporting analyses of seepage data from lower lithophysal zone 
LB0302SCMREV02.002 Summary tables of derived air permeabilities and capillary-strength parameters 
April 2003 137 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
MDL-NBS-HS-000004 REV02 
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9. INPUTS AND REFERENCES 
The following is a list of the references cited in this document. Column 1 represents the unique 
six digit numerical identifier (the Document Input Reference System [DIRS] number), which is 
placed in the text following the reference callout (e.g., BSC 2002 [160819]). The purpose of 
these numbers is to assist the reader in locating a specific reference. Within the reference list, 
multiple sources by the same author (e.g., BSC 2002) are sorted alphabetically by title. 
139 
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Unsaturated Fractures under Evaporative Conditions. Water Resources Research, 
36, (2), 381-393. Washington, D.C.: American Geophysical Union. TIC: 246982. 
152512 Oreskes, N.; Shrader-Frechette, K.; and Belitz, K. 1994. Verification, Validation, 
and Confirmation of Numerical Models in the Earth Sciences. Science, 263, (5147), 
641-646. Washington, D.C.: American Association for the Advancement of Science. 
TIC: 248958. 
105743 Philip, J.R.; Knight, J.H.; and Waechter, R.T. 1989. Unsaturated Seepage and 
Subterranean Holes: Conspectus, and Exclusion Problem for Circular Cylindrical 
Cavities. Water Resources Research, 25, (1), 16-28. Washington, D.C.: American 
Geophysical Union. TIC: 239117. 
April 2003 142 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
100684 Pruess, K. 1987. TOUGH Users Guide. NUREG/CR-4645. Washington, D.C.: 
U.S. Nuclear Regulatory Commission. TIC: 217275. 
117112 Pruess, K.; Faybishenko, B.; and Bodvarsson, G.S. 1999. Alternative Concepts and 
Approaches for Modeling Flow and Transport in Thick Unsaturated Zones of 
Fractured Rocks. Journal of Contaminant Hydrology, 38, (1-3), 281-322. New 
York, New York: Elsevier. TIC: 244160. 
104252 Richards, L.A. 1931. Capillary Conduction of Liquids Through Porous Mediums. 
Physics, 1, 318-333. [New York, New York: American Physical Society]. TIC: 
225383. 
158324 Rohsenow, W.M. and Choi, H.Y. 1961. Heat, Mass, and Momentum Transfer. 
Englewood Cliffs, New Jersey: Prentice-Hall. TIC: 249864. 
161318 Salve, R.; Wang, J.S.Y.; and Doughty, C. 2002. Liquid-Release Tests in 
Unsaturated Fractured Welded Tuffs: I. Field Investigations. Journal of Hydrology, 
256, ([1-2]), 60-79. [New York, New York]: Elsevier. TIC: 253774. 
139195 Tokunaga, T.K. and Wan, J. 1997. Water Film Flow Along Fracture Surfaces of 
Porous Rock. Water Resources Research, 33, (6), 1287-1295. Washington, D.C.: 
American Geophysical Union. TIC: 242739. 
161044 Trautz, R. 2001. UZ Drift Scale Model (YMP-LBNL-RCT-DSM-1). Scientific 
Notebook SN-LBNL-SCI-157-V1. ACC: MOL.19990723.0302; 
MOL.20010201.0423; MOL.20010724.0145. 
156903 Trautz, R.C. 2001. Moisture Monitoring in the ESF (Phase 2)/Drift Seepage Test. 
Scientific Notebook YMP-LBNL-RCT-2. ACC: MOL.20011030.0706. 
160335 Trautz, R.C. and Wang, J.S.Y. 2002. Seepage into an Underground Opening 
Constructed in Unsaturated Fractured Rock Under Evaporative Conditions. Water 
Resources Research, 38, (10), 6-1 through 6-14. [Washington, D.C.]: American 
Geophysical Union. TIC: 253348. 
100610 van Genuchten, M.T. 1980. A Closed-Form Equation for Predicting the Hydraulic 
Conductivity of Unsaturated Soils. Soil Science Society of America Journal, 44, (5), 
892-898. Madison, Wisconsin: Soil Science Society of America. TIC: 217327. 
153449 Wang, J. 1999. Characterization of Yucca Mountain Percolation in the Unsaturated 
Zone - ESF Study. Scientific Notebook YMP-LBNL-JSW-6C. ACC: 
MOL.19991013.0462. 
161456 Wang, J.S. 2003. "Scientific Notebooks Referenced in Model Report U0080, 
Seepage Calibration Model and Seepage Testing Data MDL-NBS-HS-000004 REV 
02." Memorandum from J.S. Wang (BSC) to File, March 13, 2003, with attachments. 
ACC: MOL.20030320.0082. 
April 2003 143 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
104366 Wang, J.S.Y. and Elsworth, D. 1999. Permeability Changes Induced by Excavation 
in Fractured Tuff. Rock Mechanics for Industry, Proceedings of the 37th U.S. Rock 
Mechanics Symposium, Vail, Colorado, USA, 6-9 June 1999. Amadei, B.; Kranz, 
R.L.; Scott, G.A.; and Smeallie, P.H., eds. 2, 751-757. Brookfield, Vermont: A.A. 
Balkema. TIC: 245246. 
160442 Whelan, J.F.; Paces, J.B.; and Peterman, Z.E. 2002. Physical and Stable-Isotope 
Evidence for Formation of Secondary Calcite and Silica in the Unsaturated Zone, 
Yucca Mountain, Nevada. Applied Geochemistry, 17, ([6]), 735-750. [New York, 
New York]: Elsevier. TIC: 253462. 
Software Cited 
147402 CRWMS M&O 1999. Software Routine: ECRB-XYZ. V.03. PC. 30093-V.03. 
162369 Dynamic Graphics 2003. EarthVision. V4.0. SGI/IRIX 6.2. 10174-4.0-00. 
139918 LBNL (Lawrence Berkeley National Laboratory) 09/16/1999. Software Code: 
iTOUGH2. V4.0. SUN, DEC. 10003-4.0-00. 
152823 LBNL (Lawrence Berkeley National Laboratory) 10/17/2000. Software Routine: 
AddBound. V1.0. SUN w/Unix OS. 10357-1.0-00. 
152814 LBNL (Lawrence Berkeley National Laboratory) 10/17/2000. Software Routine: 
AddCoord. V1.0. SUN w/Unix OS. 10355-1.0-00. 
152816 LBNL (Lawrence Berkeley National Laboratory) 10/17/2000. Software Routine: 
CutDrift. V1.0. SUN w/Unix OS. 10375-1.0-00. 
152815 LBNL (Lawrence Berkeley National Laboratory) 10/17/2000. Software Routine: 
CutNiche. V1.2. SUN w/Unix OS. 10356-1.2-00. 
152824 LBNL (Lawrence Berkeley National Laboratory) 10/17/2000. Software Routine: 
MoveMesh. V1.0. SUN w/Unix OS. 10358-1.0-00. 
152826 LBNL (Lawrence Berkeley National Laboratory) 10/17/2000. Software Routine: 
Perm2Mesh. V1.0. SUN w/Unix OS. 10359-1.0-00. 
134141 LBNL (Lawrence Berkeley National Laboratory) 1999. Software Code: EXT. V1.0. 
Sun. 10047-1.0-00. 
134139 LBNL (Lawrence Berkeley National Laboratory) 1999. Software Code: GSLIB. 
V1.0MGAMV2V1.201. Sun. 10087-1.0MGAMV2V1.201-00. 
134136 LBNL (Lawrence Berkeley National Laboratory) 1999. Software Code: GSLIB. 
V1.0MSISIMV1.203. Sun, PC. 10001-1.0MSISIMV1.203-00. 
MDL-NBS-HS-000004 REV02 April 2003 144 U0080 Seepage Calibration Model and Seepage Testing Data 
153099 LBNL (Lawrence Berkeley National Laboratory) 2000. Software Code: GSLIB. 
V1.0GAMV3V1.201. SUN w/Unix OS. 10398-1.0GAMV3V1.201-00. 
153100 LBNL (Lawrence Berkeley National Laboratory) 2000. Software Code: GSLIB. 
V1.0SISIMV1.204. SUN w/Unix OS. 10397-1.0SISIMV1.204-00. 
152822 LBNL (Lawrence Berkeley National Laboratory) 2000. Software Routine: 
AddBorehole. V1.0. SUN w/Unix OS. 10373-1.0-00. 
152828 LBNL (Lawrence Berkeley National Laboratory) 2000. Software Routine: CutNiche. 
V1.3. SUN w/Solaris OS. 10402-1.3-00. 
160106 LBNL (Lawrence Berkeley National Laboratory) 2002. Software Code: iTOUGH2. 
V5.0. SUN UltraSparc., DEC ALPHA, LINUX. 10003-5.0-00. 
9.2 CODES, STANDARDS, REGULATIONS, AND PROCEDURES 
156605 10 CFR 63. Energy: Disposal of High-Level Radioactive Wastes in a Geologic 
Repository at Yucca Mountain, Nevada. Readily available. 
AP-2.22Q, Rev. 0, ICN 0. Classification Criteria and Maintenance of the Monitored Geologic 
Repository Q-List. Washington, D.C.: U.S. Department of Energy, Office of Civilian 
Radioactive Waste Management. ACC: MOL.20020314.0046. 
AP-SI.1Q, Rev. 4, Mod 0. Software Management. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. ACC: 
MOL.20030113.0149. 
AP-SIII.10Q, Rev. 1, ICN 0. Models. Washington, D.C.: U.S. Department of Energy, Office of 
Civilian Radioactive Waste Management. ACC: DOC.20030312.0039. 
9.3 SOURCE DATA, LISTED BY DATA TRACKING NUMBER 
153141 LB00090012213U.001. Air K Testing in Borehole SYBT-ERCB-LA#2 at CS 17+26 
in Cross Drift. Submittal date: 11/03/2000. 
153154 LB00090012213U.002. Liquid Release Tests from Borehole SYBT-ECRB-LA#2 at 
CS 17+26 in Cross Drift. Submittal date: 11/09/2000. 
153144 LB0010NICH3LIQ.001. Niche 3107 Seepage Test. Submittal date: 11/02/2000. 
153145 LB0010NICH4LIQ.001. Niche 4788 Seepage Test. Submittal date: 11/02/2000. 
145 MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
154292 LB0010SCMREV01.001. Input/Output for Seepage Calibration Modeling AMR 
U0080. Submittal date: 11/29/2000. 
153155 LB0011AIRKTEST.001. Air Permeability Testing in Niches 3566 and 3650. 
Submittal date: 11/08/2000. 
156904 LB0110AKN5POST.001. Niche 5 (1620 in ECRB) Post-Excavation Air-K. 
Submittal date: 11/12/2001. 
156879 LB0110ECRBLIQR.002. Systematic Testing in ECRB-SYBT-LA#1, 2/28/2001. 
Submittal date: 11/12/2001. 
160409 LB0110SYST0015.001. Developed Data for Systematic Testing. Submittal date: 
12/06/2001. 
158462 LB0203ECRBLIQR.001. Systematic Testing in ECRB-SYBT-LA#3 (May-July 
2001). Submittal date: 03/20/2002. 
159525 LB0205REVUZPRP.001. Fracture Properties for UZ Model Layers Developed from 
Field Data. Submittal date: 05/14/2002. 
160408 LB0207NICH5LIQ.001. Niche 5 Seepage Tests (CD 1620). Submittal date: 
07/09/2002. 
160410 LB0207PRESCMN5.001. Pre-Test Prediction of Seepage into Niche 5: Modeling 
Input/Output Files. Submittal date: 07/26/2002. 
161192 LB0207PRESCMN5.002. Pre-Test Prediction of Seepage into Niche 5: Data 
Summary. Submittal date: 07/26/2002. 
160796 LB0209NICH5LIQ.001. Niche 5 Seepage Tests (CD 1620), June-August 2002. 
Submittal date: 09/11/2002. 
160792 LB0211NICH5LIQ.001. Niche 5 Seepage Tests (CD 1620), August-October 2002. 
Submittal date: 11/14/2002. 
161733 LB0301N5CEILNG.001. Niche 5 Field Measurements of the Niche Ceiling and Slot 
Geometry. Submittal date: 01/27/2003. 
136583 LB980001233124.004. Liquid Release Test Data from Niche 3566 and Niche 3650 
of the ESF in Milestone Report, Drift Seepage Test and Niche Moisture Study: 
Phase 1 Report on Flux Threshold Determination, Air Permeability Distribution, and 
Water Potential Measurement. Submittal date: 11/23/1999. 
105888 LB990601233124.001. Seepage Data Feed to UZ Drift-Scale Flow Model for TSPASR. 
Submittal date: 06/18/1999. 
April 2003 146 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
106785 LB990701233129.001. 3-D UZ Model Grids for Calculation of Flow Fields for PA 
for AMR U0000, Development of Numerical Grids for UZ Flow and Transport 
Modeling. Submittal date: 09/24/1999. 
122757 LB990801233129.003. TSPA Grid Flow Simulations for AMR U0050, UZ Flow 
Models and Submodels (Flow Field #3). Submittal date: 11/29/1999. 
104055 LB997141233129.001. Calibrated Basecase Infiltration 1-D Parameter Set for the 
UZ Flow and Transport Model, FY99. Submittal date: 07/21/1999. 
152625 MO0002GSC00064.000. Exploratory Studies Facilities (ESF) Niche #3 (Niche 
3107) Borehole As-Built Information. Submittal date: 02/09/2000. 
152623 MO0002GSC00076.000. Exploratory Studies Facility (ESF) Niche #2 (Niche 3650) 
Borehole As-Built Information. Submittal date: 02/15/2000. 
152167 MO0003GSC00096.000. Exploratory Studies Facility (ESF) Niche #2 Profile 
Alignment. Submittal date: 03/01/2000. 
152176 MO0003GSC00103.000. Exploratory Studies Facility (ESF) Niche 3 Profile 
Alignment. Submittal date: 03/03/2000. 
152626 MO0008GSC00273.000. Exploratory Studies Facility (ESF) Niche 4, Profile 
Alignment. Submittal date: 08/01/2000. 
152627 MO0008GSC00310.000. ESF Niche #4 (Niche 4788) Borehole As-Built 
Information. Submittal date: 08/28/2000. 
155370 MO0009GSC00332.000. Exploratory Studies Facility (ESF) Niche 5, Plan and 
Profile As-Built. Submittal date: 09/27/2000. 
155369 MO0107GSC01061.000. As-Built Profile of Bat-Wing Excavation, Niche #5 ECRB. 
Submittal date: 07/03/2001. 
156941 MO0107GSC01069.000. ESF Niche #4 (Niche 4788) Borehole As-Built 
Information. Submittal date: 07/19/2001. 
160407 MO0209GSC02116.000. Enhanced Characterization of the Repository Block 
(ECRB) Niche 5 (Niche 1620), Borehole As-Built Information. Submittal date: 
09/23/2002. 
161496 MO0301SEPFEPS1.000. LA FEP List. Submittal date: 01/21/2003. 
April 2003 147 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
9.4 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER 
LB0302SCMREV02.001. Seepage-Related Model Parameters K and  / 1 : Supporting Files. 
Submittal date: 02/28/2003. 
LB0302SCMREV02.002. Seepage-Related Model Parameters K and  / 1 : Data Summary. 
Submittal date: 02/28/2003. 
148 MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
DRIFT 
10. ATTACHMENTS 
ATTACHMENT I-LIST OF COMPUTER FILES SUBMITTED WITH THIS MODEL 
REPORT UNDER DTN: LB0302SCMREV02.001 
ATTACHMENT II-VARIOGRAM FITTING 
ATTACHMENT III-MESH GENERATION FOR SIMULATION OF SEEPAGE TESTS IN 
ECRB 
ATTACHMENT IV-MESH GENERATION FOR SIMULATION OF SEEPAGE TESTS IN 
NICHES 3107, 3650, AND 4788 
ATTACHMENT V-MESH GENERATION FOR SEEPAGE TEST SIMULATIONS IN NICHE 
1620 
ATTACHMENT VI-PREPARATION OF SEEPAGE RATE AND RELATIVE-HUMIDITY 
DATA FOR THE SIMULATION OF LIQUID-RELEASE TESTS IN THE ECRB CROSS 
ATTACHMENT VII-EXECUTION OF MULTIPLE INVERSIONS OF DATA FROM ECRB 
149 April 2003 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
MDL-NBS-HS-000004 REV02 
INTENTIONALLY LEFT BLANK 
150 
U0080 
April 2003 Seepage Calibration Model and Seepage Testing Data 
ATTACHMENT I 
LIST OF COMPUTER FILES SUBMITTED WITH THIS MODEL REPORT UNDER 
DTN: LB0302SCMREV02.001 
Computer files needed to reproduce the model results discussed in this Model Report are listed 
below and are submitted to the TDMS under DTN: LB0302SCMREV02.001. Reproducibility is 
given by referring to the pertinent scientific notebook pages as listed in Table 7 and throughout 
this Model Report. Each file name is complemented with a short description of its contents 
and/or purpose. 
Meshgeneration/Permeability/ 
measured_log-k_12_N5.dat 
N5-airK.dat 
N5-airK.par 
N5-airK.var 
N5-airK.xls 
Meshgeneration/Roughness/ 
ceiling_N5_survey.dat 
ceiling_N5_interpolated.dat 
ceiling_N5_1.dat 
ceiling_N5_2.dat 
ceiling_N5_3.dat 
leftbatwing_N5_survey.dat 
leftbatwing_N5_interpolated.dat 
leftbatwing_N5_1.dat 
leftbatwing_N5_2.dat 
leftbatwing_N5_3.dat 
rightbatwing_N5_survey.dat 
rightbatwing_N5_interpolated.dat 
Table I-1 contains the files pertaining to the modeling of liquid-release tests conducted in Niche 
1620; Table I-2 contains those for the modeling of test in the ECRB Cross Drift. The files used 
to analyze data from seepage experiments in Niches 3107, 3560, and 4788 (located in the middle 
nonlithophysal zone) have been previously submitted under DTN: LB0010SCMREV01.001 
[154292]. 
Table I-1. File Name and Description for Modeling of Liquid-Release Tests in Niche 1620 
File/Folder Name 
Meshgeneration/ 
Description/File Location 
Measured air permeability data, input file mesh generation 
Measured air permeability data, input file to GAMV3 
Parameter file, input to GAMV3 
Computed variogram by GAMV3 
Excel file to compile variogram 
Compilation of the original survey and roughness 
measurements of the main niche 
Interpolated data on a regular x-y coordinate (10 cm x 10 cm 
grid) 
Interpolated main niche ceiling for 15.60<y<17.60 
Interpolated main niche ceiling for 18.60<y<20.60 
Interpolated main niche ceiling for 20.90<y<22.90 
Compilation of the original survey and roughness 
measurements of the left batwing niche 
Interpolated data on a regular x-y coordinate (10 cm x 10 cm 
grid) 
Interpolated left batwing niche ceiling for 15.60<y<17.60 
Interpolated left batwing niche ceiling for 18.60<y<20.60 
Interpolated left batwing niche ceiling for 20.90<y<22.90 
Compilation of the original survey and roughness 
measurements of the right batwing niche 
Interpolated data on a regular x-y coordinate (10 cm x 10 cm 
grid) 
MDL-NBS-HS-000004 REV02 
U0080 
April 2003 Attachment I1 Seepage Calibration Model and Seepage Testing Data 
rightbatwing_N5_1.dat 
rightbatwing_N5_2.dat 
rightbatwing_N5_3.dat 
Niche1620_ceiling.lpk 
Niche1620_ceiling.wmf 
Niche5SurveySummary.xls 
Interpolated right batwing niche ceiling for 15.60<y<17.60 
Interpolated right batwing niche ceiling for 18.60<y<20.60 
Interpolated right batwing niche ceiling for 20.90<y<22.90 
Tecplot file with the top view of the niche 5 ceiling 
Tecplot file with the top view of the niche 5 ceiling 
Excel file to compile the survey data 
TOUGH2 input file with MESHMAKER block 
TOUGH2 input file to perform a single time step 
Parameter file for generation of random permeability field 
Sequence of instructions to execute multiple steps of mesh 
generations 
Sequence of instructions to run the above Sequence of 
instructions multiple times by changing the permeability 
field seed number 
Sequence of instructions to run one time step 
Mesh with permeability realization #1 
Mesh with permeability realization #2 
Mesh with permeability realization #3 
Mesh with permeability realization #4 
Mesh with permeability realization #5 
Mesh with permeability realization #6 
Mesh with permeability realization #7 
Mesh with permeability realization #8 
Mesh with permeability realization #9 
Mesh with permeability realization #10 
Mesh with permeability realization #11 
Mesh with permeability realization #12 
Mesh with permeability realization #13 
Mesh with permeability realization #14 
Mesh with permeability realization #15 
Mesh with permeability realization #16 
Mesh with permeability realization #17 
Mesh with permeability realization #18 
Mesh with permeability realization #19 
Mesh with permeability realization #20 
Mesh with permeability realization #21 
Mesh with permeability realization #22 
Mesh with permeability realization #23 
Mesh with permeability realization #24 
Mesh with permeability realization #25 
Mesh with permeability realization #26 
Meshgeneration/N5BH4_10-11ft/ 
N5BH4_10-11ft 
onestep 
N5BH4_10-11ft_sisim.par 
sh.N5BH4_10-11ft_mesh 
sh.N5BH4_10-11ft_run 
sh.onestep 
N5BH4_10-11ft.mes1 
N5BH4_10-11ft.mes2 
N5BH4_10-11ft.mes3 
N5BH4_10-11ft.mes4 
N5BH4_10-11ft.mes5 
N5BH4_10-11ft.mes6 
N5BH4_10-11ft.mes7 
N5BH4_10-11ft.mes8 
N5BH4_10-11ft.mes9 
N5BH4_10-11ft.mes10 
N5BH4_10-11ft.mes11 
N5BH4_10-11ft.mes12 
N5BH4_10-11ft.mes13 
N5BH4_10-11ft.mes14 
N5BH4_10-11ft.mes15 
N5BH4_10-11ft.mes16 
N5BH4_10-11ft.mes17 
N5BH4_10-11ft.mes18 
N5BH4_10-11ft.mes19 
N5BH4_10-11ft.mes20 
N5BH4_10-11ft.mes21 
N5BH4_10-11ft.mes22 
N5BH4_10-11ft.mes23 
N5BH4_10-11ft.mes24 
N5BH4_10-11ft.mes25 
N5BH4_10-11ft.mes26 
MDL-NBS-HS-000004 REV02 
U0080 
April 2003 Attachment I2 Seepage Calibration Model and Seepage Testing Data 
N5BH4_10-11ft.mes27 
N5BH4_10-11ft.mes28 
N5BH4_10-11ft.mes29 
N5BH4_10-11ft.mes30 
ceiling_N5_1.dat 
measured_log-k_12_N5.dat 
Mesh with permeability realization #27 
Mesh with permeability realization #28 
Mesh with permeability realization #29 
Mesh with permeability realization #30 
Meshgeneration/N5BH5_21-22ft/ 
N5BH5_21-22ft 
sh.N5BH5_21-22ft_mes 
N5BH5_21-22ft.mes 
onestep 
sh.onestep 
ceiling_N5_2.dat 
leftbatwing_N5_2.dat 
rightbatwing_N5_2.dat 
Meshgeneration/N5BH5_28-29ft/ 
N5BH5_28-29ft 
N5BH5_28-29ft_sisim.par 
sh.N5BH5_28-29ft_mesh 
sh.N5BH5_28-29ft_run 
N5BH5_28-29ft.mes1 
N5BH5_28-29ft.mes2 
N5BH5_28-29ft.mes3 
N5BH5_28-29ft.mes4 
N5BH5_28-29ft.mes5 
N5BH5_28-29ft.mes6 
N5BH5_28-29ft.mes7 
N5BH5_28-29ft.mes8 
N5BH5_28-29ft.mes9 
N5BH5_28-29ft.mes10 
N5BH5_28-29ft.mes11 
N5BH5_28-29ft.mes12 
N5BH5_28-29ft.mes13 
N5BH5_28-29ft.mes14 
N5BH5_28-29ft.mes15 
N5BH5_28-29ft.mes16 
N5BH5_28-29ft.mes17 
MDL-NBS-HS-000004 REV02 
U0080 
File is in folder: Meshgeneration/Roughness/ 
File is in folder: Meshgeneration/Permeability/ 
TOUGH2 input file 
Sequence of instructions to execute multiple steps of mesh 
generations 
Mesh with permeability realization # 
File is in folder: Meshgeneration/N5BH4_10-11ft/ 
File is in folder: Meshgeneration/N5BH4_10-11ft/ 
File is in folder: Meshgeneration/Roughness/ 
File is in folder: Meshgeneration/Roughness/ 
File is in folder: Meshgeneration/Roughness/ 
TOUGH2 input file 
Parameter file for generation of random permeability field 
Sequence of instructions to execute multiple steps of mesh 
generations 
Sequence of instructions to run the above sequence of 
instructions multiple times by changing the permeability 
field seed number 
Mesh with permeability realization #1 
Mesh with permeability realization #2 
Mesh with permeability realization #3 
Mesh with permeability realization #4 
Mesh with permeability realization #5 
Mesh with permeability realization #6 
Mesh with permeability realization #7 
Mesh with permeability realization #8 
Mesh with permeability realization #9 
Mesh with permeability realization #10 
Mesh with permeability realization #11 
Mesh with permeability realization #12 
Mesh with permeability realization #13 
Mesh with permeability realization #14 
Mesh with permeability realization #15 
Mesh with permeability realization #16 
Mesh with permeability realization #17 
April 2003 Attachment I3 Seepage Calibration Model and Seepage Testing Data 
N5BH5_28-29ft.mes18 
N5BH5_28-29ft.mes19 
N5BH5_28-29ft.mes20 
N5BH5_28-29ft.mes21 
N5BH5_28-29ft.mes22 
N5BH5_28-29ft.mes23 
N5BH5_28-29ft.mes24 
N5BH5_28-29ft.mes25 
N5BH5_28-29ft.mes26 
N5BH5_28-29ft.mes27 
N5BH5_28-29ft.mes28 
N5BH5_28-29ft.mes29 
N5BH5_28-29ft.mes30 
measured_log-k_12_N5.dat 
ceiling_N5_3.dat 
leftbatwing_N5_3.dat 
rightbatwing_N5_3.dat 
Onestep 
sh.onestep 
Mesh with permeability realization #18 
Mesh with permeability realization #19 
Mesh with permeability realization #20 
Mesh with permeability realization #21 
Mesh with permeability realization #22 
Mesh with permeability realization #23 
Mesh with permeability realization #24 
Mesh with permeability realization #25 
Mesh with permeability realization #26 
Mesh with permeability realization #27 
Mesh with permeability realization #28 
Mesh with permeability realization #29 
Mesh with permeability realization #30 
LiquidReleaseTestData/ 
LB0207NICH5LIQ5-01-RH-T.xls 
LB0207NICH5LIQ5-01.xls 
LB0207NICH5LIQ5-02.xls 
LB0209NICH5LIQ7-15.xls 
LB0209NICH5LIQ7-16.xls 
LB0211NICH5LIQ9-17#1.xls 
LB0211NICH5LIQ9-17#2.xls 
N5BH4_10-11ft_rate.dat 
N5BH5_21-22ft_rate.dat 
N5BH5_28-29ft_05-06-02_rate.dat 
N5BH5_28-29ft_rate.dat 
CalibrationSummary.xls 
Calibration/ 
Calibration/N5B4_10-11ft/ 
sh.N5BH4_101-11ft_cal 
MDL-NBS-HS-000004 REV02 
File is in folder: Meshgeneration/Permeability/ 
File is in folder: Meshgeneration/Roughness/ 
File is in folder: Meshgeneration/Roughness/ 
File is in folder: Meshgeneration/Roughness/ 
File is in folder: Meshgeneration/N5BH4_10-11ft/ 
File is in folder: Meshgeneration/N5BH4_10-11ft/ 
Compilation of Relative humidity and temperature data from 
Compilation of Liquid release test data from 
Compilation of Liquid release test data from 
Compilation of Liquid release test data from 
Compilation of Liquid release test data from 
Compilation of Liquid release test data from 
Compilation of Liquid release test data from 
DTN: LB0207NICH5LIQ.001 [160408] 
DTN: LB0207NICH5LIQ.001 [160408] 
DTN: LB0207NICH5LIQ.001 [160408] 
DTN: LB0209NICH5LIQ.001 [160796] 
DTN: LB0209NICH5LIQ.001 [160796] 
DTN: LB0211NICH5LIQ.001 [160792] 
DTN: LB0211NICH5LIQ.001 [160792] 
Seepage rate for Borehole #4 (1011ft) 
Seepage rate for Borehole #5 (2122ft) 
Seepage rate for Borehole #5 (2829ft), for test started on 
5/6/02 
Seepage rate for Borehole #5 (2829ft), for test started on 
7/15/02 
Excel file with compilation of the calibration results 
Sequence of commands to start iTOUGH2 on a numbered 
Attachment I4 
U0080 
April 2003 Seepage Calibration Model and Seepage Testing Data 
sh.N5BH4_101-11ft_calm 
N5BH4_10-11ft_SS 
N5BH4_10-11ft_cal 
N5BH4_10-11ft_cali 
N5BH4_10-11ft_cal1i.out 
N5BH4_10-11ft_cal2i.out 
N5BH4_10-11ft_cal3i.out 
N5BH4_10-11ft_cal4i.out 
N5BH4_10-11ft_cal5i.out 
N5BH4_10-11ft_cal6i.out 
N5BH4_10-11ft_cal7i.out 
N5BH4_10-11ft_cal8i.out 
N5BH4_10-11ft_cal9i.out 
N5BH4_10-11ft_cal10i.out 
N5BH4_10-11ft_cal11i.out 
N5BH4_10-11ft_cal12i.out 
N5BH4_10-11ft_cal13i.out 
N5BH4_10-11ft_cal14i.out 
N5BH4_10-11ft_cal15i.out 
N5BH4_10-11ft_cal16i.out 
N5BH4_10-11ft_cal17i.out 
N5BH4_10-11ft_cal18i.out 
N5BH4_10-11ft_cal19i.out 
N5BH4_10-11ft_cal20i.out 
N5BH4_10-11ft_cal21i.out 
N5BH4_10-11ft_cal22i.out 
N5BH4_10-11ft_cal23i.out 
N5BH4_10-11ft_cal24i.out 
N5BH4_10-11ft_cal25i.out 
N5BH4_10-11ft_cal26i.out 
N5BH4_10-11ft_cal27i.out 
N5BH4_10-11ft_cal28i.out 
N5BH4_10-11ft_cal29i.out 
N5BH4_10-11ft_cal30i.out 
N5BH4_10-11ft_rate.dat 
Sequence of commands to start iTOUGH2 on the master node 
TOUGH2 input file for initial condition without evaporation 
TOUGH2 input file 
iTOUGH2 input file 
iTOUGH2 output file, permeability realization #1 
iTOUGH2 output file, permeability realization #2 
iTOUGH2 output file, permeability realization #3 
iTOUGH2 output file, permeability realization #4 
iTOUGH2 output file, permeability realization #5 
iTOUGH2 output file, permeability realization #6 
iTOUGH2 output file, permeability realization #7 
iTOUGH2 output file, permeability realization #8 
iTOUGH2 output file, permeability realization #9 
iTOUGH2 output file, permeability realization #10 
iTOUGH2 output file, permeability realization #11 
iTOUGH2 output file, permeability realization #12 
iTOUGH2 output file, permeability realization #13 
iTOUGH2 output file, permeability realization #14 
iTOUGH2 output file, permeability realization #15 
iTOUGH2 output file, permeability realization #16 
iTOUGH2 output file, permeability realization #17 
iTOUGH2 output file, permeability realization #18 
iTOUGH2 output file, permeability realization #19 
iTOUGH2 output file, permeability realization #20 
iTOUGH2 output file, permeability realization #21 
iTOUGH2 output file, permeability realization #22 
iTOUGH2 output file, permeability realization #23 
iTOUGH2 output file, permeability realization #24 
iTOUGH2 output file, permeability realization #25 
iTOUGH2 output file, permeability realization #26 
iTOUGH2 output file, permeability realization #27 
iTOUGH2 output file, permeability realization #28 
iTOUGH2 output file, permeability realization #29 
iTOUGH2 output file, permeability realization #30 
Calibration/N5B5_28-29ft/ 
sh.N5BH5_28-29ft_cal 
sh.N5BH5_28-29ft_calM 
N5BH5_28-29ft_ininonevap 
MDL-NBS-HS-000004 REV02 
U0080 
node (Node 1 to Node 10) 
File is in folder: LiquidReleaseTestData/ 
Sequence of commands start iTOUGH2 on a numbered node 
(Node 1 to Node 10) 
Sequence of commands to start iTOUGH2 on the master node 
TOUGH2 input file for initial condition without evaporation 
April 2003 Attachment I5 Seepage Calibration Model and Seepage Testing Data 
N5BH5_28-29ft_inievap 
N5BH5_28-29ft_cal 
N5BH5_28-29ft_cali 
N5BH5_28-29ft_cal1i.out 
N5BH5_28-29ft_cal3i.out 
N5BH5_28-29ft_cal4i.out 
N5BH5_28-29ft_cal6i.out 
N5BH5_28-29ft_cal7i.out 
N5BH5_28-29ft_cal8i.out 
N5BH5_28-29ft_cal9i.out 
N5BH5_28-29ft_cal11i.out 
N5BH5_28-29ft_cal12i.out 
N5BH5_28-29ft_cal13i.out 
N5BH5_28-29ft_cal14i.out 
N5BH5_28-29ft_cal15i.out 
N5BH5_28-29ft_cal16i.out 
N5BH5_28-29ft_cal18i.out 
N5BH5_28-29ft_cal19i.out 
N5BH5_28-29ft_cal20i.out 
N5BH5_28-29ft_cal21i.out 
N5BH5_28-29ft_cal23i.out 
N5BH5_28-29ft_cal24i.out 
N5BH5_28-29ft_cal25i.out 
N5BH5_28-29ft_cal26i.out 
N5BH5_28-29ft_cal27i.out 
N5BH5_28-29ft_cal28i.out 
N5BH5_28-29ft_cal29i.out 
N5BH5_28-29ft.mesX 
N5BH5_28-29ft_rate.dat 
TOUGH2 input file for initial condition with evaporation 
TOUGH2 input file 
iTOUGH2 input file 
iTOUGH2 output file, permeability realization #1 
iTOUGH2 output file, permeability realization #2 
iTOUGH2 output file, permeability realization #3 
iTOUGH2 output file, permeability realization #4 
iTOUGH2 output file, permeability realization #5 
iTOUGH2 output file, permeability realization #6 
iTOUGH2 output file, permeability realization #7 
iTOUGH2 output file, permeability realization #8 
iTOUGH2 output file, permeability realization #9 
iTOUGH2 output file, permeability realization #10 
iTOUGH2 output file, permeability realization #11 
iTOUGH2 output file, permeability realization #12 
iTOUGH2 output file, permeability realization #13 
iTOUGH2 output file, permeability realization #14 
iTOUGH2 output file, permeability realization #15 
iTOUGH2 output file, permeability realization #16 
iTOUGH2 output file, permeability realization #17 
iTOUGH2 output file, permeability realization #18 
iTOUGH2 output file, permeability realization #19 
iTOUGH2 output file, permeability realization #20 
iTOUGH2 output file, permeability realization #21 
iTOUGH2 output file, permeability realization #22 
iTOUGH2 output file, permeability realization #23 
iTOUGH2 output file, permeability realization #24 
Validation/ 
Validation/N5BH4_1011ft/ 
N5BH4_10-11ft_val 
N5BH4_10-11ft_vali 
N5BH4_10-11ft_vali.out 
N5BH4_10-11ft_vali.tec 
N5BH4_10-11ft_vali_mc.tec 
N5BH4_10-11ft_val.dat 
N5BH4_10-11ft_val.lpk 
N5BH4_10-11ft_val.wmf 
measured_log-k_12_N5.dat 
MDL-NBS-HS-000004 REV02 
U0080 
Files are in folder: Meshgeneration/N5BH4_10-11ft/ 
where X is mesh number 
File is in folder: LiquidReleaseTestData/ 
TOUGH2 input file 
iTOUGH2 input file 
iTOUGH2 output file 
iTOUGH2 output file for Tecplot 
iTOUGH2 output file for Tecplot (Monte Carlo) 
Tecplot input file 
Tecplot file (packaged data) 
Image file 
File is in folder: Meshgeneration/Permeability/ 
April 2003 Attachment I6 Validation/N5BH5_21-22ft/ 
N5BH5_21-22ft_val 
N5BH5_21-22ft_vali 
N5BH5_21-22ft_vali.out 
N5BH5_21-22ft_vali.tec 
N5BH5_21-22ft_vali_mc.tec 
N5BH5_21-22ft_val.dat 
N5BH5_21-22ft_val.lpk 
N5BH5_21-22ft_val.wmf 
measured_log-k_12_N5.dat 
N5BH5_21-22ft.mes 
N5BH5_21-22ft_rate.dat 
Validation/N5BH5_28-29ft_05-06-02/ 
N5BH5_28-29ft_05-06-02_val 
N5BH5_28-29ft_05-06-02_vali 
N5BH5_28-29ft_05-06-02_vali.out 
N5BH5_28-29ft_05-06-02_vali.tec 
N5BH5_28-29ft_05-06-02_vali_mc.tec 
N5BH5_28-29ft_05-06-02_val.dat 
N5BH5_28-29ft_05-06-02_val.lpk 
N5BH5_28-29ft_05-06-02_val.wmf 
measured_log-k_12_N5.dat 
N5BH5_28-29ft.mes1 
N5BH5_28-29ft_05-06-02_rate.dat 
Seepage Calibration Model and Seepage Testing Data 
N5BH4_10-11ft.mes1 
N5BH4_10-11ft_rate.dat 
File is in folder: Meshgeneration/N5BH4_10-11ft/ 
File is in folder: LiquidReleaseTestData/ 
TOUGH2 input file 
iTOUGH2 input file 
iTOUGH2 output file 
iTOUGH2 output file for Tecplot 
iTOUGH2 output file for Tecplot (Monte Carlo) 
Input file for Tecplot 
Tecplot file (packaged data) 
Image file 
File is in folder: Meshgeneration/Permeability/ 
File is in folder: Meshgeneration/N5BH5_21-22ft/ 
File is in folder: LiquidReleaseTestData/ 
TOUGH2 input file 
iTOUGH2 input file 
iTOUGH2 output file 
iTOUGH2 output file for Tecplot 
iTOUGH2 output file for Tecplot (Monte Carlo) 
Input file for Tecplot 
Tecplot file (packaged data) 
Image file 
File is in folder: Meshgeneration/Permeability/ 
File is in folder: Meshgeneration/N5BH5_28-29ft/ 
File is in folder: LiquidReleaseTestData/ 
TOUGH2 input file 
iTOUGH2 input file 
iTOUGH2 output file 
iTOUGH2 output file for Tecplot 
iTOUGH2 output file for Tecplot (Monte Carlo) 
Input file for Tecplot 
Tecplot file (packaged data) 
Image file 
File is in folder: Meshgeneration/Permeability/ 
File is in folder: Meshgeneration/N5BH5_28-29ft/ 
File is in folder: LiquidReleaseTestData/ 
Validation/N5BH5_28-29ft_07-15-02/ 
N5BH5_28-29ft_07-15-02_val 
N5BH5_28-29ft_07-15-02_vali 
N5BH5_28-29ft_07-15-02_vali.out 
N5BH5_28-29ft_07-15-02_vali.tec 
N5BH5_28-29ft_07-15-02_vali_mc.tec 
N5BH5_28-29ft_07-15-02_val.dat 
N5BH5_28-29ft_07-15-02_val.lpk 
N5BH5_28-29ft_07-15-02_val.wmf 
measured_log-k_12_N5.dat 
N5BH5_28-29ft.mes1 
N5BH5_28-29ft_rate.dat 
MDL-NBS-HS-000004 REV02 
U0080 
April 2003 Attachment I7 Seepage Calibration Model and Seepage Testing Data 
TOUGH2 input file 
iTOUGH2 input file, with evaporation connections 
iTOUGH2 output file, with evaporation connections 
Tecplot input file, with evaporation connections 
TOUGH input file 
iTOUGH2 input file, with seepage and deep flow connections 
iTOUGH2 output file, with seepage and deep flow connections 
iTOUGH2 output file for Tecplot, with seepage and deep flow 
connections 
MassBalance/ 
N5BH4_10-11ft_forwardevap 
N5BH4_10-11ft_forwardevapi 
N5BH4_10-11ft_forwardevapi.out 
N5BH4_10-11ft_forwardevapi.tec 
N5BH4_10-11ft_forwardseep 
N5BH4_10-11ft_forwardseepi 
N5BH4_10-11ft_forwardseepi.out 
N5BH4_10-11ft_forwardseepi.tec 
N5BH5_28-29ft.mes1 
FlowDiversion/ 
N5BH5_28-29ft_forwarddeep 
N5BH5_28-29ft_forwarddeepi 
N5BH5_28-29ft_forwarddeepi.out 
N5BH5_28-29ft_forwarddeepi.tec 
N5BH5_28-29ft_forwardseep 
N5BH5_28-29ft_forwardseepi 
N5BH5_28-29ft_forwardseepi.out 
N5BH5_28-29ft_forwardseepi.tec 
N5BH5_28-29ft.mes1 
Evaporation/ 
Evaporation_Calibration.xls 
MDL-NBS-HS-000004 REV02 
U0080 
File is in folder: Meshgeneration/N5BH4_10-11ft/ 
TOUGH2 input file 
iTOUGH2 input file, with seepage components connections 
iTOUGH2 output file, with seepage components connections 
iTOUGH2 output file for Tecplot, with seepage components 
connections 
TOUGH2 input file 
iTOUGH2 input file, with seepage connections 
iTOUGH2 output file, with seepage connections 
iTOUGH2 output file for Tecplot, with seepage connections 
File is in folder: Meshgeneration/N5BH5_28-29ft/ 
Estimation of boundary-layer thickness () for evaporation by 
vapor diffusion 
April 2003 Attachment I8 ST/ 
ST/Figures/ 
122.dat 
122Sat.dat 
211.dat 
221.dat 
222.dat 
222_0Sat.dat 
222_10Sat.dat 
222_20Sat.dat 
222_30Sat.dat 
231.dat 
232.dat 
311.dat 
321.dat 
Seepage Calibration Model and Seepage Testing Data 
Table I-2. File Name and Description for Modeling of Liquid-Release Tests in ECRB Cross Drift 
File/Folder Name 
For plot rate vs. time, LA#1, Zone 2, Set 2 
For saturation and flux distribution plot, LA#1, Zone 2, Set 2 
For plot rate vs. time, LA#2, Zone 1, Set 1 
For plot rate vs. time, LA#2, Zone 2, Set 1 
For plot rate vs. time, LA#2, Zone 2, Set 2 
For saturation distribution plot after 0 days, LA#2, Zone 2, Set 2 
For saturation distribution plot after 10 days, LA#2, Zone 2, Set 
2 
For saturation distribution plot after 20 days, LA#2, Zone 2, Set 
2 
For saturation distribution plot after 30 days, LA#2, Zone 2, Set 
2 
For plot rate vs. time, LA#2, Zone 3, Set 1 
For plot rate vs. time, LA#2, Zone 3, Set 2 
For plot rate vs. time, LA#3, Zone 1, Set 1 
For plot rate vs. time, LA#3, Zone 2, Set 1 
(files used for simulation of liquid-release tests in borehole SYBT-ECRB-LA#1) 
Mesh with permeability realization #1 
Mesh with permeability realization #2 
Mesh with permeability realization #3 
Mesh with permeability realization #4 
Mesh with permeability realization #6 
Mesh with permeability realization #10 
Mesh with permeability realization #11 
Mesh with permeability realization #12 
Mesh with permeability realization #13 
Mesh with permeability realization #14 
Mesh with permeability realization #16 
Mesh with permeability realization #17 
Mesh with permeability realization #21 
Mesh with permeability realization #23 
Mesh with permeability realization #24 
Mesh with permeability realization #25 
Mesh with permeability realization #26 
ST/LA1/ 
ST/LA1/Zone2 
LA1_zone2.mes1 
LA1_zone2.mes2 
LA1_zone2.mes3 
LA1_zone2.mes4 
LA1_zone2.mes6 
LA1_zone2.mes10 
LA1_zone2.mes11 
LA1_zone2.mes12 
LA1_zone2.mes13 
LA1_zone2.mes14 
LA1_zone2.mes16 
LA1_zone2.mes17 
LA1_zone2.mes21 
LA1_zone2.mes23 
LA1_zone2.mes24 
LA1_zone2.mes25 
LA1_zone2.mes26 
ST/LA1/Zone2/Set2 
MDL-NBS-HS-000004 REV02 
Description/File Location 
(files used for visualization purposes only) 
Attachment I9 
U0080 
April 2003 ST/LA2/ 
ST/LA2/Zone1 
Seepage Calibration Model and Seepage Testing Data 
Cum.xls Excel file with processed seepage data from 
DTN: LB0110ECRBLIQR.002 [156879] 
TOUGH2 input file to create initial conditions with dry-out zone 
TOUGH2 input file to create initial conditions without ventilation 
Relative humidity boundary condition file 
Seepage-rate data file for calibration 
TOUGH2 input for simulating liquid-release test 
iTOUGH2 input for calibrating against seepage-rate data 
iTOUGH2 output file with permeability realization #1 
iTOUGH2 output file with permeability realization #2 
iTOUGH2 output file with permeability realization #3 
iTOUGH2 output file with permeability realization #4 
iTOUGH2 output file with permeability realization #6 
iTOUGH2 output file with permeability realization #10 
iTOUGH2 output file with permeability realization #11 
iTOUGH2 output file with permeability realization #12 
iTOUGH2 output file with permeability realization #13 
iTOUGH2 output file with permeability realization #14 
iTOUGH2 output file with permeability realization #16 
iTOUGH2 output file with permeability realization #17 
iTOUGH2 output file with permeability realization #21 
iTOUGH2 output file with permeability realization #23 
iTOUGH2 output file with permeability realization #24 
iTOUGH2 output file with permeability realization #25 
iTOUGH2 output file with permeability realization #26 
Excel file with processed relative-humidity data from 
DTN: LB0110ECRBLIQR.002 [156879] 
Dummy iTOUGH2 input file for generating initial conditions with 
(files used for simulation of liquid-release tests in borehole SYBT-ECRB-LA#2) 
Excel file with processed seepage data from 
DTN: LB00090012213U.002 [153154] 
Seepage-rate data file for validation 
TOUGH2 input file for simulating liquid-release test 
iTOUGH2 input file for performing Monte Carlo simulations 
iTOUGH2 output file 
Mesh file used for validation runs 
Mesh with permeability realization #1 
ST/LA2/Zone2 
MDL-NBS-HS-000004 REV02 
U0080 
LA1_zone2_inievap 
LA1_zone2_ininoevap 
LA1_zone2_set2.bc 
LA1_zone2_set2.dat 
LA1_zone2_set2 
LA1_zone2_set2i 
LA1_zone2_set2i.out1 
LA1_zone2_set2i.out2 
LA1_zone2_set2i.out3 
LA1_zone2_set2i.out4 
LA1_zone2_set2i.out6 
LA1_zone2_set2i.out10 
LA1_zone2_set2i.out11 
LA1_zone2_set2i.out12 
LA1_zone2_set2i.out13 
LA1_zone2_set2i.out14 
LA1_zone2_set2i.out16 
LA1_zone2_set2i.out17 
LA1_zone2_set2i.out21 
LA1_zone2_set2i.out23 
LA1_zone2_set2i.out24 
LA1_zone2_set2i.out25 
LA1_zone2_set2i.out26 
RH.xls 
inievapi evaporation 
ST/LA2/Zone1/Set1 
Cum.xls 
LA2_zone1_set1.dat 
LA2_zone1_set1_val 
LA2_zone1_set1_vali 
LA2_zone1_set1_vali.out 
LA2_zone1_val.mes 
LA2_zone2.mes1 
April 2003 Attachment I10 ST/LA2/Zone2/Set1 
LA2_zone2_set1.bc 
LA2_zone2_set1.dat 
LA2_zone2_set1_val 
LA2_zone2_set1_vali 
LA2_zone2_set1_vali.out 
LA2_zone2_val.mes 
LA2_zone2_set2i 
LA2_zone2_set2i.out1 
Seepage Calibration Model and Seepage Testing Data 
LA2_zone2.mes2 
LA2_zone2.mes3 
LA2_zone2.mes4 
LA2_zone2.mes5 
LA2_zone2.mes6 
LA2_zone2.mes8 
LA2_zone2.mes9 
LA2_zone2.mes10 
LA2_zone2.mes11 
LA2_zone2.mes12 
LA2_zone2.mes13 
LA2_zone2.mes14 
LA2_zone2.mes16 
LA2_zone2.mes17 
LA2_zone2.mes18 
LA2_zone2.mes21 
LA2_zone2.mes22 
LA2_zone2.mes24 
LA2_zone2.mes25 
LA2_zone2.mes26 
LA2_zone2.mes98 
LA2_zone2.mes99 
LA2_zone2.mes200 
Mesh with permeability realization #2 
Mesh with permeability realization #3 
Mesh with permeability realization #4 
Mesh with permeability realization #5 
Mesh with permeability realization #6 
Mesh with permeability realization #8 
Mesh with permeability realization #9 
Mesh with permeability realization #10 
Mesh with permeability realization #11 
Mesh with permeability realization #12 
Mesh with permeability realization #13 
Mesh with permeability realization #14 
Mesh with permeability realization #16 
Mesh with permeability realization #17 
Mesh with permeability realization #18 
Mesh with permeability realization #21 
Mesh with permeability realization #22 
Mesh with permeability realization #24 
Mesh with permeability realization #25 
Mesh with permeability realization #26 
Mesh, boundary-layer thickness 0.5 cm 
Mesh, boundary-layer thickness 2.0 cm 
Mesh, extended mesh 
(seepage data from DTN: LB00090012213U.002 [153154]) 
Relative humidity boundary condition file 
Seepage-rate data file 
TOUGH2 input file for simulating liquid-release test 
iTOUGH2 input file for performing Monte Carlo simulations 
iTOUGH2 output file 
Mesh file used for validation runs 
TOUGH2 input file to create initial conditions with dry-out zone 
TOUGH2 input file to create initial conditions without ventilation 
Relative humidity boundary condition file 
Seepage-rate data file for calibration 
TOUGH2 input for simulating liquid-release test 
Processed seepage and relative humidity data from 
DTN: LB0110SYST0015.001 [160409] 
iTOUGH2 input for calibrating against seepage-rate data 
iTOUGH2 output file with permeability realization #1 
ST/LA2/Zone2/Set2 
LA2_zone2_inievap 
LA2_zone2_ininoevap 
LA2_zone2_set2.bc 
LA2_zone2_set2.dat 
LA2_zone2_set2 
LA2_zone2_set2_rates_RH.prn 
MDL-NBS-HS-000004 REV02 
(seepage data from DTN: LB0110SYST0015.001 [160409]) 
Attachment I11 
U0080 
April 2003 ST/LA2/Zone2/Set2half 
LA2_zone2_inievap 
LA2_zone2_ininoevap 
LA2_zone2_set2.dat 
LA2_zone2_set2half.bc 
LA2_zone2_set2half 
LA2_zone2_set2halfi 
LA2_zone2_set2halfi.out17 
Seepage Calibration Model and Seepage Testing Data 
LA2_zone2_set2i.out2 
LA2_zone2_set2i.out3 
LA2_zone2_set2i.out4 
LA2_zone2_set2i.out5 
LA2_zone2_set2i.out6 
LA2_zone2_set2i.out8 
LA2_zone2_set2i.out9 
LA2_zone2_set2i.out10 
LA2_zone2_set2i.out11 
LA2_zone2_set2i.out12 
LA2_zone2_set2i.out13 
LA2_zone2_set2i.out14 
LA2_zone2_set2i.out16 
LA2_zone2_set2i.out17 
LA2_zone2_set2i.out18 
LA2_zone2_set2i.out21 
LA2_zone2_set2i.out22 
LA2_zone2_set2i.out24 
LA2_zone2_set2i.out25 
LA2_zone2_set2i.out26 
LA2_zone2_set2i.out98 
LA2_zone2_set2i.out99 
iTOUGH2 output file with permeability realization #2 
iTOUGH2 output file with permeability realization #3 
iTOUGH2 output file with permeability realization #4 
iTOUGH2 output file with permeability realization #5 
iTOUGH2 output file with permeability realization #6 
iTOUGH2 output file with permeability realization #8 
iTOUGH2 output file with permeability realization #9 
iTOUGH2 output file with permeability realization #10 
iTOUGH2 output file with permeability realization #11 
iTOUGH2 output file with permeability realization #12 
iTOUGH2 output file with permeability realization #13 
iTOUGH2 output file with permeability realization #14 
iTOUGH2 output file with permeability realization #16 
iTOUGH2 output file with permeability realization #17 
iTOUGH2 output file with permeability realization #18 
iTOUGH2 output file with permeability realization #21 
iTOUGH2 output file with permeability realization #22 
iTOUGH2 output file with permeability realization #24 
iTOUGH2 output file with permeability realization #25 
iTOUGH2 output file with permeability realization #26 
iTOUGH2 output file, boundary-layer thickness 0.5 cm 
iTOUGH2 output file, boundary-layer thickness 2.0 cm 
(sensitivity to reduction in seepage rate) 
TOUGH2 input file to create initial conditions with dry-out zone 
TOUGH2 input file to create initial conditions without ventilation 
Seepage-rate data file for calibration 
Relative humidity boundary condition file 
TOUGH2 input for simulating liquid-release test 
iTOUGH2 input for calibrating against seepage-rate data 
iTOUGH2 output for calibrating against seepage-rate data 
(sensitivity to extent of model domain) 
TOUGH2 input file to create initial conditions with dry-out zone 
TOUGH2 input file to create initial conditions without ventilation 
Seepage-rate data file for calibration 
Relative humidity boundary condition file 
TOUGH2 input for simulating liquid-release test 
iTOUGH2 input for calibrating against seepage-rate data 
iTOUGH2 output for calibrating against seepage-rate data 
ST/LA2/Zone2/Set2large 
LA2_zone2_inievap 
LA2_zone2_ininoevap 
LA2_zone2_set2.dat 
LA2_zone2_set2large.bc 
LA2_zone2_set2large_forward 
LA2_zone2_set2large_forwardi 
LA2_zone2_set2large_forwardi.out 
MDL-NBS-HS-000004 REV02 
U0080 
April 2003 Attachment I12 ST/LA2/Zone2/Set2lessevap 
LA2_zone2_set2.dat 
LA2_zone2_set2lessevap.bc 
LA2_zone2_set2lessevap 
LA2_zone2_set2lessevapi 
LA2_zone2_set2lessevapi.out 
ST/LA2/Zone2/Set2noevap 
LA2_zone2_inievap 
LA2_zone2_ininoevap 
LA2_zone2_set2.dat 
LA2_zone2_set2noevap.bc 
LA2_zone2_set2noevap 
LA2_zone2_set2noevapi 
LA2_zone2_set2noevapi.out 
ST/LA2/Zone2/Set2sens 
LA2_zone2_inievap 
LA2_zone2_ininoevap 
LA2_zone2_set2.dat 
LA2_zone2_set2sens.bc 
LA2_zone2_set2sens_forward 
LA2_zone2_set2sens_forwardi 
LA2_zone2_set2sens_forwardi.out 
Seepage Calibration Model and Seepage Testing Data 
(sensitivity to evaporative surface area) 
TOUGH2 input file to create initial conditions with dry-out zone 
TOUGH2 input file to create initial conditions without ventilation 
Seepage-rate data file for calibration 
Relative humidity boundary condition file 
TOUGH2 input for simulating liquid-release test 
iTOUGH2 input for calibrating against seepage-rate data 
iTOUGH2 output for calibrating against seepage-rate data 
Dummy TOUGH2 input file to create initial conditions 
TOUGH2 input file to create initial conditions without ventilation 
Seepage-rate data file for calibration 
Relative humidity boundary condition file 
TOUGH2 input for simulating liquid-release test 
iTOUGH2 input for calibrating against seepage-rate data 
iTOUGH2 output for calibrating against seepage-rate data 
(sensitivity to input parameters) 
TOUGH2 input file to create initial conditions with dry-out zone 
TOUGH2 input file to create initial conditions without ventilation 
Seepage-rate data file for calibration 
Relative humidity boundary condition file 
TOUGH2 input for simulating liquid-release test 
iTOUGH2 input for performing sensitivity analysis 
iTOUGH2 output for sensitivity analysis 
Mesh with permeability realization #1 
Mesh with permeability realization #2 
Mesh with permeability realization #3 
Mesh with permeability realization #4 
Mesh with permeability realization #5 
Mesh with permeability realization #6 
Mesh with permeability realization #9 
Mesh with permeability realization #10 
Mesh with permeability realization #11 
Mesh with permeability realization #12 
Mesh with permeability realization #13 
Mesh with permeability realization #14 
Mesh with permeability realization #15 
ST/LA2/Zone3 
LA2_zone3.mes1 
LA2_zone3.mes2 
LA2_zone3.mes3 
LA2_zone3.mes4 
LA2_zone3.mes5 
LA2_zone3.mes6 
LA2_zone3.mes9 
LA2_zone3.mes10 
LA2_zone3.mes11 
LA2_zone3.mes12 
LA2_zone3.mes13 
LA2_zone3.mes14 
LA2_zone3.mes15 
MDL-NBS-HS-000004 REV02 
LA2_zone2_inievap 
LA2_zone2_ininoevap 
(sensitivity to evaporation) 
Attachment I13 
U0080 
April 2003 ST/LA2/Zone3/Set1 
LA2_zone3_set1.dat 
LA2_zone3_set1_val 
LA2_zone3_set1_vali 
LA2_zone3_set1_vali.out 
LA2_zone3_val.mes 
Seepage Calibration Model and Seepage Testing Data 
LA2_zone3.mes16 
LA2_zone3.mes18 
LA2_zone3.mes19 
LA2_zone3.mes20 
LA2_zone3.mes21 
LA2_zone3.mes22 
Mesh with permeability realization #16 
Mesh with permeability realization #18 
Mesh with permeability realization #19 
Mesh with permeability realization #20 
Mesh with permeability realization #21 
Mesh with permeability realization #22 
Seepage-rate data file 
TOUGH2 input file for simulating liquid-release test 
iTOUGH2 input file for performing Monte Carlo simulations 
iTOUGH2 output file 
Mesh file used for validation runs 
(seepage data from DTN: LB0110SYST0015.001 [160409]) 
TOUGH2 input file to create initial conditions with dry-out zone 
TOUGH2 input file to create initial conditions without ventilation 
Relative humidity boundary condition file 
Seepage-rate data file for calibration 
TOUGH2 input for simulating liquid-release test 
iTOUGH2 input for calibrating against seepage-rate data 
iTOUGH2 output file with permeability realization #1 
iTOUGH2 output file with permeability realization #2 
iTOUGH2 output file with permeability realization #3 
iTOUGH2 output file with permeability realization #4 
iTOUGH2 output file with permeability realization #5 
iTOUGH2 output file with permeability realization #6 
iTOUGH2 output file with permeability realization #9 
iTOUGH2 output file with permeability realization #10 
iTOUGH2 output file with permeability realization #11 
iTOUGH2 output file with permeability realization #12 
iTOUGH2 output file with permeability realization #13 
iTOUGH2 output file with permeability realization #14 
iTOUGH2 output file with permeability realization #15 
iTOUGH2 output file with permeability realization #16 
iTOUGH2 output file with permeability realization #18 
iTOUGH2 output file with permeability realization #19 
iTOUGH2 output file with permeability realization #20 
iTOUGH2 output file with permeability realization #21 
iTOUGH2 output file with permeability realization #22 
ST/LA2/Zone3/Set2 
LA2_zone3_inievap 
LA2_zone3_ininoevap 
LA2_zone3_set2.bc 
LA2_zone3_set2.dat 
LA2_zone3_set2 
LA2_zone3_set2i 
LA2_zone3_set2i.out1 
LA2_zone3_set2i.out2 
LA2_zone3_set2i.out3 
LA2_zone3_set2i.out4 
LA2_zone3_set2i.out5 
LA2_zone3_set2i.out6 
LA2_zone3_set2i.out9 
LA2_zone3_set2i.out10 
LA2_zone3_set2i.out11 
LA2_zone3_set2i.out12 
LA2_zone3_set2i.out13 
LA2_zone3_set2i.out14 
LA2_zone3_set2i.out15 
LA2_zone3_set2i.out16 
LA2_zone3_set2i.out18 
LA2_zone3_set2i.out19 
LA2_zone3_set2i.out20 
LA2_zone3_set2i.out21 
LA2_zone3_set2i.out22 
MDL-NBS-HS-000004 REV02 
U0080 
(seepage data from DTN: LB00090012213U.002 [153154]) 
April 2003 Attachment I14 Seepage Calibration Model and Seepage Testing Data 
(files used for simulation of liquid-release tests in borehole SYBT-ECRB-LA#3) 
Mesh with permeability realization #1 
Mesh with permeability realization #2 
Mesh with permeability realization #3 
Mesh with permeability realization #4 
Mesh with permeability realization #5 
Mesh with permeability realization #6 
Mesh with permeability realization #7 
Mesh with permeability realization #8 
Mesh with permeability realization #9 
Mesh with permeability realization #10 
Mesh with permeability realization #11 
Mesh with permeability realization #12 
Mesh with permeability realization #13 
Mesh with permeability realization #14 
Mesh with permeability realization #15 
Mesh with permeability realization #16 
Mesh with permeability realization #17 
Mesh with permeability realization #18 
Mesh with permeability realization #19 
Mesh with permeability realization #20 
Mesh with permeability realization #21 
Mesh with permeability realization #22 
Mesh with permeability realization #23 
Mesh with permeability realization #24 
Mesh with permeability realization #25 
Excel file with processed seepage data from 
DTN: LB0203ECRBLIQR.001 [158462] 
TOUGH2 input file to create initial conditions with dry-out zone 
TOUGH2 input file to create initial conditions without ventilation 
Relative humidity boundary condition file 
Seepage-rate data file for calibration 
TOUGH2 input for simulating liquid-release test 
iTOUGH2 input for calibrating against seepage-rate data 
iTOUGH2 output file with permeability realization #1 
iTOUGH2 output file with permeability realization #2 
iTOUGH2 output file with permeability realization #3 
iTOUGH2 output file with permeability realization #4 
iTOUGH2 output file with permeability realization #5 
ST/LA3/ 
ST/LA3/Zone1 
LA3_zone1.mes1 
LA3_zone1.mes2 
LA3_zone1.mes3 
LA3_zone1.mes4 
LA3_zone1.mes5 
LA3_zone1.mes6 
LA3_zone1.mes7 
LA3_zone1.mes8 
LA3_zone1.mes9 
LA3_zone1.mes10 
LA3_zone1.mes11 
LA3_zone1.mes12 
LA3_zone1.mes13 
LA3_zone1.mes14 
LA3_zone1.mes15 
LA3_zone1.mes16 
LA3_zone1.mes17 
LA3_zone1.mes18 
LA3_zone1.mes19 
LA3_zone1.mes20 
LA3_zone1.mes21 
LA3_zone1.mes22 
LA3_zone1.mes23 
LA3_zone1.mes24 
LA3_zone1.mes25 
ST/LA3/Zone1/Set1 
Cum.xls 
LA3_zone1_inievap 
LA3_zone1_ininoevap 
LA3_zone1_set1.bc 
LA3_zone1_set1.dat 
LA3_zone1_set1 
LA3_zone1_set1i 
LA3_zone1_set1i.out1 
LA3_zone1_set1i.out2 
LA3_zone1_set1i.out3 
LA3_zone1_set1i.out4 
LA3_zone1_set1i.out5 
MDL-NBS-HS-000004 REV02 Attachment I15 
U0080 
April 2003 Seepage Calibration Model and Seepage Testing Data 
ST/LA3/Zone2 
ST/Meshgeneration/ 
mesh3dblock 
mesh3dlargeblock 
onestep 
perm.par 
primary.mes 
primarylarge.mes 
sh.LA1_zone2_mesh 
sh.LA2_zone1_mesh 
sh.LA2_zone2_largemesh 
sh.LA2_zone2_mesh 
MDL-NBS-HS-000004 REV02 
LA3_zone1_set1i.out6 
LA3_zone1_set1i.out7 
LA3_zone1_set1i.out8 
LA3_zone1_set1i.out9 
LA3_zone1_set1i.out10 
LA3_zone1_set1i.out11 
LA3_zone1_set1i.out12 
LA3_zone1_set1i.out13 
LA3_zone1_set1i.out14 
LA3_zone1_set1i.out15 
LA3_zone1_set1i.out16 
LA3_zone1_set1i.out17 
LA3_zone1_set1i.out18 
LA3_zone1_set1i.out20 
LA3_zone1_set1i.out22 
LA3_zone1_set1i.out23 
LA3_zone1_set1i.out24 
LA3_zone1_set1i.out25 
ST/LA3/Zone2/Set1 
Cum.xls 
LA3_zone2_set1.dat 
LA3_zone2_set1_val 
LA3_zone2_set1_vali 
LA3_zone2_set1_vali.out 
LA3_zone2_val.mes 
U0080 
iTOUGH2 output file with permeability realization #6 
iTOUGH2 output file with permeability realization #7 
iTOUGH2 output file with permeability realization #8 
iTOUGH2 output file with permeability realization #9 
iTOUGH2 output file with permeability realization #10 
iTOUGH2 output file with permeability realization #11 
iTOUGH2 output file with permeability realization #12 
iTOUGH2 output file with permeability realization #13 
iTOUGH2 output file with permeability realization #14 
iTOUGH2 output file with permeability realization #15 
iTOUGH2 output file with permeability realization #16 
iTOUGH2 output file with permeability realization #17 
iTOUGH2 output file with permeability realization #19 
iTOUGH2 output file with permeability realization #20 
iTOUGH2 output file with permeability realization #22 
iTOUGH2 output file with permeability realization #23 
iTOUGH2 output file with permeability realization #24 
iTOUGH2 output file with permeability realization #25 
Excel file with processed seepage data from 
DTN: LB0203ECRBLIQR.001 [158462] 
Seepage-rate data file 
TOUGH2 input file for simulating liquid-release test 
iTOUGH2 input file for performing Monte Carlo simulations 
iTOUGH2 output file 
Mesh file used for validation runs 
(files used for mesh generation) 
TOUGH2 input file with MESHMAKER block 
TOUGH2 input file with MESHMAKER block, extended model 
TOUGH2 input file to perform single time step 
SISIM input file for generating heterogeneous log-permeability 
modifier field 
Primary mesh file 
Primary mesh file, extended model domain 
Sequence of commands used to generate meshes for tests in 
Sequence of commands used to generate meshes for tests in 
Sequence of commands used to generate extended mesh for 
zone 2 of borehole SYBT-ECRB-LA#1 
zone 1 of borehole SYBT-ECRB-LA#2 
tests in zone 2 of borehole SYBT-ECRB-LA#2 
Sequence of commands used to generate meshes for tests in 
April 2003 Attachment I16 Seepage Calibration Model and Seepage Testing Data 
sh.LA2_zone3_mesh 
sh.LA3_zone1_mesh 
sh.LA3_zone2_mesh 
sh.onestep 
results.xls 
sh.run 
sh.run_forward 
sh.run_val 
zone 2 of borehole SYBT-ECRB-LA#2 
Sequence of commands used to generate meshes for tests in 
Sequence of commands used to generate meshes for tests in 
Sequence of commands used to generate meshes for tests in 
Sequence of commands used to run iTOUGH2 simulation with 
Excel file with compilation of inverse modeling results 
Sequence of commands used to perform multiple inversions 
with multiple realizations of underlying permeability field 
Sequence of commands used to perform a single forward run 
Sequence of commands used to perform validation runs 
MDL-NBS-HS-000004 REV02 
U0080 
zone 3 of borehole SYBT-ECRB-LA#2 
zone 1 of borehole SYBT-ECRB-LA#3 
zone 2 of borehole SYBT-ECRB-LA#3 
a single time step 
April 2003 Attachment I17 Seepage Calibration Model and Seepage Testing Data 
INTENTIONALLY LEFT BLANK 
Attachment I18 MDL-NBS-HS-000004 REV02 
U0080 
April 2003 Seepage Calibration Model and Seepage Testing Data 
ATTACHMENT II 
m 
S =i
=1 
n + c = 
h
a 
..
5 . 1 
. 
= n + c 
Here, h is the lag distance (stored in Column C), n is the nugget effect (stored in Cell J2), a is 
the correlation length (stored in Cell J3), and c is the sill value (stored in Cell J4). The 
coefficient w in Equation (II-1) is taken to be the inverse of the number of data pairs 
supporting the empirical variogram value (stored in Column E; the inverse is stored in a 
newly inserted Column F). 
3. Column J contains Equation (II-2), Column K holds the squared weighted differences (see 
Equation (II-1)), and Cell K6 holds the objective function S. 
4. The objective function of Cell K6 is minimized by updating the three parameters stored in 
Cells J2, J3, and J4 using the EXCEL Solver Add-in (to be loaded by clicking on gTools | 
VARIOGRAM FITTING 
Section 6.6.2.1 discusses the fitting of a spherical variogram model to the empirical variogram 
data obtained from the geostatistical analysis of air-permeability data. The purpose of the fitting 
is to determine the nugget effect, sill value, and correlation length of the log-permeability field. 
Weighted least-squares fitting was performed using standard functions of the exempt software 
EXCEL (97 SR-2). The following narrative explains the fitting process for clarification, using 
worksheet N3107_airk_SD of file Vario.xls as an example. 
1. The result of the variogram calculation using GAMV3 V1.201 (LBNL 2000 [153099]) (see 
file N3107_airk.var, submitted with this Model Report under Output-DTN: 
LB0302SCMREV02.001) was loaded into the worksheet. Each data line in file 
N3107_airk.var is labeled. Lines 3 through 31 contain the empirical variogram information; 
Lines 1, 2, and 32 through 52 contain unrelated information and are removed. The relevant 
information is now contained in Rows 7 through 35 of the worksheet N3107_airk_SD of 
spreadsheet Vario.xls (in the remainder of this attachment, all references to a column are 
restricted to Rows 7 through 35). 
2. Performing a weighted least-square fit consists of minimizing the following objective 
function S: 
2 ) * (  i i , (II-1) 
. 
i 
if h < a 
w2 
where i is the value calculated with the spherical variogram model at lag distance h , i *i 
is the corresponding empirical variogram value, and i w is a coefficient for weighting the 
data. The spherical variogram with a nugget effect is given by (after Deutsch and Journel 
1992 [100567], p. 23, Eq. II-2): 
h . 
a . 
. . 0.5. . 
. if h . a 
3 .. 
.. 
Attachment II.1 
( ; , ,c a n h ) 
MDL-NBS-HS-000004 REV02 
U0080 
(II-2) 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
Add-ins | Solver Add-in). Click on Tools | Solver, set Set Target Cell to $K$6, 
Equal to to Min, By Changing Cells to $J$2:$J$4, and Subject to the Constraints to 
$J$2>=0, $J$3>=0, and $J$4>=0. Looking at the empirical variogram, provide reasonable 
initial guesses for the three parameters (e.g., n=0.1, a=1.0, c=0.5) and click on Solve to get 
the best-fit parameters, which are displayed in Cells J2 through J4. 
The appropriateness of the fitting procedure was checked as follows: 
1. The spreadsheet was developed by Rick Ahlers. Stefan Finsterle has verified that Equations 
(II-1) and (II-2) were correctly coded into the appropriate cells. 
2. The calculated variogram value (shown in Column H) was spot-checked. 
3. Figure 12 shows that the variogram model fits the data in a least-square sense. 
The EXCEL spreadsheet Vario.xls has been submitted as part of the previous revision (CRWMS 
M&O 2001 [153045]) under DTN: LB0010SCMREV01.001 [154292]; therefore, the input, 
equations used (click on the appropriate cells), and output is available, traceable, and reproducible 
by an appropriately qualified individual. The spreadsheet is reproduced in Table II-1. 
April 2003 Attachment II2 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
Table II-1. EXCEL Spreadsheet Vario.xls for Fitting Spherical Variogram to Empirical Log- 
Permeability Variogram 
A B C D E F 
2 
3 
4 
5 
6 
Lag [m] Gamma # of pairs 1/(# of pairs) log(k_head) Log(k_tail) 
0.00725 
0.00758 
0.00355 
0.0022 
0.00301 
0.00313 
0.00177 
0.00259 
0.00314 
0.00314 
0.00336 
0.00376 
0.0041 
0.00467 
0.00463 
0.00562 
0.00595 
0.00735 
0.00806 
0.00862 
0.01064 
0.01351 
0.01724 
0.02273 
0.03125 
0.05 
0.07143 
0.125 
0.5 
7 3 0.305 0.34193 
8 4 0.609 0.51454 
9 5 0.928 0.48461 
10 6 1.226 0.43619 
11 7 1.512 0.48658 
12 8 1.817 0.4684 
13 9 2.145 0.48656 
14 10 2.45 0.50127 
15 11 2.733 0.55705 
16 12 3.033 0.47056 
17 13 3.342 0.46302 
18 14 3.653 0.49027 
19 15 3.963 0.5031 
20 16 4.265 0.54863 
21 17 4.576 0.53108 
22 18 4.89 0.62485 
23 19 5.198 0.59026 
24 20 5.507 0.55459 
25 21 5.806 0.6776 
26 22 6.114 0.56408 
27 23 6.433 0.39963 
28 24 6.745 0.49685 
29 25 7.041 0.42472 
30 26 7.34 0.55424 
31 27 7.638 0.66126 
32 28 7.938 0.48026 
33 29 8.233 0.86247 
34 30 8.522 0.75716 
35 31 8.753 0.00045 
138 
132 
282 
454 
332 
320 
564 
386 
318 
318 
298 
266 
244 
214 
216 
178 
168 
136 
124 
116 
94 
74 
58 
44 
32 
20 
14
8
2 
Attachment II3 MDL-NBS-HS-000004 REV02 
H I J 
nugget 
G 
0.005957 
correlation length 0.608829 
sill 
Spherical 
-12.21159 0.34193 
-12.23576 0.493878 
-12.24096 0.493878 
-12.19152 0.493878 
-12.20027 0.493878 
-12.201 0.493878 
-12.23769 0.493878 
-12.23959 0.493878 
-12.2467 0.493878 
-12.22242 0.493878 
-12.23587 0.493878 
-12.20598 0.493878 
-12.22635 0.493878 
-12.24701 0.493878 
-12.22051 0.493878 
-12.18056 0.493878 
-12.14107 0.493878 
-12.15426 0.493878 
-12.16726 0.493878 
-12.20509 0.493878 
-12.21426 0.493878 
-12.30514 0.493878 
-12.29034 0.493878 
-12.30341 0.493878 
-12.33875 0.493878 
-12.1745 0.493878 
-12.03286 0.493878 
-12.06625 0.493878 
-11.625 0.493878 
-12.21159 
-12.23576 
-12.24096 
-12.19152 
-12.20027 
-12.201 
-12.23769 
-12.23959 
-12.2467 
-12.22242 
-12.23587 
-12.20598 
-12.22635 
-12.24701 
-12.22051 
-12.18056 
-12.14107 
-12.15426 
-12.16726 
-12.20509 
-12.21426 
-12.30514 
-12.29034 
-12.30341 
-12.33875 
-12.1745 
-12.03286 
-12.06625 
-11.625 
U0080 
K 
0.487922 K
6=objective func. 
3173.542618 
6.78058E-12 
7.430211773 
6.815955381 
687.5866471 
5.878806928 
66.25919213 
17.09435459 
8.145356588 
404.751331 
55.14775388 
84.34520866 
0.920845218 
5.059074452 
137.4561849 
64.56062946 
543.1046002 
262.3957768 
68.22957436 
519.5790967 
66.32586675 
78.46250161 
0.048389527 
16.09206783 
7.052232487 
28.68909386 
0.074181294 
26.62748957 
4.43631024 
0.973885245 
K7-K35 =weighted residuals 
April 2003 Seepage Calibration Model and Seepage Testing Data 
INTENTIONALLY LEFT BLANK 
Attachment II4 MDL-NBS-HS-000004 REV02 
U0080 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
ATTACHMENT III 
MESH GENERATION FOR SIMULATION OF SEEPAGE TESTS IN ECRB 
Multiple numerical meshes of a 12 ft (3.6576 m) long section of the ECRB Cross Drift are 
developed, each with a different statistical realization of the underlying heterogeneous permeability 
field. The following steps are performed: 
1. A mesh is generated with X-Y-Z dimensions of 4.0 m  3.6576 m  11.0 m, respectively, 
discretized into regular gridblocks with side lengths of 0.1 m  0.3 m  0.1 m. The Y-axis is 
aligned with the drift axis. Figure III-1 shows the input file mesh3dblock and the command 
used to generate the mesh. 
2. The Z-coordinate of the mesh is shifted by 8 m using software MoveMesh V1.0 (LBNL 2000 
[152824]) to translate the origin of the mesh to the center of the drift. The resulting grid is 
referred to as the primary mesh (file primary.mes). 
3. For each realization, a new seed number is inserted into the SISIM V1.204 input file 
perm.par (see Figure III-2). SISIM V1.204 (LBNL 2000 [153100]) is then executed to generate 
a random, spatially correlated field of log-permeability modifiers (file perm.dat). 
4. The heterogeneous field of permeability modifiers is mapped onto the mesh using software 
Perm2Mesh V1.0 (LBNL 2000 [152826]). 
5. A cylindrical drift of radius 2.5 m is cut from the mesh using software CutDrift V1.0 (LBNL 
2000 [152816]). The drift is centered at X = 0 and Z = 0 with its axis parallel to the Y-axis. 
6. Software AddBound V1.0 (LBNL 2000 [152823]) is used to attach boundary elements at the 
top and bottom of the model domain. The bottom-boundary gridblock is assigned to a special 
material domain (DRAIN) to allow specifying a free-drainage boundary condition. 
7. Software AddBorehole V1.0 (LBNL 2000 [152822]) is used to insert gridblocks representing 
a 6 ft (1.8288 m) long injection interval with a diameter of 3 inches (0.076 m). The injection 
interval lies within the Y-Z plane at a 15 angle from the horizontal, centered at X = 0.0 m, Y 
= 1.8288 m, and a Z coordinate that depends on the packed-off zone being tested (see Table 
III-1). The elevations Z [m] of the beginning and end of the borehole interval are calculated 
from their respective distances from the borehole collar d [ft] as follows: 
5 . 2 sin(15 3048 . 0 (III-1) Z = d   
elements represents evaporation. 
April 2003 MDL-NBS-HS-000004 REV02 
) +  
8. Drift elements (DRI98 and DRI99) are assigned a large volume so that Dirichlet boundary 
conditions can be specified. Flux into the drift elements represents seepage. 
9. Two new evaporation elements (EVA98 and EVA99) are added and connected to the same 
formation elements as the drift elements. The nodal distance from the formation elements to 
the evaporation elements is set to the diffusive boundary-layer thickness. Flux into these 
Attachment III-1 Seepage Calibration Model and Seepage Testing Data 
10. A single time step is performed using a generic TOUGH2 input file onestep (as input to 
iTOUGH2 V5.0; see Figure III-3) to test the mesh and to obtain cross-referencing informa- 
11. The final mesh is stored on file LAx_zoneY.mesZ, where x refers to the borehole number, Y 
designates the test interval, and Z labels the realization of the underlying random permeabil- 
File sh.LAx_zoneY_mes (see Figure III-5) was used to execute Mesh Generation Steps 311. The 
file documents all the Unix commands used as well as input variables to the individual software 
codes. An excerpt from a final sample mesh file LAx_zoneY.mesZ is shown in Figure III-6. 
NX 
NX 
NY 
NZ 
NZ 
NZ 
TOUGH2 input file for generating 3D block 
Command: tough2 mesh mesh3dblock 9 
MESHMAKER ----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
XYZ 
ENDFI ---1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
MDL-NBS-HS-000004 REV02 
SYBT-ECRB-LA#1 2 ~10 (3.0 m) 3.29 ~16 (4.9 m) 3.76 
SYBT-ECRB-LA#2 1 17 3.84 23 4.31 
2 33 5.10 39 5.58 
3 49 6.37 55 6.84 
SYBT-ECRB-LA#3 1 18 3.92 24 4.39 
2 34 5.18 40 5.66 
1 0.0500000 
40 0.1000000 
12 0.3048000 
1 0.600E-10 
110 0.1000000 
1 0.600E-10 
Figure III-1. Input file mesh3dblock to generate primary mesh 
April 2003 Attachment III-2 
U0080 
tion. The execution of the simulation is performed using file sh.onestep (Figure III-4) 
ity field. 
Table III-1. Input Z-Coordinates to Software AddBorehole V1.0 (Borehole Interval Elevations) 
End of interval Beginning of Interval 
Borehole Zone Distance from Collar Elevation 
d [ft] 
Distance from Collar Elevation 
d [ft] Z [m] Z [m] Seepage Calibration Model and Seepage Testing Data 
Generates weakly correlated random field of log-permeability modifiers 
for the seepage model of the systematic testing area in the ECRB Cross Drift. 
START OF PARAMETERS: 
dummy.dat 
1 2 3 4 
-1.0e21 1.0e21 
-2.0 2.0 
1 2.5 
1 1.0 
4 2.5 
dummy.dat 
3 0 
direct.ik 
perm.dat 
1
perm.dbg 
0
59067 
1
41 0.00 0.10 
12 0.1524 0.3048 
110 -3.00 0.10 
1
0
2.0 
0.0 0.0 0.0 1.0 1.0 
0 20 
12 
0 2.5 
0
8
-1.75 0.025 1 0.0 
1 0.2 1.00 
0.0 0.0 0.0 1.0 1.0 
1 0.0 
0.2 1.00 
-1.25 0.10 
1
0.0 0.0 0.0 1.0 1.0 
-0.75 0.225 1 0.0 
1 0.2 1.00 
0.0 0.0 0.0 1.0 1.0 
1 0.0 
0.2 1.00 
-0.25 0.40 
1
0.0 0.0 0.0 1.0 1.0 
1 0.0 0.25 0.60 
1 0.2 1.00 
0.0 0.0 0.0 1.0 1.0 
0.75 0.775 1 0.0 
0.2 1.00 1
0.0 0.0 0.0 1.0 1.0 
1 0.0 
0.2 1.00 
1.25 0.90 
1
0.0 0.0 0.0 1.0 1.0 
1.75 0.975 1 0.0 
1 0.2 1.00 
0.0 0.0 0.0 1.0 1.0 
SISIM V1.204 INPUT FILE perm.par 
******************************** 
Figure III-2. Input file perm.par to generate random field of log-permeability modifiers. 
MDL-NBS-HS-000004 REV02 
U0080 
ang1,ang2,ang3,anis1,2 
\data file 
\column: x,y,z,vr 
\data trimming limits 
\minimum and maximum data value 
\lower tail option and parameter 
\middle option and parameter 
\upper tail option and parameter 
\tabulated values for classes 
\column for variable, weight 
\direct input of indicators 
\output file for simulation 
\debugging level: 0,1,2,3 
\output File for Debugging 
\0=standard order relation corr 
\seed number 
\number of simulations 
\nx,xmn,xsiz 
\ny,ymn,ysiz 
\nz,zmn,zsiz 
\0=two part search, 1=data-nodes 
\ max per octant(0 -> not used) 
\ maximum search radius 
\ sang1,sang2,sang3,sanis1,2 
\ min, max data for simulation 
\number simulated nodes to use 
\0=full IK, 1=med approx(cutoff) 
\0=SK, 1=OK 
\number cutoffs 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ 
April 2003 Attachment III-3 Seepage Calibration Model and Seepage Testing Data 
Generic TOUGH2 input file; performs a single small time step 
ROCKS----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
.1000 1.000E-12 
.9900 1.000E-06 
2650. 
2650. 
FRACT 
LITHO 
.9900 1.000E-08 
.9900 1.000E-08 
2650. 
2650. 
DRIFT 
EVAPO 
.9900 1.000E-08 
.9900 1.000E-08 
2650. 
2650. 
BOREH 
BOUND 
.9900 1.000E-08 
.2000 1.000E-12 
2650. 
2650. 
DRAIN 
SKINZ 
.1000 1.000E-17 
.1000 1.000E-20 
2650. 
2650. 
MATRI 
PACKE 
.9900 1.000E-08 
.9900 1.000E-06 
2650. 
2650. 
NICHE 
CAVIT 
0
0
0
0
0
0
0
0
0
0
0
0 
PARAM----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
2 1 1100000000000000400003000 
1.000E-10 
0.5 
TIMES----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
1 
1.000E-11 
START----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
INCON----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
ENDCY----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
Figure III-3. Input file onestep used to perform a single time step. 
Figure III-4. File sh.onestep used to execute a forward run with a single time step. 
#! /bin/sh 
#
# Unix shell script file sh.onestep 
# usage: sh.onestep MeshFileName 
#
# Performs a single time step to create TOUGH2 mesh file 
#
# S. Finsterle, August 2002 
#
echo 
echo Start shell script sh.onestep $1 
echo ============================= 
#
echo 
echo Run one time step 
echo ----------------- 
tough2 -v 5.0 -mesh -m $1 onestep 9 
mv onestep.mes $1 
Attachment III-4 MDL-NBS-HS-000004 REV02 
U0080 
1000. 
100000. 
100000. 
100000. 
100000. 
100000. 
100000. 
1000. 
1000. 
1000. 
100000. 
100000. 
April 2003 echo "============================================================================" 
echo "Run $j of $runs" 
echo "============================================================================" 
echo "Create permeability modifier field, seed number: $i" 
U0080 Seepage Calibration Model and Seepage Testing Data 
#! /bin/sh 
#
# Unix shell script file to generate TOUGH2 mesh 
#
# sh.LAx_zoneY_mesh 
#
# S. Finsterle, 8/27/2002, V1.0 
#
echo 
echo Start shell script sh.LAx_zoneY_mesh 
echo ==================================== 
echo Date : `date` 
echo Directory : `pwd` 
echo 
#
i=0 
j=0 
runs=50 
# Start loop 
while test $j -lt $runs 
do 
# generate new seed number 
j=`expr $j + 1` 
i=`expr $j + $j` 
i=`expr $i + 59067` 
echo " " 
cat perm.par | sed "s/^.*seed/$i 
> perm.par$j 
xSisim << eof 
perm.par$j 
eof 
#
#
echo Map permeability field 
echo ---------------------- 
xPerm2Mesh << eof 
perm.dat 
primary.mes 
temp2.mes 
2
3
3
1
histdrift.tec 
0.1 
eof 
#
echo 
echo Cut out drift 
echo ------------- 
xCutDrift << eof 
temp2.mes 
temp3.mes 
35.91 
1.0e-10 
1.0 
0.0 
0.0 
MDL-NBS-HS-000004 REV02 
\\\seed/" \ 
# input permeability field 
# input mesh file 
# output mesh file 
# number of header lines 
# dimension of permeability field 
# TOUGH2 mesh is xyz 
# replace/add/multiply 
# histogram file name 
# class size 
# input mesh file 
# output mesh file 
# 1/2 drift volume 
# nodal distance niche - wall 
# cosine multiplication factor 
# XCenter 
# ZCenter 
April 2003 Attachment III-5 Seepage Calibration Model and Seepage Testing Data 
2.5 
eof 
#
echo 
echo Add top boundary 
echo ---------------- 
xAddBound << eof 
temp3.mes 
temp4.mes 
TOP99 
BOUND 
1.5e-1 
1.0e-5 
-100.0 
100.0 
-100.0 
100.0 
7.99 
8.01 
eof 
#
echo 
echo Add bottom boundary 
echo ------------------- 
xAddBound << eof 
temp4.mes 
temp5.mes 
BOT99 
DRAIN 
1.0e+20 
1.0e-5 
-100.0 
100.0 
-100.0 
100.0 
-3.01 
-2.99 
eof 
#
echo 
echo Add Borehole 
echo ------------ 
xAddBorehole << eof 
temp5.mes # input mesh file 
temp6.mes # output mesh file 
0.05 # dx 
0.3048 # dy 
0.10 # dz 
0.0 # XStart 
0.9145 # YStart=3*0.3048+0.0001 
5.1033 # ZStart=33*0.3048*sin(15)+2.5 
0.0 # XEnd 
2.681 # YEnd=YStart+6*0.3048*cos(15) 
5.57663 # ZEnd=39*0.3048*sin(15)+2.5 
0.01905 # Radius/2 (symmetry plane; d=3") 
eof 
#
echo 
echo Edit elements and connections 
echo ----------------------------- 
#
# increase drift element volume 
sed 's/DRIFT........../DRIFT0.5000E+52/g' temp6.mes > LAx_zoneY_noevap.mes 
MDL-NBS-HS-000004 REV02 
U0080 
# Radius 
# input mesh file 
# output mesh file 
# boundary element name 
# boundary material type 
# boundary element volume 
# nodal distance to boundary element 
# xmin 
# xmax 
# ymin 
# ymax 
# zmin 
# zmax 
# input mesh file 
# output mesh file 
# boundary element name 
# boundary material type 
# boundary element volume 
# nodal distance to boundary element 
# xmin 
# xmax 
# ymin 
# ymax 
# zmin 
# zmax 
April 2003 Attachment III-6 #
# separate blocks ELEME and CONNE 
cat LAx_zoneY_noevap.mes | sed -n '1,/BOR 0/p' > eleme 
cat LAx_zoneY_noevap.mes | sed -n '/TOP99A21 1/,$p' > conne 
#
# extract all drift elements and duplicate them for evaporation b.c. 
grep DRI LAx_zoneY_noevap.mes | sed 's/DRI/EVA/' | sed 's/DRIFT/EVAPO/' > elemeconne 
rm LAx_zoneY_noevap.mes 
#
# append the two evaporation elements at the end of block ELEME 
grep EVAPO elemeconne >> eleme 
#
# add empty line and keyword CONNE 
cat << eof >> eleme 
U0080 Seepage Calibration Model and Seepage Testing Data 
CONNE 
eof 
#
# change ISOT and nodal distances of connections to evaporation elements 
grep -v EVAP elemeconne | \ 
sed 's/EVA\(.......\).*0.1000E-090.5000E-01\(..........\).*$/EVA\1 
-180.1000E-090.7500E-02\2/' >> eleme 
#
# concatenate blcoks ELEME and CONNE 
cat eleme conne | sed 's/+++/ /' > LAx_zoneY.mes$j 
#
# run one time step to get "+++ " block in mesh file 
sh.onestep LAx_zoneY.mes$j 
#
echo 
echo Mesh generated: LAx_zoneY.mes$j 
echo ================================= 
done 
echo Script sh.LAx_zoneY_mesh completed: `date` 
echo =================================== 
Figure III-5. File sh.LAx_zoneY_mes used to execute mesh generation steps 311. 
Attachment III-7 MDL-NBS-HS-000004 REV02 April 2003 Seepage Calibration Model and Seepage Testing Data 
ELEME5 NX= 41 NY= 12 NZ= 112 
A21 1 
A31 1 
A41 1 
A51 1 
..... 
D3C41 
D4C41 
D5C41 
D6C41 
DRI98 
DRI99 
TOP99 
BOT99 
B 1 
B 2 
B 3 
B 4 
B 5 
B 6 
B 7 
B 8 
B 9 
B 10 
BOR 0 
EVA98 
EVA99
2AU5 1 
CONNE 
EVA99BL1 1 
EVA99D21 1 
EVA99BL2 1 
.......... 
EVA98CHC26 
EVA98CIC26 
EVA99CJC25 
TOP99A21 1 
A21 1A21 2 
A21 1A22 1 
A21 1A31 1 
.......... 
BK1 1BL1 1 
BL1 1BL1 2 
BL1 1BL2 1 
DRI99BL1 1 
DRI99D21 1 
D21 1D21 2 
D21 1D22 1 
D21 1D31 1 
.......... 
D61 1D61 2 
D61 1D62 1 
D61 1BOT99 
TOP99A22 1 
A22 1A22 2 
A22 1A23 1 
A22 1A32 1 
.......... 
D4C41D5C41 
D5C41D6C41 
D6C41BOT99 
B 1AU4 1 
B 
dx/dy/dz 0.0000E+000.0000E+000.8000E+01 
-.4604E+020.2500E-010.1524E+000.7950E+01 
-.1644E-010.2500E-010.1524E+000.7850E+01 
-.1477E+010.2500E-010.1524E+000.7750E+01 
-.1477E+010.2500E-010.1524E+000.7650E+01 
........................................ 
-.1320E+010.4000E+010.3505E+01-.2650E+01 
-.1236E+010.4000E+010.3505E+01-.2750E+01 
-.1236E+010.4000E+010.3505E+01-.2850E+01 
-.6929E+000.4000E+010.3505E+01-.2950E+01 
0.0000E+000.0000E+000.0000E+000.0000E+00 
0.0000E+000.0000E+000.0000E+000.0000E+00 
0.0000E+00-.1000E+04-.1000E+04-.1000E+04 
0.0000E+00-.1000E+04-.1000E+04-.1000E+04 
0.08633-.1000E+010.0000E+000.1067E+010.5144E+01 
0.18851-.1000E+010.0000E+000.1247E+010.5193E+01 
0.27478-.1000E+010.0000E+000.1400E+010.5233E+01 
0.38019-.1000E+010.0000E+000.1586E+010.5283E+01 
0.46646-.1000E+010.0000E+000.1738E+010.5324E+01 
0.57215-.1000E+010.0000E+000.1925E+010.5374E+01 
0.65842-.1000E+010.0000E+000.2078E+010.5415E+01 
0.76411-.1000E+010.0000E+000.2264E+010.5465E+01 
0.85039-.1000E+010.0000E+000.2417E+010.5506E+01 
0.93139-.1000E+010.0000E+000.2560E+010.5544E+01 
-.1000E+010.0000E+000.1798E+010.5340E+01 
0.0000E+000.0000E+000.0000E+000.0000E+00 
0.0000E+000.0000E+000.0000E+000.0000E+00 
10.1524E-02 
10.1524E-02 
10.1524E-02 
10.1524E-02 
........... 
10.3048E-02 
10.3048E-02 
10.3048E-02 
10.3048E-02 
DRIFT0.5000E+52 
DRIFT0.5000E+52 
BOUND0.1500E+00 
DRAIN0.1000E+21 
BOREH0.3598E-03 
BOREH0.6585E-04 
BOREH0.2939E-03 
BOREH0.1475E-03 
BOREH0.2122E-03 
BOREH0.2280E-03 
BOREH0.1317E-03 
BOREH0.3085E-03 
BOREH0.5121E-04 
BOREH0.2861E-03 
BOREH0.2085E-02 
EVAPO0.5000E+52 
EVAPO0.5000E+52 
-180.1000E-090.7500E-020.1524E-01 
-180.1000E-090.7500E-020.1524E-01 
-180.1000E-090.7500E-020.1524E-01 
................................. 
-180.1000E-090.7500E-020.3048E-01 
-180.1000E-090.7500E-020.3048E-01 
-180.1000E-090.7500E-020.3048E-01 
30.1000E-040.5000E-010.1524E-010.1000E+01 
10.2500E-010.5000E-010.3048E-010.0000E+00 
20.1524E+000.1524E+000.5000E-020.0000E+00 
30.5000E-010.5000E-010.1524E-010.1000E+01 
................................. 
30.5000E-010.5000E-010.1524E-010.1000E+01 
10.2500E-010.5000E-010.3048E-010.0000E+00 
20.1524E+000.1524E+000.5000E-020.0000E+00 
30.1000E-090.5000E-010.1524E-01-.1000E+01 
30.1000E-090.5000E-010.1524E-010.1000E+01 
10.2500E-010.5000E-010.3048E-010.0000E+00 
20.1524E+000.1524E+000.5000E-020.0000E+00 
30.5000E-010.5000E-010.1524E-010.1000E+01 
................................. 
10.2500E-010.5000E-010.3048E-010.0000E+00 
20.1524E+000.1524E+000.5000E-020.0000E+00 
30.5000E-010.1000E-040.1524E-010.1000E+01 
30.1000E-040.5000E-010.1524E-010.1000E+01 
10.2500E-010.5000E-010.3048E-010.0000E+00 
20.1524E+000.1524E+000.5000E-020.0000E+00 
30.5000E-010.5000E-010.1524E-010.1000E+01 
................................. 
30.5000E-010.5000E-010.3048E-010.1000E+01 
30.5000E-010.5000E-010.3048E-010.1000E+01 
30.5000E-010.1000E-040.3048E-010.1000E+01 
10.1000E-090.5000E-010.3777E-010.9659E+00 
10.1000E-090.5000E-010.6913E-020.9659E+00 
MDL-NBS-HS-000004 REV02 Attachment III-8 
U0080 
April 2003 Seepage Calibration Model and Seepage Testing Data 
B 3AT5 1 
B 4AT6 1 
B 5AS6 1 
B 6AS7 1 
B 7AR7 1 
B 8AR8 1 
B 9AQ8 1 
B 10AQ9 1 
B 1B 2 
B 2B 3 
B 3B 4 
B 4B 5 
B 5B 6 
B 6B 7 
B 7B 8 
B 8B 9 
B 9B 10 
BOR 0B 1 
BOR 0B 2 
BOR 0B 3 
BOR 0B 4 
BOR 0B 5 
BOR 0B 6 
BOR 0B 7 
BOR 0B 8 
BOR 0B 9 
BOR 0B 10 
+++ 
55 
176 
42113 
42113 
355 
..... 
42113 
..... 
42110 
42105 
42109 
42111 
42110 42111 
Figure III-6. Excerpt from sample mesh file LAx_zoneY.mesZ. 
10.1000E-090.5000E-010.3086E-010.9659E+00 
10.1000E-090.5000E-010.1549E-010.9659E+00 
10.1000E-090.5000E-010.2228E-010.9659E+00 
10.1000E-090.5000E-010.2394E-010.9659E+00 
10.1000E-090.5000E-010.1383E-010.9659E+00 
10.1000E-090.5000E-010.3239E-010.9659E+00 
10.1000E-090.5000E-010.5377E-020.9659E+00 
10.1000E-090.5000E-010.3004E-010.9659E+00 
20.1578E+000.2888E-010.1140E-02-.2588E+00 
20.2888E-010.1289E+000.1140E-02-.2588E+00 
20.1289E+000.6470E-010.1140E-02-.2588E+00 
20.6470E-010.9307E-010.1140E-02-.2588E+00 
20.9307E-010.1000E+000.1140E-02-.2588E+00 
20.1000E+000.5777E-010.1140E-02-.2588E+00 
20.5777E-010.1353E+000.1140E-02-.2588E+00 
20.1353E+000.2246E-010.1140E-02-.2588E+00 
20.2246E-010.1255E+000.1140E-02-.2588E+00 
30.1000E-090.1905E-010.3777E-010.1000E+01 
30.1000E-090.1905E-010.6913E-020.1000E+01 
30.1000E-090.1905E-010.3086E-010.1000E+01 
30.1000E-090.1905E-010.1549E-010.1000E+01 
30.1000E-090.1905E-010.2228E-010.1000E+01 
30.1000E-090.1905E-010.2394E-010.1000E+01 
30.1000E-090.1905E-010.1383E-010.1000E+01 
30.1000E-090.1905E-010.3239E-010.1000E+01 
30.1000E-090.1905E-010.5377E-020.1000E+01 
30.1000E-090.1905E-010.3004E-010.1000E+01 
42113 
42113 
56 
235 
42113 
42113 
42113 
..... 
356 
..... 
42113 
..... 
42111 
42111 
42101 
42106 
42111 
42111 
MDL-NBS-HS-000004 REV02 
U0080 
175 
296 
42113 
42113 
116 
295 
42113 
42113 
115 
236 
475 
..... 
42113 
..... 
416 
..... 
42113 
..... 
415 
..... 
42104 
42109 
42111 
42111 
42103 
42108 
42111 
42111 
42102 
42107 
April 2003 Attachment III-9 Seepage Calibration Model and Seepage Testing Data 
INTENTIONALLY LEFT BLANK 
Attachment III-10 MDL-NBS-HS-000004 REV02 
U0080 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
ATTACHMENT IV 
MESH GENERATION FOR SIMULATION OF SEEPAGE TESTS IN 
niche axis. 
MDL-NBS-HS-000004 REV02 
NICHES 3107, 3650, AND 4788 
Four 3D meshes for the simulation of liquid-release tests in niches located in the middle 
nonlithophysal zone are generated: two 1.5 m long sections of Niche 3650 centered (a) 4.42 m 
and (b) 5.64 m from the collar of borehole UM, (c) a 1.5 m long section of Niche 3107 centered 
at Niche 3107 station 00+10.25 m, and (d) a 2.0 m long section of Niche 4788 centered at Niche 
4788 station 00+11.45 m. The meshes are created in several steps as follows (where steps differ, 
information for each mesh is preceded by the letter referring to a specific panel of Figure 16): 
1. Primary meshes are generated with X-Y-Z dimensions of (a & b) 6.0 m  1.5 m  5.0 m, (c) 
6.5 m  1.5 m  5.0 m, and (d) 6.0 m  2.0 m  5.0 m, respectively, that are discretized into 
regular gridblocks with side lengths of 0.1 m  0.1 m  0.1 m. The Y-axis is parallel to the 
2. The X-, Y-, and Z-coordinates of each primary mesh are translated using software 
MoveMesh V1.0 (LBNL 2000 [152824]) so that X = 0 is at the center of the Niche, Y = 0 
coincides with Niche station 00 + 0.0 m for Meshes (c) and (d), and Z = 0 is (a & b) at the 
bottom of the mesh and (c & d) coincides with the local survey Z datum. 
3. The heterogeneous permeability fields are mapped onto their respective meshes using routine 
Perm2Mesh V1.0 (LBNL 2000 [152826]). 
4. (a & b) A niche with vertical walls at X = -2 m and X = 2 m and a ceiling of radius 3.04 m 
with the crown at (a) Z = 3.13 m and (b) Z = 3.33 m is cut from the mesh using software 
CutNiche V1.3 (LBNL 2000 [152828]). (c & d) Niches with vertical walls at (c) X = -2.15 m 
and X = 2.35 m and (d) X = -2.00 m and X = 1.90 m and ceilings defined by survey data are 
cut from their respective meshes using software CutNiche V1.2 (LBNL 2000 [152815]). A 
very small nodal distance is defined between the interfaces representing the drift surface and 
the gridblocks denoting the drift, which sets boundary conditions directly at the drift wall. 
The length of the last vertical connection from the gridblocks representing the formation and 
the interface denoting the drift surface is thus .Z/2 = 0.05 m. 
5. Software AddBound V1.0 (LBNL 2000 [152823]) is used to attach boundary elements at the 
top and bottom of the model domain. The bottom boundary gridblock is assigned to a special 
material domain to allow specifying a free-drainage boundary condition. 
6. Gridblocks along the alignment of the injection boreholes are modified to represent 1 ft 
(0.3048 m) long injection intervals with a diameter of 3 inches (0.076 m). 
The final meshes (see Figure 16) contain approximately (a) 28,000 gridblocks and 79,000 
connections between them, (b) 26,000 gridblocks and 76,000 connections between them, (c) 
34,000 gridblocks and 99,000 connections between them, (d) 36,000 gridblocks and 108,000 
connections between them. Mesh generation is further documented in various SNs (Finsterle 
1999 [153448], pp. 100.102; Ahlers 2002 [161045], pp. 27.29, 42.44, 54; Hedegaard 2002 
[161046], pp. 27.29; Wang 1999 [153449], pp. 108.123; and Trautz 2001 [156903], pp. 35.45). 
Attachment IV-1 April 2003 Seepage Calibration Model and Seepage Testing Data 
INTENTIONALLY LEFT BLANK 
Attachment IV-2 MDL-NBS-HS-000004 REV02 
U0080 
April 2003 Seepage Calibration Model and Seepage Testing Data 
Preparation of the computational meshes for simulating liquid-release tests performed in Niche 
1620 involved three major steps: (1) preparation of niche ceiling coordinates, (2) preparation of 
geostatistical parameters of the permeability field, and (3) preparation of numerical grids. 
MESH GENERATION FOR SEEPAGE TEST SIMULATIONS IN NICHE 1620 
V-1. Preparation of Niche Ceiling Coordinates 
The niche surface roughness was reproduced by interpolation from niche survey data (data 
sources are listed in Table V-1). 
Table V-1. Survey Data Sources for the Ceiling of Niche 1620 
DTN 
MO0009GSC00332.000 [155370] ECRB Niche 1620 profile survey data 
MO0107GSC01061.000 [155369] ECRB Niche 1620 slot survey data 
LB0301N5CEILNG.001 [161733] ECRB Niche 1620 survey data for collars, 
Description 
LB0301N5CEILNG.001 [161733] ECRB Niche 1620 detailed profile survey data Distance from reference frame 
The steps followed in preparing the interpolated Niche 1620 ceiling profiles are described below. 
The datum point for the meshes was selected to be the intersection of the ECRB centerline and 
Niche 1620 centerline (DTN: MO0009GSC00332.000 [155370]). The location of the datum in 
the Nevada coordinate system is given in Table V-2. 
The coordinates of the ECRB Niche 1620 profile survey data (DTN: MO0009GSC00332.000 
[155370]), slot survey data (DTN: MO0107GSC01061.000 [155369]), and survey data for 
collars, projected bottoms, and intervals (DTN: MO0209GSC02116.000 [160407]) were 
X . transformed to a regular Y . Z coordinate system using the following elementary analytical 
geometry formulae: 
MDL-NBS-HS-000004 REV02 
233276.41 170662.51 1105.91 
(V-1) X = D D 
Y = 
Elevation 
ELD [m] 
U0080 
ATTACHMENT V 
DIRS # Coordinate System 
Nevada State Plae 
projected bottoms, and intervals 
Table V-2. Datum of Niche 1620 in the Nevada Coordinate System 
(DTN: MO0009GSC00332.000 [155370]) 
Easting 
ESD [m] 
Northing 
ND [m] 
D D 
D 
Azimuth 
A [degrees] 
181 
April 2003 
( )cos sin  . .  + . . ES ES ()(N N) () 
(V-2) ( cos . . .  + N N ) ( ) (ES . ES ) sin( )  
( ) EL . EL (V-3) Z = 
Attachment V-1 U0080 Seepage Calibration Model and Seepage Testing Data 
where ES [m] is easting, N [m] is northing, EL [m] is elevation, and the subscript D denotes 
the values of the datum (see Table V-2). The angle  [degrees] is related to the azimuth angle 
A .  =  360 
A [m] by, 
(V-4) 
Niche 1620 Profile 
X . 
The original ECRB Niche 1620 profile survey data (DTN: MO0009GSC00332.000 [155370]), 
slot survey data (DTN: MO0107GSC01061.000 [155369]) and their corresponding values in 
Y . Z are given in Table V-3. 
Table V-3. Niche 1620 Profile Survey Data (DTN: MO0009GSC00332.000 [155370]) and Slot 
Y . Z Coordinate System 
Survey Data (DTN: MO0107GSC01061.000 [155369]) and Their Corresponding 
Values in the X . 
Station Y [m] X [m] Northing [m] Elevation [m] Easting [m] Z [m] 
0+00.97 170667.36 233277.30 1108.24 -4.83 -0.81 2.33 
0+00.83 170665.36 233275.54 1108.23 -2.86 0.92 2.32 
0+01.48 170662.48 233274.93 1106.39 0.00 1.48 0.48 
0+01.49 170662.48 233274.92 1110.70 0.00 1.49 4.79 
0+02.11 170662.47 233274.31 1110.63 0.00 2.10 4.72 
0+02.12 170662.47 233274.30 1106.42 0.00 2.11 0.51 
0+02.37 170662.47 233274.04 1111.72 0.00 2.37 5.81 
0+02.38 170662.47 233274.04 1106.42 0.00 2.37 0.51 
0+05.12 170662.42 233271.29 1112.09 0.00 5.12 6.18 
0+05.12 170662.42 233271.29 1106.51 0.00 5.12 0.60 
0+06.18 170659.37 233270.29 1108.42 3.03 6.06 2.51 
0+06.88 170658.44 233269.60 1107.96 3.95 6.74 2.05 
0+07.45 170665.05 233268.92 1108.40 -2.67 7.53 2.49 
0+07.86 170659.65 233268.60 1108.46 2.72 7.76 2.55 
0+09.57 170662.34 233266.84 1112.87 0.00 9.57 6.96 
0+09.57 170662.34 233266.84 1106.59 0.00 9.57 0.68 
0+09.88 170659.75 233266.58 1108.52 2.59 9.78 2.61 
0+11.57 170665.07 233264.80 1108.38 -2.76 11.65 2.47 
0+12.50 170659.63 233263.96 1108.48 2.66 12.40 2.57 
0+13.04 170662.28 233263.37 1112.82 0.00 13.03 6.91 
0+13.24 170662.28 233263.18 1106.60 0.00 13.22 0.69 
0+13.26 170662.28 233263.16 1111.52 0.00 13.24 5.61 
0+13.69 170659.76 233262.77 1108.62 2.51 13.59 2.71 
0+14.00 170662.27 233262.42 1110.09 0.00 13.98 4.18 
0+14.02 170662.27 233262.39 1106.57 0.00 14.01 0.66 
0+14.17 170664.52 233262.21 1108.48 -2.26 14.23 2.57 
0+14.18 170660.22 233262.28 1108.57 2.04 14.09 2.66 
0+14.96 170662.25 233261.45 1110.08 0.00 14.95 4.17 
0+14.98 170662.25 233261.44 1106.64 0.00 14.96 0.73 
0+14.98 170660.22 233261.47 1108.21 2.03 14.90 2.30 
0+15.10 170664.42 233261.27 1108.41 -2.17 15.17 2.50 
April 2003 Attachment V-2 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
0+17.47 170662.21 233258.94 1106.58 0.00 17.46 0.67 
0+17.47 170662.21 233258.94 1110.10 0.00 17.46 4.19 
0+18.63 170660.11 233257.82 1108.55 2.08 18.55 2.64 
0+18.75 170664.04 233257.64 1108.55 -1.86 18.79 2.64 
0+20.39 170662.16 233256.02 1106.65 -0.01 20.38 0.74 
0+20.41 170662.16 233256.01 1110.17 -0.01 20.39 4.26 
0+21.52 170660.00 233254.94 1108.68 2.13 21.42 2.77 
0+21.94 170664.00 233254.44 1108.57 -1.87 21.99 2.66 
0+24.77 170660.11 233251.68 1108.50 1.97 24.68 2.59 
0+24.89 170664.26 233251.49 1108.56 -2.18 24.95 2.65 
0+25.94 170662.06 233250.47 1106.70 0.00 25.93 0.79 
0+25.95 170662.06 233250.47 1110.29 0.00 25.93 4.38 
0+26.79 170664.49 233249.58 1108.61 -2.45 26.86 2.70 
0+27.33 170664.12 233249.05 1108.55 -2.09 27.38 2.64 
0+28.45 170662.02 233247.97 1110.16 -0.01 28.43 4.25 
0+28.46 170662.02 233247.96 1106.71 -0.01 28.44 0.80 
0+28.46 170659.96 233247.99 1108.78 2.05 28.37 2.87 
0+28.57 170664.02 233247.81 1108.66 -2.01 28.62 2.75 
0+28.97 170662.01 233247.45 1110.10 -0.01 28.95 4.19 
0+28.97 170662.01 233247.45 1106.88 -0.01 28.95 0.97 
0+29.21 170662.00 233247.21 1108.73 0.00 29.19 2.82 
Niche 1620 Slots 
Y [m] X [m] Northing [m] Elevation [m] Easting [m] Point No. Z [m] 
100 170664.23 233256.66 1108.93 -2.06 19.78 3.02 
101 170664.58 233256.63 1108.94 -2.41 19.81 3.03 
102 170665.03 233256.61 1109.09 -2.87 19.84 3.18 
103 170665.35 233256.60 1108.96 -3.19 19.86 3.05 
104 170665.55 233256.65 1108.91 -3.38 19.81 3.00 
105 170665.75 233256.68 1108.86 -3.58 19.78 2.95 
106 170665.72 233256.66 1108.51 -3.55 19.80 2.60 
107 170665.62 233256.66 1108.27 -3.45 19.80 2.36 
108 170665.23 233256.58 1108.06 -3.07 19.87 2.15 
109 170664.89 233256.60 1107.96 -2.73 19.85 2.05 
110 170664.48 233256.57 1107.84 -2.32 19.87 1.93 
111 170664.24 233256.50 1107.55 -2.08 19.94 1.64 
112 170664.10 233256.79 1109.08 -1.93 19.64 3.17 
113 170664.06 233255.67 1109.15 -1.91 20.76 3.24 
114 170664.20 233255.72 1108.97 -2.05 20.72 3.06 
115 170664.69 233255.79 1108.97 -2.54 20.65 3.06 
116 170664.89 233255.91 1109.02 -2.74 20.54 3.11 
117 170665.16 233255.79 1109.28 -3.01 20.66 3.37 
118 170665.55 233255.76 1109.32 -3.40 20.70 3.41 
119 170665.85 233255.79 1109.18 -3.70 20.68 3.27 
120 170666.00 233255.84 1108.87 -3.85 20.63 2.96 
121 170665.97 233255.78 1108.54 -3.82 20.69 2.63 
122 170665.60 233255.71 1108.19 -3.45 20.75 2.28 
123 170665.35 233255.76 1107.95 -3.20 20.70 2.04 
124 170665.16 233255.71 1107.90 -3.01 20.74 1.99 
April 2003 Attachment V-3 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
125 170664.57 233255.62 1107.72 -2.42 20.82 1.81 
126 170664.40 233255.49 1107.38 -2.25 20.95 1.47 
127 170664.08 233254.52 1109.29 -1.95 21.91 3.38 
128 170664.34 233254.59 1109.11 -2.21 21.85 3.20 
129 170664.78 233254.58 1109.35 -2.65 21.87 3.44 
130 170665.34 233254.54 1109.33 -3.21 21.92 3.42 
131 170665.61 233254.52 1109.27 -3.48 21.94 3.36 
132 170665.84 233254.42 1109.01 -3.71 22.04 3.10 
133 170665.73 233254.43 1108.61 -3.60 22.03 2.70 
134 170665.63 233254.29 1108.40 -3.51 22.17 2.49 
135 170665.50 233254.31 1108.10 -3.38 22.15 2.19 
136 170665.15 233254.39 1108.01 -3.02 22.06 2.10 
137 170664.59 233254.48 1107.94 -2.46 21.96 2.03 
138 170664.18 233254.48 1107.45 -2.05 21.96 1.54 
139 170664.16 233253.96 1109.11 -2.04 22.48 3.20 
140 170664.34 233253.91 1109.06 -2.22 22.53 3.15 
141 170664.68 233253.90 1109.17 -2.56 22.54 3.26 
142 170665.07 233253.99 1109.26 -2.95 22.46 3.35 
143 170665.30 233254.03 1109.24 -3.18 22.43 3.33 
144 170665.75 233253.98 1109.41 -3.63 22.48 3.50 
145 170666.06 233253.77 1109.25 -3.94 22.70 3.34 
146 170666.12 233253.75 1109.01 -4.00 22.72 3.10 
147 170665.73 233253.78 1108.73 -3.61 22.68 2.82 
148 170665.74 233253.82 1108.37 -3.62 22.64 2.46 
149 170665.40 233253.91 1108.15 -3.28 22.55 2.24 
150 170665.07 233253.88 1108.12 -2.95 22.57 2.21 
151 170664.71 233253.81 1108.04 -2.59 22.63 2.13 
152 170664.44 233253.66 1107.96 -2.33 22.78 2.05 
153 170664.35 233253.75 1107.83 -2.24 22.69 1.92 
154 170664.22 233254.08 1108.87 -2.10 22.36 2.96 
155 170664.28 233257.61 1108.66 -2.10 18.83 2.75 
156 170664.35 233257.44 1108.66 -2.17 19.00 2.75 
157 170664.44 233257.30 1107.87 -2.26 19.14 1.96 
158 170664.34 233257.33 1108.65 -2.16 19.11 2.74 
159 170664.47 233257.22 1107.86 -2.29 19.22 1.95 
160 170664.22 233256.09 1108.76 -2.06 20.35 2.85 
161 170664.25 233256.04 1106.73 -2.10 20.40 0.82 
162 170664.18 233254.74 1107.45 -2.05 21.70 1.54 
163 170664.20 233254.76 1108.87 -2.07 21.68 2.96 
164 170664.24 233254.20 1108.93 -2.12 22.24 3.02 
165 170664.25 233254.13 1107.53 -2.13 22.31 1.62 
166 170664.40 233252.89 1108.74 -2.30 23.55 2.83 
167 170664.36 233253.57 1108.67 -2.25 22.87 2.76 
168 170664.65 233253.77 1108.73 -2.53 22.67 2.82 
169 170665.15 233253.86 1108.67 -3.03 22.59 2.76 
170 170665.64 233253.87 1108.71 -3.52 22.59 2.80 
171 170664.20 233257.98 1108.63 -2.01 18.46 2.72 
172 170664.36 233257.73 1108.75 -2.18 18.71 2.84 
April 2003 Attachment V-4 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
173 170664.73 233257.23 1108.81 -2.55 19.22 2.90 
174 170665.26 233257.03 1109.12 -3.09 19.43 3.21 
175 170665.46 233256.97 1109.14 -3.29 19.49 3.23 
176 170665.31 233257.07 1108.04 -3.14 19.39 2.13 
177 170664.88 233257.14 1108.02 -2.71 19.31 2.11 
178 170664.31 233257.45 1107.90 -2.13 18.99 1.99 
179 170664.24 233257.79 1107.88 -2.05 18.65 1.97 
180 170664.25 233257.80 1108.32 -2.06 18.64 2.41 
181 170664.34 233257.46 1108.32 -2.16 18.98 2.41 
182 170664.73 233257.32 1108.38 -2.55 19.13 2.47 
183 170664.86 233257.16 1108.42 -2.69 19.29 2.51 
184 170665.36 233257.08 1108.50 -3.19 19.38 2.59 
185 170660.10 233255.84 1109.44 2.05 20.52 3.53 
186 170659.81 233255.88 1109.15 2.34 20.48 3.24 
187 170659.58 233255.87 1108.88 2.57 20.49 2.97 
188 170659.29 233255.88 1108.73 2.86 20.47 2.82 
189 170659.34 233255.88 1108.55 2.81 20.47 2.64 
190 170659.66 233255.83 1108.42 2.49 20.53 2.51 
191 170659.91 233255.74 1108.19 2.24 20.62 2.28 
192 170660.01 233255.80 1107.87 2.14 20.56 1.96 
193 170659.92 233256.93 1108.65 2.25 19.43 2.74 
194 170659.82 233256.57 1108.62 2.34 19.79 2.71 
195 170659.52 233256.31 1108.61 2.64 20.04 2.70 
196 170659.39 233256.02 1108.68 2.76 20.33 2.77 
197 170659.26 233255.84 1108.62 2.89 20.51 2.71 
198 170659.42 233255.68 1108.61 2.73 20.67 2.70 
199 170659.70 233255.42 1108.58 2.44 20.94 2.67 
200 170659.68 233255.04 1108.62 2.46 21.32 2.71 
201 170659.82 233254.56 1108.66 2.31 21.80 2.75 
Detailed measurement of the niche ceiling roughness was carried out with reference to a 
horizontal frame located 2.98 m above the datum as shown in Table V-4 (DTN: 
LB0301N5CEILNG.001 [161733]). 
April 2003 Attachment V-5 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
Table V-4. Niche 1620 Ceiling Roughness Data 
X [m] 
-1.40 
-1.09 
-0.78 
-0.48 
-0.17 
0.14 
0.45 
0.76 
1.06 
1.37 
1.68 
-1.40 
-1.09 
-0.78 
-0.48 
-0.17 
0.14 
0.45 
0.76 
1.06 
1.37 
1.68 
-1.40 
-1.09 
-0.78 
-0.48 
-0.17 
0.14 
0.45 
0.76 
1.06 
1.37 
1.68 
-1.40 
-1.09 
-0.78 
-0.48 
-0.17 
0.14 
0.45 
0.76 
1.06 
1.37 
1.68 
-1.40 
-1.09 
-0.78 
MDL-NBS-HS-000004 REV02 
U0080 
Z [m] 
4.02 
4.29 
4.38 
4.54 
4.30 
4.27 
4.25 
4.26 
4.30 
4.17 
3.96 
4.21 
4.30 
4.36 
4.40 
4.54 
4.46 
4.39 
4.37 
4.35 
4.20 
3.98 
4.06 
4.26 
4.27 
4.57 
4.36 
4.35 
4.38 
4.38 
4.28 
4.15 
4.09 
4.18 
4.29 
4.33 
4.36 
4.49 
4.42 
4.42 
4.47 
4.38 
4.28 
4.05 
3.98 
4.18 
4.32 
Y [m] 
27.86 
27.86 
27.86 
27.86 
27.86 
27.86 
27.86 
27.86 
27.86 
27.86 
27.86 
26.56 
26.56 
26.56 
26.56 
26.56 
26.56 
26.56 
26.56 
26.56 
26.56 
26.56 
25.26 
25.26 
25.26 
25.26 
25.26 
25.26 
25.26 
25.26 
25.26 
25.26 
25.26 
23.96 
23.96 
23.96 
23.96 
23.96 
23.96 
23.96 
23.96 
23.96 
23.96 
23.96 
22.66 
22.66 
22.66 
April 2003 Attachment V-6 Seepage Calibration Model and Seepage Testing Data 
-0.48 
-0.17 
0.14 
0.45 
0.76 
1.06 
1.37 
1.68 
-1.40 
-1.09 
-0.78 
-0.48 
-0.17 
0.14 
0.45 
0.76 
1.06 
1.37 
1.68 
-1.40 
-1.09 
-0.78 
-0.48 
-0.17 
0.14 
0.45 
0.76 
1.06 
1.37 
1.68 
-1.40 
-1.09 
-0.78 
-0.48 
-0.17 
0.14 
0.45 
0.76 
1.06 
1.37 
1.68 
-1.40 
-1.09 
-0.78 
-0.48 
-0.17 
22.66 
22.66 
22.66 
22.66 
22.66 
22.66 
22.66 
22.66 
21.36 
21.36 
21.36 
21.36 
21.36 
21.36 
21.36 
21.36 
21.36 
21.36 
21.36 
20.06 
20.06 
20.06 
20.06 
20.06 
20.06 
20.06 
20.06 
20.06 
20.06 
20.06 
18.76 
18.76 
18.76 
18.76 
18.76 
18.76 
18.76 
18.76 
18.76 
18.76 
18.76 
17.46 
17.46 
17.46 
17.46 
17.46 
17.46 
17.46 
17.46 
17.46 
0.14 
0.45 
0.76 
1.06 
Attachment V-7 MDL-NBS-HS-000004 REV02 
U0080 
4.42 
4.58 
4.42 
4.71 
4.38 
4.36 
4.26 
4.36 
3.97 
4.13 
4.18 
4.25 
4.35 
4.33 
4.63 
4.28 
4.19 
4.18 
3.99 
3.90 
4.11 
4.17 
4.25 
4.27 
4.21 
4.22 
4.32 
4.31 
4.16 
4.00 
3.96 
3.89 
4.03 
4.10 
4.09 
4.07 
4.08 
4.08 
4.13 
4.20 
3.79 
4.00 
3.91 
3.93 
3.99 
4.17 
4.19 
4.06 
4.10 
4.05 
April 2003 Seepage Calibration Model and Seepage Testing Data 
1.37 
1.68 
-1.40 
-1.09 
-0.78 
-0.48 
-0.17 
0.14 
0.45 
0.76 
1.06 
1.37 
1.68 
-1.40 
-1.09 
-0.78 
-0.48 
-0.17 
0.14 
0.45 
0.76 
1.06 
1.37 
1.68 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
-1.40 
17.46 
17.46 
16.16 
16.16 
16.16 
16.16 
16.16 
16.16 
16.16 
16.16 
16.16 
16.16 
16.16 
14.87 
14.87 
14.87 
14.87 
14.87 
14.87 
14.87 
14.87 
14.87 
14.87 
14.87 
15.19 
15.51 
15.84 
16.49 
16.81 
17.14 
17.79 
18.11 
18.44 
19.09 
19.41 
19.74 
20.39 
20.71 
21.04 
21.69 
22.01 
22.34 
22.99 
23.31 
23.64 
24.29 
24.61 
24.94 
25.59 
25.91 
Attachment V-8 MDL-NBS-HS-000004 REV02 
U0080 
3.92 
3.62 
3.83 
3.86 
4.06 
4.14 
4.12 
4.09 
4.18 
4.09 
4.07 
3.92 
3.77 
3.65 
3.79 
3.92 
4.15 
4.20 
4.05 
4.18 
4.24 
4.34 
3.90 
3.98 
3.66 
3.62 
3.63 
3.77 
3.91 
3.78 
4.08 
3.70 
3.73 
3.88 
3.93 
3.97 
4.16 
4.09 
4.10 
4.00 
3.96 
3.96 
4.09 
4.19 
4.17 
4.12 
4.18 
4.28 
4.20 
4.27 
April 2003 Seepage Calibration Model and Seepage Testing Data 
-1.40 
-1.40 
-1.40 
-1.40 
1.68 
1.68 
1.68 
1.68 
1.68 
1.68 
-2.19 
-2.49 
-2.21 
-2.15 
-1.87 
-1.98 
-1.85 
-1.77 
-1.85 
-1.91 
-2.11 
2.13 
2.14 
2.19 
2.22 
2.33 
2.34 
2.21 
2.38 
2.18 
2.22 
2.09 
-1.40 
0.14 
1.68 
26.24 
26.89 
27.21 
27.54 
15.19 
15.51 
15.84 
16.49 
16.81 
17.14 
14.87 
16.16 
17.46 
18.76 
20.06 
21.36 
22.66 
23.96 
25.26 
26.56 
27.86 
14.87 
16.16 
17.46 
18.76 
20.06 
21.36 
22.66 
23.96 
25.26 
26.56 
27.86 
27.86 
27.86 
27.86 
The survey data shown in Table V-3 and Table V-4 were interpolated onto a regular X - Y 
plane of 0.1 m  0.1 m resolution using a linear interpolation tool of the software Tecplot V9.0. 
Excerpts of the resulting Niche 1620 ceiling and slot profiles are shown in Figure V-1, and 
Figure V-4 shows the plan view of the ceiling roughness. 
Attachment V-9 MDL-NBS-HS-000004 REV02 
U0080 
4.34 
4.40 
4.11 
4.07 
3.87 
3.74 
3.79 
3.84 
3.82 
3.81 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
2.98 
April 2003 Figure V-1. Excerpts from interpolated ceiling profile of Niche 1620. 
Niche 1620 left batwing 
-4.450000E+000 1.455000E+001 0.000000E+000 
-4.350000E+000 1.455000E+001 0.000000E+000 
-4.250000E+000 1.455000E+001 0.000000E+000 
-2.850000E+000 1.965000E+001 3.026709E+000 
-2.650000E+000 1.965000E+001 2.910188E+000 
-2.550000E+000 1.965000E+001 2.883803E+000 
x y z 
.... 
.... 
-1.650000E+000 2.355000E+001 0.000000E+000 
-1.550000E+000 2.355000E+001 0.000000E+000 
-1.450000E+000 2.355000E+001 0.000000E+000 
Figure V-2. Excerpts from interpolated left slot profile of Niche 1620. 
Niche 1620 right batwing data 
x y z 
2.050000E+000 1.455000E+001 0.000000E+000 
2.150000E+000 1.455000E+001 0.000000E+000 
2.250000E+000 1.455000E+001 0.000000E+000 
2.250000E+000 2.005000E+001 2.991148E+000 
2.350000E+000 2.005000E+001 2.904599E+000 
2.450000E+000 2.005000E+001 2.835122E+000 
2.750000E+000 2.355000E+001 0.000000E+000 
2.850000E+000 2.355000E+001 0.000000E+000 
2.950000E+000 2.355000E+001 0.000000E+000 
Figure V-3. Excerpts from interpolated right slot profile of Niche 1620. 
Seepage Calibration Model and Seepage Testing Data 
Niche 1620 ceiling 
x y z 
-3.050000E+000 1.455000E+001 0.000000E+000 
-2.950000E+000 1.455000E+001 0.000000E+000 
-2.850000E+000 1.455000E+001 0.000000E+000 
... 
6.500000E-001 1.505000E+001 4.222630E+000 
7.500000E-001 1.505000E+001 4.225305E+000 
8.500000E-001 1.505000E+001 4.252642E+000 
... 
2.750000E+000 2.355000E+001 0.000000E+000 
2.850000E+000 2.355000E+001 0.000000E+000 
2.950000E+000 2.355000E+001 0.000000E+000 
Attachment V-10 MDL-NBS-HS-000004 REV02 
U0080 
April 2003 Seepage Calibration Model and Seepage Testing Data 
24 
23 
22 
21 
20 
19 
18 
17 
16 
15 
14 
-3 -4 
Figure V-4. Plan view of Niche 1620 ceiling and slot surface roughness (output DTN: 
X [m] 
LB0302SCMREV02.002) 
MDL-NBS-HS-000004 REV02 
Y [m] 
U0080 
Z [m] 
4.5 
4.2 
3.9 
3.6 
3.4 
3.1 
2.8 
2.5 
3 2 1 0 -1 -2 
April 2003 Attachment V-11 Seepage Calibration Model and Seepage Testing Data 
V-2. Location of Boreholes and Preparation of Geostatistical Parameters of Air- 
Permeability 
The locations of the borehole collars and projected endpoints (DTN: MO0209GSC02116.000 
X - [160407]) were transformed from the Nevada coordinate system to the regular Y - Z 
coordinate system using Equations (V-1) to (V-4). The original borehole surveys and their 
transformed equivalents are listed in Table V-5. 
Table V-5. Original and Transformed Coordinates of Borehole Collars and Projected Bottoms 
ECRB-NICHE1620 #1 
Collar #1 
Projected Bottom 
ECRB-NICHE1620 #2 
Collar #2 
Projected Bottom 
ECRB-NICHE1620 #3 
Collar #3 
Projected Bottom 
ECRB-NICHE1620 #4 
Collar #4 
Projected Bottom 
ECRB-NICHE1620 #5 
Collar #5 
Projected Bottom 
ECRB-NICHE1620 #6 
Collar #6 
Projected Bottom 
Borehole Collar/Bottom Easting (m) 
170662.22 
170661.91 
170663.25 
170662.83 
170662.25 
170661.98 
170661.26 
170661.16 
170663.27 
170662.87 
170662.26 
170662.21 
170661.28 
170661.17 
ECRB-NICHE1620 #7 
Permeability was measured by air-injection tests conducted in boreholes #2, #3, and #5 (see 
Section 6.5.2). The tests were performed by isolating a 1 ft section of the boreholes using an 
inflatable packer system (DTN: LB0110AKN5POST.001 [156904]), and then injecting 
compressed air at a constant rate into the isolated injection interval. The pressure buildup in the 
injection interval and in nearby observation intervals was monitored with time until steady-state 
conditions were reached, which typically occurred within a few minutes. Air-permeability values 
were derived from the steady-state pressure data. For the purpose of air-injection tests, the 
MDL-NBS-HS-000004 REV02 
Collar #7 
Projected Bottom 
Elevation 
(m) 
Attachment V-12 
1108.99 
1109.14 
1110.99 
1111.61 
1111.00 
1111.29 
1111.04 
1111.57 
1111.42 
1113.25 
1111.44 
1113.58 
1111.47 
1113.27 
Depth (m) 
15.39 
16.02 
15.50 
15.02 
15.88 
16.00 
14.81 
Northing 
(m) 
233262.19 
233246.82 
233262.93 
233246.93 
233262.72 
233247.23 
233262.76 
233247.76 
233262.84 
233247.08 
233262.78 
233246.93 
233262.71 
233248.01 
Y (m) 
14.21 
13.49 
13.68 
13.63 
13.58 
13.62 
13.68 
X (m) 
0.04 
-0.98 
0.02 
1.01 
-1.00 
0.01 
0.99 
Z (m) 
3.08 
0.08 29.58 3.23 
5.08 
-0.83 29.48 5.70 
5.09 
0.02 29.17 5.38 
5.13 
0.85 28.62 5.66 
5.51 
-0.87 29.33 7.34 
5.53 
-0.21 29.47 7.67 
5.56 
0.84 28.37 7.36 
April 2003 
U0080 Seepage Calibration Model and Seepage Testing Data 
boreholes were named differently (borehole ECRB-NICHE1620 #5 was renamed as #0, ECRBNICHE1620 
#2 was renamed as #3, and ECRB-NICHE1620 #3 was renamed as #4). The 
locations of the air-injection test intervals were reported as distances in feet from the borehole 
collars. These distances were first converted to meters and then transformed to their correspond- 
X . ing Y . Z coordinates by the following elementary analytical geometry formulae: 
x + 
2 2 2 
where d is the midpoint of the test interval. The collar and projected endpoints of the borehole 
are denoted by ( ) x, y, z and ( ) x, y, z , respectively (see Table V-5 for coordinates of 
endpoints). The transformation of coordinates is shown in Table V-6. 
Table V-6. Locations of Air-Injection Test Intervals and Measured Air-Permeabilities 
DTN: LB0110AKN5POST.001 
BH k [m2] Midpoint 
[ft] 
End 
[ft] 
Start 
[ft] 
Midpoint 
[m] 
0 3 4 2.70E-12 3.5 1.07 
0 4 5 5.62E-12 4.5 1.37 
0 5 6 5.48E-09 5.5 1.68 
0 6 7 4.27E-09 6.5 1.98 
0 7 8 4.08E-12 7.5 2.29 
0 8 9 1.21E-11 8.5 2.59 
0 9 10 7.77E-12 9.5 2.90 
3.20 0 10 11 3.30E-12 10.5 
3.51 0 11 12 2.79E-11 11.5 
3.81 0 12 13 3.83E-11 12.5 
4.11 0 13 14 1.65E-10 13.5 
4.42 0 14 15 1.82E-10 14.5 
4.72 0 15 16 2.35E-11 15.5 
3 4 5 1.61E-11 4.5 1.37 -0.96 14.57 5.13 -10.7932 
3 5 6 3.18E-12 5.5 1.68 -0.96 14.87 5.14 -11.4976 
3 6 7 1.56E-11 6.5 1.98 -0.96 15.18 5.16 -10.8069 
Calculated 
Y [m] 
14.26 
14.56 
14.86 
15.16 
15.47 
15.77 
16.07 
16.38 
16.68 
16.98 
17.28 
17.59 
17.89 
X [m] 
-0.99 
-0.99 
-0.98 
-0.98 
-0.98 
-0.98 
-0.97 
-0.97 
-0.97 
-0.97 
-0.97 
-0.96 
-0.96 
Z [m] 
5.63 
5.66 
5.70 
5.73 
5.77 
5.80 
5.84 
5.87 
5.90 
5.94 
5.97 
6.01 
6.04 
Log(k [m2]) 
-11.5686 
-11.2503 
-8.2612 
-8.3696 
-11.3893 
-10.9172 
-11.1096 
-11.4815 
-10.5544 
-10.4168 
-9.7825 
-9.7399 
-10.6289 
d( ) y . y 
( ) + x . x +(y . y) (z . z) 
2 
d( ) z . z 
( ) + x . x +(y . y) (z . z)2 2 
MDL-NBS-HS-000004 REV02 
X = 
y + Y = 
d( ) x . x 
( ) + x . x +(y . y) (z . z) 
2 2 2 
Z = z + 
Attachment V-13 
(V-5) 
(V-6) 
(V-7) 
U0080 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
3.20 0.02 16.53 5.15 -12.9355 
3.51 0.02 16.83 5.15 -13.3125 
3.81 0.02 17.14 5.16 -12.2798 
4.11 0.02 17.44 5.17 -10.6576 
4.42 0.02 17.75 5.17 -10.4365 
4.72 0.02 18.05 5.18 -13.3170 
5.03 0.02 18.36 5.18 -12.2284 
5.33 0.02 18.66 5.19 -10.8729 
5.64 0.02 18.97 5.19 -10.4306 
5.94 0.02 19.27 5.20 -12.0762 
6.25 0.02 19.58 5.20 -11.6055 
6.55 0.02 19.88 5.21 -11.7399 
6.86 0.02 20.18 5.22 -12.7305 
7.16 0.02 20.49 5.22 -12.6326 
7.47 0.02 20.79 5.23 -11.5768 
7.77 0.02 21.10 5.23 -11.6696 
8.08 0.02 21.40 5.24 -12.6757 
8.38 0.02 21.71 5.24 -12.5302 
8.69 0.02 22.01 5.25 -10.1733 
8.99 0.02 22.32 5.25 -10.1630 
3 7 8 1.47E-12 7.5 2.29 -0.96 15.48 5.17 -11.8327 
3 8 9 4.08E-10 8.5 2.59 -0.95 15.79 5.18 -9.3893 
3 9 10 6.23E-10 9.5 2.90 -0.95 16.09 5.19 -9.2055 
3 10 11 6.24E-10 10.5 3.20 -0.95 16.40 5.20 -9.2048 
3 11 12 5.52E-10 11.5 3.51 -0.94 16.70 5.21 -9.2581 
3 12 13 1.19E-12 12.5 3.81 -0.94 17.01 5.22 -11.9245 
3 13 14 3.20E-11 13.5 4.11 -0.94 17.31 5.24 -10.4949 
3 14 15 3.23E-11 14.5 4.42 -0.94 17.61 5.25 -10.4908 
3 15 16 2.23E-12 15.5 4.72 -0.93 17.92 5.26 -11.6517 
3 16 17 4.03E-09 16.5 5.03 -0.93 18.22 5.27 -8.3947 
3 17 18 1.92E-09 17.5 5.33 -0.93 18.53 5.28 -8.7167 
4 3 4 5.85E-09 3.5 1.07 0.02 14.39 5.11 -8.2328 
4 4 5 9.51E-09 4.5 1.37 0.02 14.70 5.12 -8.0218 
4 5 6 9.32E-12 5.5 1.68 0.02 15.00 5.12 -11.0306 
4 6 7 8.85E-12 6.5 1.98 0.02 15.31 5.13 -11.0531 
4 7 8 9.68E-12 7.5 2.29 0.02 15.61 5.13 -11.0141 
4 8 9 4.16E-13 8.5 2.59 0.02 15.92 5.14 -12.3809 
4 9 10 1.87E-12 9.5 2.90 0.02 16.22 5.14 -11.7282 
4 10 11 1.16E-13 10.5 
4 11 12 4.87E-14 11.5 
4 12 13 5.25E-13 12.5 
4 13 14 2.20E-11 13.5 
4 14 15 3.66E-11 14.5 
4 15 16 4.82E-14 15.5 
4 16 17 5.91E-13 16.5 
4 17 18 1.34E-11 17.5 
4 18 19 3.71E-11 18.5 
4 19 20 8.39E-13 19.5 
4 20 21 2.48E-12 20.5 
4 21 22 1.82E-12 21.5 
4 22 23 1.86E-13 22.5 
4 23 24 2.33E-13 23.5 
4 24 25 2.65E-12 24.5 
4 25 26 2.14E-12 25.5 
4 26 27 2.11E-13 26.5 
4 27 28 2.95E-13 27.5 
4 28 29 6.71E-11 28.5 
4 29 30 6.87E-11 29.5 
April 2003 Attachment V-14 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
4 30 31 1.64E-11 30.5 9.30 0.02 22.62 5.26 -10.7852 
4 31 32 7.19E-12 31.5 9.60 0.02 22.93 5.27 -11.1433 
4 32 33 2.43E-12 32.5 9.91 0.02 23.23 5.27 -11.6144 
4 33 34 4.88E-13 33.5 10.21 0.02 23.54 5.28 -12.3116 
4 34 35 1.06E-12 34.5 10.52 0.02 23.84 5.28 -11.9747 
4 35 36 1.57E-12 35.5 10.82 0.02 24.15 5.29 -11.8041 
4 36 37 1.48E-10 36.5 11.13 0.02 24.45 5.29 -9.8297 
Dimensions [m] 
X X Y 
2.0 6.0 6.0 
2.0 8.0 8.0 
2.0 8.0 8.0 
V-3. Preparation of Meshes 
Multiple numerical meshes of a 2 m long section of the Niche 1620 were developed, each with a 
different statistical realization of the underlying heterogeneous permeability field. There were 
three test zones labeled as Niche1620a, Niche1620b, and Niche1620c. The locations and primary 
dimensions of these meshes are listed below in Table V-7. 
Table V-7. Primary Dimensions of Niche 1620 Meshes 
generate the mesh. 
Location of Test Zone 
Along Y-axis from ECRB 
MDL-NBS-HS-000004 REV02 
Centerline 
0.0 + 15.60 
0.0 + 19.60 
0.0 + 21.90 
The following mesh generation steps are performed. File names in the following steps refer to 
mesh of borehole #5 (28-29 ft). 
1. A mesh is generated with X-Y-Z dimensions as listed in Table V-7, discretized into regular 
gridblocks with side lengths of 0.1 m  0.1 m  0.1 m. The Y-axis is aligned with the Niche 
centerline. Figure V-5 shows the input file N5BH5_28-29ft and the command used to 
2. The mesh is shifted using software MoveMesh V1.0 (LBNL 2000 [152824]) to translate the 
origin of the mesh to the datum of Niche 1620. 
3. The GSLIB module SISIM V1.204 (LBNL 2000 [153100]) is executed to generate a random, 
spatially correlated field of log-permeability modifiers. For each realization, a new seed 
number is inserted into the SISIM V1.204 input file N5BH5_28-29ft_sisim.par (see Figure 
V-6). The generated permeability field is conditioned on measured air-permeability data 
provided in the file measured_log-k_12_N5.dat (see Figure V-7). Excerpt of the generated 
permeability field is shown in Figure V-8. 
4. The heterogeneous field of permeability modifiers is mapped onto the mesh using software 
Perm2Mesh V1.0 (LBNL 2000 [152826]). 
Attachment V-15 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
5. A niche is cut from the mesh with software CutDrift V1.0 (LBNL 2000 [152816]), using 
interpolated ceiling surface data given in Figure V-1. 
6. Left and right slots are cut from the mesh with software CutDrift V1.0 (LBNL 2000 
[152816]), using interpolated ceiling surface data given in Figure V-2 and Figure V-3. 
7. Software AddBound V1.0 (LBNL 2000 [152823]) is used to attach boundary elements at the 
top and bottom of the model domain. The bottom boundary gridblock is assigned to a special 
material domain (DRAIN) to allow specifying a free-drainage boundary condition. 
8. Gridblocks along the alignment of the injection boreholes are modified to represent 1 ft 
(0.3 m) long injection intervals and 3 ft (0.9 m) long packers on both sides of the injection 
interval. 
9. Drift elements (DRI78, DRI79, DRI88, DRI89, DRI98, and DRI99) are assigned a large 
volume so Dirichlet boundary conditions can be specified. Flux into the drift elements 
represents seepage. 
10. Six new evaporation elements (EVP78, EVP79, EVP88, EVP89, EVP98 and EVP99) are 
added and connected to the same formation elements as the drift elements. The nodal 
distance from the formation elements to the evaporation elements is set to the diffusive 
boundary-layer thickness. Flux into these elements represents evaporation. 
11. A single time step is performed using a generic TOUGH2 input onestep file (as input to 
iTOUGH2 V5.0; see Figure III-3) to test the mesh and to obtain cross-referencing information. 
The execution of the simulation is performed using file sh.onestep (Figure III-4) 
The steps 1-11 listed above were executed using file sh.N5BH5_28-29ft_mesh shown in Figure 
V-9. The script file sh.N5BH5_28-29ft_run (see Figure V-10) assigns new seed numbers for the 
generation of permeability field and generates multiple meshes by calling the script file 
sh.N5BH5_28-29ft_mesh. 
The final mesh is stored on file N5BH5_28-29ft.mesZ where Z, labels the realization of the 
underlying random permeability field. 
TOUGH2 input file for generating 3D grid for Niche 5 
MESHMAKER ----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
XYZ 
80 0.1000000 
20 0.1000000 
1 0.600E-10 
50 0.1000000 
1 0.600E-10 
NX 
NY 
NZ 
NZ 
NZ 
ENDFI ---1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
Figure V-5. Input file N5BH5_28-29ft used to generate primary mesh. 
MDL-NBS-HS-000004 REV02 April 2003 Attachment V-16 Seepage Calibration Model and Seepage Testing Data 
Parameters for SISIM 
******************** 
Niche 5 Borehole #5 (28-29 ft) 
TAG July 22, 2002 
START OF PARAMETERS: 
measured_log-k_12_N5.dat 
1 2 3 4 
-1.0e21 1.0e21 
-2.0 5.0 
1 2.5 
1 1.0 
4 2.5 
dummy.dat 
3 0 
direct.ik 
N5BH5_28-29ft_airK.dat 
2
N5BH5_28-29ft_airK.dbg 
0
59069 
1
80 -4.45 0.10 
20 20.95 0.10 
50 2.05 0.10 
1
0
2.0 
0.0 0.0 0.0 1.0 1.0 
0 20 
12 
0 2.5 
0
8
-0.725 0.066 1 0.02 
0.96 1.82 1
0.0 1.0 0.0 1.0 
0.02 
0.0 
-0.050 0.197 1
0.96 1.82 
0.0 1.0 
1
0.0 1.0 0.0 
0.625 0.443 1 0.02 
0.96 1.82 1
0.0 1.0 0.0 1.0 
0.02 
0.0 
1.300 0.623 1
0.96 1.82 
0.0 1.0 
1
0.0 1.0 0.0 
1.975 0.787 1 0.02 
0.96 1.82 1
0.0 1.0 0.0 1.0 
0.02 
0.0 
2.650 0.852 1
0.96 1.82 
0.0 1.0 
1
0.0 1.0 0.0 
3.325 0.918 1 0.02 
0.96 1.82 1
0.0 1.0 0.0 1.0 
0.02 
0.0 
4.000 0.999 1
0.96 1.82 
0.0 1.0 
1
0.0 1.0 0.0 
Figure V-6. Input file parameter file N5BH5_28-29ft_sisim.par for random permeability field 
generating software SISIM 
MDL-NBS-HS-000004 REV02 
U0080 
\column: x,y,z,vr 
\data trimming limits 
\minimum and maximum data value 
\lower tail option and parameter 
\middle option and parameter 
\upper tail option and parameter 
\tabulated values for classes 
\column for variable, weight 
\direct input of indicators 
\output file for simulation 
\debugging level: 0,1,2,3 
\output File for Debugging 
\0=standard order relation corr 
\random number seed 
\number of simulations 
ang1,ang2,ang3,anis1,2 
\0=two part search, 1=data-nodes 
\ max per octant(0 -> not used) 
\ maximum search radius 
\ sang1,sang2,sang3,sanis1,2 
\ min, max data for simulation 
\number simulated nodes to use 
\0=full IK, 1=med approx(cutoff) 
\0=SK, 1=OK 
\number cutoffs 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ ang1,ang2,ang3,anis1,2 
\cutoff, global cdf, nst, nugget 
\ it, aa, cc 
\ 
April 2003 Attachment V-17 U0080 Seepage Calibration Model and Seepage Testing Data 
N5-air K data 
4
x
y
z
log-k+12 
-0.98851 14.25626 5.63022 0.43136 
-0.98617 14.55911 5.66456 0.74974 
-0.98382 14.86196 5.69891 3.73878 
-0.98148 15.16481 5.73326 3.63043 
-0.97913 15.46766 5.76761 0.61066 
-0.97679 15.77051 5.80195 1.08279 
-0.97444 16.07336 5.83630 0.89042 
-0.97210 16.37621 5.87065 0.51851 
-0.96976 16.67906 5.90500 1.44560 
-0.96741 16.98191 5.93934 1.58320 
-0.96507 17.28476 5.97369 2.21748 
-0.96272 17.58761 6.00804 2.26007 
-0.96038 17.89046 6.04239 1.37107 
-0.96330 14.56905 5.13219 1.20683 
-0.96067 14.87362 5.14378 0.50243 
-0.95804 15.17818 5.15538 1.19312 
-0.95541 15.48275 5.16698 0.16732 
-0.95278 15.78732 5.17858 2.61066 
-0.95014 16.09189 5.19017 2.79449 
-0.94751 16.39645 5.20177 2.79518 
-0.94488 16.70102 5.21337 2.74194 
-0.94225 17.00559 5.22496 0.07555 
-0.93962 17.31016 5.23656 1.50515 
-0.93699 17.61473 5.24816 1.50920 
-0.93435 17.91929 5.25976 0.34830 
-0.93172 18.22386 5.27135 3.60531 
-0.92909 18.52843 5.28295 3.28330 
0.02101 14.39458 5.10953 3.76716 
0.02100 14.69933 5.11511 3.97818 
0.02100 15.00408 5.12069 0.96942 
0.02099 15.30883 5.12627 0.94694 
0.02098 15.61358 5.13185 0.98588 
0.02097 15.91833 5.13743 -0.38091 
0.02097 16.22307 5.14301 0.27184 
0.02096 16.52782 5.14859 -0.93554 
0.02095 16.83257 5.15417 -1.31247 
0.02095 17.13732 5.15975 -0.27984 
0.02094 17.44207 5.16533 1.34242 
0.02093 17.74682 5.17091 1.56348 
0.02092 18.05157 5.17649 -1.31695 
0.02092 18.35632 5.18207 -0.22841 
0.02091 18.66107 5.18765 1.12710 
0.02090 18.96581 5.19323 1.56937 
0.02089 19.27056 5.19881 -0.07624 
0.02089 19.57531 5.20439 0.39445 
0.02088 19.88006 5.20997 0.26007 
0.02087 20.18481 5.21555 -0.73049 
0.02087 20.48956 5.22113 -0.63264 
0.02086 20.79431 5.22671 0.42325 
0.02085 21.09906 5.23229 0.33041 
0.02084 21.40381 5.23787 -0.67572 
0.02084 21.70855 5.24345 -0.53018 
0.02083 22.01330 5.24903 1.82672 
0.02082 22.31805 5.25461 1.83696 
0.02081 22.62280 5.26019 1.21484 
0.02081 22.92755 5.26577 0.85673 
0.02080 23.23230 5.27135 0.38561 
0.02079 23.53705 5.27693 -0.31158 
0.02079 23.84180 5.28251 0.02531 
0.02078 24.14655 5.28809 0.19590 
0.02077 24.45129 5.29367 2.17026 
Figure V-7. Measured air-permeability data provided in file measured_log-k_12_N5.dat for 
conditioning the generated permeability field 
April 2003 Attachment V-18 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
variables = x y z var 
zone i= 80 j= 20 k= 50 
-0.4450000E+01 0.2095000E+02 0.2050000E+01 0.6853335E+00 
-0.4350000E+01 0.2095000E+02 0.2050000E+01 0.1218344E+01 
-0.4250000E+01 0.2095000E+02 0.2050000E+01 0.7149986E+00 
...
0.3250000E+01 0.2285000E+02 0.6950000E+01 0.2682163E+01 
0.3350000E+01 0.2285000E+02 0.6950000E+01 0.3089783E+01 
0.3450000E+01 0.2285000E+02 0.6950000E+01 0.2990684E+01 
Figure V-8. Excerpt from the generated permeability field 
modified from S. Finsterle, August 6, 1999, Version 1.1 
# general mesh 
# input mesh file 
# output mesh file 
# dy 
# dz 
# call program 
#! /bin/sh 
#
# Unix shell script file sh.N5BH5_28-29ft_mesh 
#
# Usage: sh.N5BH5_28-29ft_mesh 
#
# Generates TOUGH2 mesh N5BH5_28-29ft.mes 
# uses 
# airK_N5_3.dat 
# ceiling_N5_3.dat 
# leftbatwing_N5_3.dat 
# rightbatwing_N5_3.dat 
#
# TA Ghezzehei (Sept 10, 2002), Version 1.2 
#
#
#
echo 
echo ' Start shell script sh.N5BH5_28-29ft_mesh' 
echo ' mesh generator for Niche 5, BH5 (28-29ft)' 
echo '==========================================' 
echo 
#
echo 
echo 1. Generate 3d mesh 
echo -------------------- 
tough2 -mesh N5BH5_28-29ft 9 
#
echo 
echo 2. Center mesh 
echo -------------- 
xMoveMesh << eof 
N5BH5_28-29ft.mes 
temp01.mes 
-4.50 # dx 
20.90 N5_3 
7.00 
eof 
#
echo 
echo 3. Map correlated permeability field 
echo ------------------------------------ 
echo 
xPerm2Mesh << eof 
N5BH5_28-29ft_airK.dat 
temp01.mes 
temp02.mes 
2 # number of header lines in permeability field 
data 
April 2003 Attachment V-19 MDL-NBS-HS-000004 REV02 U0080 
# dimension of permeability field 
# TOUGH2 mesh is xyz 
# replace/add/multiply ?? 0 in past, doesn't 
# number of header lines 
# niche volume 
# nodal distance niche - wall 
# cosine multiplication factor 
# Xmin 
# Xmax 
# Ymin N5_3 
# Ymax N5_3 
# Zmin 
# Zmax 
# number of header lines 
# niche volume 
# nodal distance niche - wall 
# cosine multiplication factor 
# Xmin 
# Xmax 
# Ymin N5_3 
# Ymax N5_3 
# Zmin 
# Zmax 
Seepage Calibration Model and Seepage Testing Data 
3
3
1
fill now ?? 
hist_N5_3.tec 
0.1 # class size 
eof 
#
echo 
echo 4. Cut out main niche 
echo --------------------- 
xCutNiche1.2 << eof 
temp02.mes 
temp04.mes 
ceiling_N5_3.dat 
2
100.0 
1.0e-10 
1.0 
-2.00 
2.10 
20.80 
23.00 
0.0 
4.7 
eof 
#
# Replace all NIC98 and NIC99 elements to NIC88 and NIC89 
# main niche is now NIC78 and NIC79, while the left batwing 
# will be NIC98 and NIC99 (TA Ghezzehei June 19, 2002) 
#
echo 
echo 5. Replace NIC9* by NIC7* 
echo ------------------------- 
sed 's/NIC98/NIC78/g' temp04.mes | \ 
sed 's/NIC99/NIC79/g' > temp05.mes 
#
echo 
echo 6. Cut out left batwing 
echo ----------------------- 
xCutNiche1.2 << eof 
temp05.mes 
temp06.mes 
leftbatwing_N5_3.dat 
2
100.0 
1.0e-10 
1.0 
-4.10 
-1.90 
20.80 
23.00 
0.0 
3.6 
eof 
#
# Replace all NIC98 and NIC99 elements to NIC88 and NIC89 
# left batwing is now NIC88 and NIC89, while the right batwing 
# will be NIC98 and NIC99 (TA Ghezzehei, June 19, 2002) 
#
echo 
echo 7. Replace NIC9* by NIC8* 
echo ------------------------- 
April 2003 Attachment V-20 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
sed 's/NIC98/NIC88/g' temp06.mes | \ 
sed 's/NIC99/NIC89/g' > temp07.mes 
#
echo 
echo 8. Cut out right batwing 
echo ------------------------ 
xCutNiche1.2 << eof 
temp07.mes 
temp08.mes 
rightbatwing_N5_3b.dat 
2
100.0 
1.0e-10 
1.0 
2.20 
3.00 
20.80 
23.00 
0.0 
3.6 
eof 
#
echo 
echo 9. Add top boundary 
echo -------------------- 
xAddBound << eof 
temp08.mes 
temp09.mes 
TOP99 
BOUND 
1.5e-1 
1.0e-5 
-100.0 
100.0 
-100.0 
100.0 
7.00 
7.05 
eof 
#
echo 
echo 10. Add bottom boundary 
echo ----------------------- 
xAddBound << eof 
temp09.mes 
temp10.mes 
BOT99 
DRAIN 
-1.0 
1.0e-5 
-100.0 
100.0 
-100.0 
100.0 
1.95 
2.00 
eof 
#
# Delete Niche to Niche connections 
# that result from multiple cuttings 
# TAG June 18, 2002 
#
#
MDL-NBS-HS-000004 REV02 
U0080 
# number of header lines 
# niche volume 
# nodal distance niche - wall 
# cosine multiplication factor 
# Xmin 
# Xmax 
# Ymin N5_3 
# Ymax N5_3 
# Zmin 
# Zmax 
# input mesh file 
# output mesh file 
# boundary element name 
# boundary material type 
# boundary element volume 
# nodal distance to boundary element 
# xmin 
# xmax 
# ymin 
# ymax 
# zmin 
# zmax 
# input mesh file 
# output mesh file 
# boundary element name 
# boundary material type 
# boundary element volume 
# nodal distance to boundary element 
# xmin 
# xmax 
# ymin 
# ymax 
# zmin 
# zmax 
April 2003 Attachment V-21 Seepage Calibration Model and Seepage Testing Data 
.....0.1000E-02/A8136 
.....0.1000E-02/A8236 
.....0.1000E-02/A8336 
.....0.1000E-02/A8436 
.....0.1000E-02/A8536 
.....0.1000E-02/A8636 
.....0.1000E-02/A8736 
.....0.1000E-02/A7836 
.....0.1000E-02/A7936 
.....0.1000E-02/A7A36 
.....0.1000E-02/A7B36 
.....0.1000E-02/A7C36 
.....0.1000E-02/A7D36 
.....0.1000E-02/A7E36 
.....0.1000E-02/A7F36 
.....0.1000E-02/A6G36 
.....0.1000E-02/A6H36 
.....0.1000E-02/A6I36 
.....0.1000E-02/A6J36 
.....0.1000E-02/A6K36 
echo 
echo 11. Remove unnecessary connections 
echo ---------------------------------- 
grep -v NIC98NIC temp10.mes | \ 
grep -v NIC99NIC | \ 
grep -v NIC88NIC | \ 
grep -v NIC89NIC | \ 
grep -v NIC78NIC | \ 
grep -v NIC79NIC | \ 
grep -v NIC98BOT | \ 
grep -v NIC99BOT | \ 
grep -v NIC88BOT | \ 
grep -v NIC89BOT | \ 
grep -v NIC78BOT | \ 
grep -v NIC79BOT > temp11.mes 
#
echo 
echo 12. Add Packers/Boreholes and Change Connections 
echo ------------------------------------------------ 
echo 
sed 's/A8136 
sed 's/A8236 
sed 's/A8336 
sed 's/A8436 
sed 's/A8536 
sed 's/A8636 
sed 's/A8736 
sed 's/A7836 
sed 's/A7936 
sed 's/A7A36 
sed 's/A7B36 
sed 's/A7C36 
sed 's/A7D36 
sed 's/A7E36 
sed 's/A7F36 
sed 's/A6G36 
sed 's/A6H36 
sed 's/A6I36 
sed 's/A6J36 
sed 's/A6K36 
sed 's/A7935A7936.*/A7935A7936 
sed 's/A7A35A7A36.*/A7A35A7A36 
sed 's/A7B35A7B36.*/A7B35A7B36 
sed 's/A7936A7937.*/A7936A7937 
sed 's/A7A36A7A37.*/A7A36A7A37 
sed 's/A7B36A7B37.*/A7B36A7B37 
sed 's/A7836A7936.*/A7836A7936 
sed 's/A7B36A7C36.*/A7B36A7C36 
sed 's/A7936A8936.*/A7936A8936 
sed 's/A7A36A8A36.*/A7A36A8A36 
sed 's/A7B36A8B36.*/A7B36A8B36 
sed 's/A6936A7936.*/A6936A7936 
sed 's/A6A36A7A36.*/A6A36A7A36 
sed 's/A6B36A7B36.*/A6B36A7B36 
sed 's/A7144 
sed 's/A7244 
sed 's/A6344 
sed 's/A6444 
sed 's/A6544 
sed 's/A6644 
sed 's/A6744 
sed 's/A6844 
sed 's/A6944 
sed 's/A5A44 
sed 's/A5B44 
sed 's/A5C44 
sed 's/A5D44 
sed 's/A5E44 
sed 's/A5F44 
.....0.1000E-02/A7144 
.....0.1000E-02/A7244 
.....0.1000E-02/A6344 
.....0.1000E-02/A6444 
.....0.1000E-02/A6544 
.....0.1000E-02/A6644 
.....0.1000E-02/A6744 
.....0.1000E-02/A6844 
.....0.1000E-02/A6944 
.....0.1000E-02/A5A44 
.....0.1000E-02/A5B44 
.....0.1000E-02/A5C44 
.....0.1000E-02/A5D44 
.....0.1000E-02/A5E44 
.....0.1000E-02/A5F44 
Attachment V-22 MDL-NBS-HS-000004 REV02 
PACKE0.1000E-02/g' temp11.mes | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
BOREH0.1000E-02/g' | \ 
BOREH0.1000E-02/g' | \ 
BOREH0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
10.5000E-010.0000E-010.1000E-010.0000E+00 /g'| \ 
10.5000E-010.0000E-010.1000E-010.0000E+00 /g'| \ 
10.5000E-010.0000E-010.1000E-010.0000E+00 /g'| \ 
10.0000E-010.1000E-090.1000E-010.0000E+00 /g'| \ 
10.0000E-010.5000E-010.1000E-010.0000E+00 /g'| \ 
10.0000E-010.5000E-010.1000E-010.0000E+00 /g'| \ 
20.5000E-010.0000E-010.1000E-010.0000E+00 /g'| \ 
20.0000E-010.5000E-010.1000E-010.0000E+00 /g'| \ 
30.0000E-010.5000E-010.1000E-010.1000E+01 /g'| \ 
30.0000E-010.5000E-010.1000E-010.1000E+01 /g'| \ 
30.0000E-010.5000E-010.1000E-010.1000E+01 /g'| \ 
30.5000E-010.0000E-010.1000E-110.1000E+01 /g'| \ 
30.5000E-010.0000E-010.1000E-110.1000E+01 /g'| \ 
30.5000E-010.0000E-010.1000E-110.1000E+01 /g'| \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
BOREH0.1000E-02/g' | \ 
BOREH0.1000E-02/g' | \ 
BOREH0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
U0080 
April 2003 Seepage Calibration Model and Seepage Testing Data 
.....0.1000E-02/A5G44 
.....0.1000E-02/A5H44 
.....0.1000E-02/A4I44 
.....0.1000E-02/A4J44 
.....0.1000E-02/A4K44 
sed 's/A5G44 
sed 's/A5H44 
sed 's/A4I44 
sed 's/A4J44 
sed 's/A4K44 
sed 's/A5A43A5A44.*/A5A43A5A44 
sed 's/A5B43A5B44.*/A5B43A5B44 
sed 's/A5C43A5C44.*/A5C43A5C44 
sed 's/A5A44A5A45.*/A5A44A5A45 
sed 's/A5B44A5B45.*/A5B44A5B45 
sed 's/A5C44A5C45.*/A5C44A5C45 
sed 's/A5944A5A44.*/A5944A5A44 
sed 's/A5C44A5D44.*/A5C44A5D44 
sed 's/A5A44A6A44.*/A5A44A6A44 
sed 's/A5B44A6B44.*/A5B44A6B44 
sed 's/A5C44A6C44.*/A5C44A6C44 
sed 's/A4A44A5A44.*/A4A44A5A44 
sed 's/A4B44A5B44.*/A4B44A5B44 
sed 's/A4C44A5C44.*/A4C44A5C44 
> temp12.mes 
#
echo 
echo 13. Edit volume of niche elements 
echo --------------------------------- 
sed 's/NICHE........../NICHE0.5000E+52/g' temp12.mes > temp13.mes 
#
#
echo 
echo 14. Add evaporation elements 
echo ---------------------------- 
cat temp13.mes | sed -n '1,/BOT99/p' > eleme 
cat temp13.mes | sed -n '/TOP99A21 1/,$p' > conne 
grep NIC temp13.mes | sed 's/NIC/EVP/' | sed 's/NICHE/EVAPP/' > elemeconne 
grep EVAPP elemeconne >> eleme 
cat << eof >> eleme 
CONNE 
eof 
grep -v EVAPP elemeconne | \ 
sed 's/EVP\(.......\).*0.1000E-090.5000E-01\(..........\).*$/EVP\1 
/' > temp14.mes 
-170.1000E-170.2000E-01\2/' >> eleme 
cat eleme conne | sed 's/+++/ 
#sh.onestep temp14.mes 
#
echo 
echo 15. Remove unnecessary files 
echo ---------------------------- 
echo 
mv temp14.mes N5BH5_28-29ft.mes 
rm temp*.* 
rm hist* 
rm t2.msg 
rm fort* 
rm *airK.dbg 
echo 
echo sh.N5BH5_28-29ft_mesh terminated 
echo ================================ 
Figure V-9. File sh.N5BH5_28-29ft_mesh used to execute Mesh Generation Steps 111 
Attachment V-23 MDL-NBS-HS-000004 REV02 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
PACKE0.1000E-02/g' | \ 
U0080 
PACKE0.1000E-02/g' | \ 
10.1000E-090.0000E-010.1000E-010.0000E+00 /g'| \ 
10.5000E-010.0000E-010.1000E-010.0000E+00 /g'| \ 
10.5000E-010.0000E-010.1000E-010.0000E+00 /g'| \ 
10.0000E-010.5000E-010.1000E-010.0000E+00 /g'| \ 
10.0000E-010.5000E-010.1000E-010.0000E+00 /g'| \ 
10.0000E-010.5000E-010.1000E-010.0000E+00 /g'| \ 
20.5000E-010.0000E-010.1000E-010.0000E+00 /g'| \ 
20.0000E-010.5000E-010.1000E-010.0000E+00 /g'| \ 
30.0000E-010.5000E-010.1000E-010.1000E+01 /g'| \ 
30.0000E-010.5000E-010.1000E-010.1000E+01 /g'| \ 
30.0000E-010.5000E-010.1000E-010.1000E+01 /g'| \ 
30.5000E-010.0000E-010.1000E-110.1000E+01 /g'| \ 
30.5000E-010.0000E-010.1000E-110.1000E+01 /g'| \ 
30.5000E-010.0000E-010.1000E-110.1000E+01 /g' \ 
\ 
April 2003 #
# sh.N5BH5_28-29ft_run 
#
#
# Unix script to perform multiple inversions of seepage data 
# using multiple realizations of permeability field. 
# Niche5, Borehole 5 (28-29ft) 
#
# uses 
# airK_N5_3.par 
# ceiling_N5_3.dat 
# leftbatwing_N5_3.dat 
# rightbatwing_N5_3b.dat 
#
# TA Ghezzehei 09/09/2002 
# Adapated from S. Finsterle, V1.0, 8/20/02 
#
runs=10 
clear 
#
echo Copy air-K and Niche ceiling survey data 
echo 
#
echo 'Generate meshes for multiple calibrations of seepage test in Niche 5 (Borehole 
5, 28-29ft)' 
echo " " 
i=0 
j=0 
while test $j -lt $runs 
do 
# calculate new seed number 
j=`expr $j + 1` 
i=`expr $j + $j` 
i=`expr $i + 59067` 
echo " " 
echo "============================================================================" 
echo "Run $j of $runs" 
echo "============================================================================" 
echo "Create permeability modifier field, seed number: $i" 
cat N5BH5_28-29ft_sisim.par | sed "s/^.*seed/$i 
U0080 Seepage Calibration Model and Seepage Testing Data 
\\\seed/" \ 
> N5BH5_28-29ft_sisim.par$j 
xSisim << eof 
N5BH5_28-29ft_sisim.par$j 
eof 
cp N5BH5_28-29ft_airK.dat N5BH5_28-29ft_airK.dat$j 
# 
echo `date`: Mesh generation 
sh.N5BH5_28-29ft_mesh 
cp N5BH5_28-29ft.mes N5BH5_28-29ft.mes$j 
#
done 
#
echo remove unnecessary files 
echo 
rm N5BH5_28-29ft_sisim.par 
#
echo sh.N5BH5_28-29ft_run terminated 
echo =============================== 
Figure V-10. Script file sh.N5BH5_28-29ft_run used to multiple meshes with different permeability 
field realizations 
Attachment V-24 MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
ATTACHMENT VI 
PREPARATION OF SEEPAGE RATE AND RELATIVE-HUMIDITY DATA FOR THE 
Col. 7=(RC[-3]-R[-1]C[-3])/(RC[-2]-R[-1]C[-2])*60 
SIMULATION OF LIQUID-RELEASE TESTS IN THE ECRB CROSS DRIFT 
Measured data from the liquid-release tests performed in the ECRB were submitted to the TDMS 
under various DTNs. The SCM is calibrated against seepage-rate data, taking into account 
evaporation effects, which are driven by relative humidity changes. Time series of seepage rates 
and relative-humidity data were extracted from the respective DTNs using the steps described in 
this Attachment. The procedure is outlined in detail for the liquid-release tests conducted in 
zone 2 of borehole SYBT-ECRB-LA#1 (DTN: LB0110ECRBLIQR.002 [156879]); similar 
procedures were applied for other liquid-release tests (see Wang 2003 [161456], SN-LBNL-SCI- 
228-V1, pp. 9, 1821, 26). 
1. DTN: LB0110ECRBLIQR.002 [156879] was obtained from the TDMS. 
2. Data are stored in four archive files (s01221_001.zip, s01221_002.zip, s01221_003.zip, and 
s01221_004.zip). Four text files (zz_sep_193257.txt, zz_sep_193258.txt, zz_sep_193259.txt, 
and zz_sep_193261.txt) were extracted from the archive files using WinZip 8.0. The four text 
files contain four data reports labeled s01221_001, s01221_002, s01221_003, and 
s01221_004, respectively. 
For the preparation of a calibration file with seepage-rate data, the following steps are 
performed: 
1. Concatenate zz_sep_193261.txt and zz_sep_193259.txt; new file name: Cum.txt. 
2. Open Cum.txt using the text editor vim 6.0.12. 
3. Delete header lines. 
4. Replace all slashes (except those in dates) with spaces to separate the data columns. 
5. Save file Cum.txt and exit vim. 
6. Open file Cum.txt in Excel 2000 (9.0.3821 SR-1) such that Column 1 holds the date and time, 
Column 2 holds the cumulative injection, Column 3 holds cumulative return flow, and 
Column 4 holds cumulative seepage. 
7. Translate date to seconds after 2/28/2001, 13:59: 
Col. 5 = (RC[-4]-2/28/2001 13:59)*86400 
8. Calculate release rate [ml/min] from cumulative injection [ml] and cumulative return [ml]: 
Col. 6=((RC[-4]-R[-1]C[-4])-(RC[-3]-R[-1]C[-3]))/(RC[-1]-R[-1]C[-1])*60 
9. Calculate seepage rate [ml/min] from cumulative seepage [ml]: 
April 2003 Attachment VI-1 MDL-NBS-HS-000004 REV02 U0080 Seepage Calibration Model and Seepage Testing Data 
10. Save as Microsoft Excel Workbook Cum.xls (for traceability only) and as space delimited 
text file Cum.prn. 
11. Open Cum.prn using text editor vim. 
12. Delete all columns except time [sec] and seepage rate [ml/min]. 
13. Add header: 
Seepage rate 
[ml/min] 
Time [sec] since 
02/28/01 13:59:00 
14. Save as LA1_zone2_set2.dat (see excerpt in Figure VI-1). This file will be read as a calibration 
data file by iTOUGH2 V5.0 (LBNL 2002 [160106]). 
[ml/min] 
0.00 
11.26 
0.00 
-0.07 
-0.07 
0.00 
..... 
5.44 
0.00 
Time [sec] since Seepage rate 
02/28/01 13:59:00 
0.0 
1200.0 
2400.0 
3600.0 
4800.0 
6000.0 
......... 
5241780.0 
5242980.0 
5244180.0 
5245380.0 
5246580.0 
-0.86 
-0.73 
-0.62 
Col. 2 = (RC[-1]-2/28/2001 13:46)*86400 
Figure VI-1. Excerpt from calibration data file LA2_zone1_set2.dat 
For the preparation of a boundary condition file with relative-humidity data, the following steps 
are performed: 
15. Concatenate zz_sep_193258.txt and zz_sep_193257.txt; new file name: RH.txt. 
16. Open RH.txt using the text editor vim. 
17. Delete header lines. 
18. Delete all columns except date, time and inside RH. 
19. Append E-02 to RH column to convert from [%] to dimensionless fraction. 
20. Save RH.txt and exit vim. 
21. Open RH.txt in Excel. 
22. Add new Column 2. 
23. Translate date and time to seconds after 2/28/01 13:46: 
Attachment VI-2 MDL-NBS-HS-000004 REV02 April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
24. Save as space delimited text file RH.txt. 
25. Open RH.txt using text editor vim. 
26. Delete columns with date and time. 
27. Add first dummy data point (-1E20, 0.190) to provide historic relative humidity. 
28. Add last dummy data point (1E20, 0.252) to cover potential prediction time frame. 
29. Duplicate all 4141 lines twice. 
30. Add 4141 2 to top of file. 
31. Remove second column from Line 2 to Line 4142. 
32. Remove first column from Line 4143 to end of file. 
33. Add EVA98, Line 4143. 
34. Add EVA99, Line 8285. 
35. Save as LA1_zone2_set2.bc. This file is supplied as time dependent boundary condition file 
to iTOUGH2 V5.0 (LBNL 2002 [160106]). An excerpt is shown in Figure VI-2. 
4141 2 
-1.0E20 
0.0 
1200.0 
2400.0 
......... 
5245380.0 
5246580.0 
5247780.0 
1.0E20 
EVA98 
0.190 
0.190 
0.190 
0.188 
..... 
0.275 
0.260 
0.252 
0.252 
EVA99 
0.190 
0.190 
0.190 
0.188 
..... 
0.275 
0.260 
0.252 
0.252 
Figure VI-2. Excerpt from boundary condition data file LA2_zone1_set2.bc 
April 2003 Attachment VI-3 MDL-NBS-HS-000004 REV02 Seepage Calibration Model and Seepage Testing Data 
INTENTIONALLY LEFT BLANK 
Attachment VI-4 MDL-NBS-HS-000004 REV02 
U0080 
April 2003 U0080 Seepage Calibration Model and Seepage Testing Data 
ATTACHMENT VII 
noruns=1 
else
noruns=$4 
EXECUTION OF MULTIPLE INVERSIONS OF DATA FROM ECRB 
Multiple inversions of seepage-rate data from the systematic testing area in the ECRB Cross 
Drift were performed, based on multiple realizations of the underlying permeability field. The 
following steps are performed (see also file sh.run, Figure VII-1): 
1. Go to the appropriate subdirectory /LAx/ZoneY/SetZ, where x indicates the borehole 
number, Y represents the injection zone, and Z designates the data set number (if multiple test 
sequences were performed in the same interval). 
2. Select the appropriate mesh corresponding to the permeability field realization j. 
3. Perform a steady-state simulation with background percolation, neglecting evaporation 
effects (vapor diffusion coefficient is set to zero). A representative TOUGH2 input file (as 
input to iTOUGH2 V5.0) LAx_zoneY_ininoevap is reproduced in Figure VII-2. 
4. Take saturation distribution from previous simulation as initial conditions for a simulation 
with evaporation effects added (vapor diffusion coefficient at standard conditions is set to 
2.1310-5 m2/s). A dry-out zone develops around the drift. 
5. Take saturation distribution from previous simulation as initial conditions for the inversion. 
A representative TOUGH2 input file LAx_zoneY_setZ (as input to iTOUGH2 V5.0) is shown 
in Figure VII-3; an excerpt from a representative iTOUGH2 V5.0 input file LAx_zoneY_setZi 
is shown in Figure VII-4. 
6. Figure VII-5 contains an excerpt from a representative iTOUGH2 V5.0 output file 
LAx_zoneY_setZi.out, showing the best estimate parameter value obtained from a single 
inversion. 
#! /bin/sh 
#
# sh.run LA ZONE SET [RUNS] [START] [NODE] 
#
# LA = Borehole number 
# ZONE = Zone number 
# SET = Test set number 
# RUNS = Number of inversions 
# START= Starting number of inversion 
# NODE = Node number 
#
# Perform multiple inversions of seepage data 
# using multiple realizations of permeability field. 
#
# S. Finsterle, 9/09/02 
#
cd $HOME/ym/Seepage/ST/LA$1/Zone$2/Set$3 
#
if test "$4" = "" 
then 
Attachment VII-1 MDL-NBS-HS-000004 REV02 April 2003 Seepage Calibration Model and Seepage Testing Data 
fi 
if test "$5" = "" 
then
j=1 
else 
fi 
if test "$6" = "" 
then
node=" " 
else 
fi 
echo "Date :" `date` 
echo "Directory :" `pwd` 
echo "Borehole 
echo "Zone :" $2 
echo "Test set :" $3 
echo "Number of runs :" $noruns 
echo "First run :" $j 
echo "Master node :" $node 
#
runs=`expr $noruns + $j - 1` 
#
while test $j -le $runs 
do 
#
#
#
#
#
#
#
done 
echo 
echo Run completed: `date` 
echo ===================== 
j=$5 
node="-node node$6"
:" SYBT-ECRB-LA#$1 
echo `date`: Create initial conditions without evaporation 
tough2 -v 5.0 $node -m ../LA$1_zone$2.mes$j LA$1_zone$2_ininoevap 9 
| sed 's/+++/ 
echo `date`: Create initial conditions with dry-out zone 
itough2 -v 5.0 $node -m ../LA$1_zone$2.mes$j -i LA$1_zone$2_inievap_$$.inc \ 
inievapi LA$1_zone$2_inievap 9 
echo `date`: Invert seepage-rate data 
itough2 -v 5.0 $node -m ../LA$1_zone$2.mes$j -i LA$1_zone$2_$$.inc \ 
-tvsp LA$1_zone$2_set$3.bc -ito LA$1_zone$2_set$3i.out$j 
LA$1_zone$2_set$3i LA$1_zone$2_set$3 9 
j=`expr $j + 1` 
Figure VII-1. File sh.run to execute multiple inversions 
MDL-NBS-HS-000004 REV02 
/' > LA$1_zone$2_inievap_$$.inc 
U0080 
echo " " 
echo "============================================================================" 
echo "Run $j of $runs" 
echo "============================================================================" 
echo `date`: Take steady-state conditions as initial conditions for subsequent run 
cat LA$1_zone$2_ininoevap.sav | sed 's/EVA\(..\).*$/EVA\1/' \ 
echo `date`: Take steady-state conditions as initial conditions for subsequent run 
cat LA$1_zone$2_inievap.sav | sed 's/+++/ /' > LA$1_zone$2_$$.inc
\ 
April 2003 Attachment VII-2 Seepage Calibration Model and Seepage Testing Data 
LAx_zoneY_ininoevap: Create initial conditions (no evaporation) 
ROCKS----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
2650. 2 FRACT 
0.01 
2.57 
2650. 
2650. 
0
2 
11 
11 
DRIFT 
EVAPO 
0.900E+00 3 
2650. 
2650. 
2650. 
0
0
0 
19 
BOREH 
BOUND 
DRAIN 
RPCAP----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
3 0.095 
0.00 1 1.00 
PARAM----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
100100000100021000400004000 0.00E-05 8-2 150 
-1.000E+12 
1.000E-04 
0.01 
SOLVR----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
5 Z0 O0 2.500E-03 1.000E-06 
GENER----1----*----2----*----3----*-- 13.6 mm/year ---*----6----*----7----*----8 
TOP99INF 0 COM1 6.3700E-06 
START----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
INDOM----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
EVAPO 
0.300 
FRACT 
0.015 
DRIFT 
0.001 
ENDCY----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
Figure VII-2. Representative TOUGH2 input file LAx_zoneY_ininoevap (as input to iTOUGH2 V5.0) 
to execute initial steady- state simulation without evaporation effects 
.0096 2.640E-11 2.640E-11 2.640E-11 
500.0 
0.9999 1.000E-08 1.000E-08 1.000E-08 
0.9999 1.000E-08 1.000E-08 1.000E-08 
1.0 
.5000 1.000E-08 1.000E-08 1.000E-08 
.9900 1.000E-08 1.000E-08 1.000E-08 
.9900 1.000E-08 1.000E-08 1.000E-08 
0.00 
1.000E+03
0 
MDL-NBS-HS-000004 REV02 
1.80 
9.81 
Attachment VII-3 
U0080 
1000. 
-1000. 
-1000. 
1000. 
-1000. 
-1000. 
April 2003 Seepage Calibration Model and Seepage Testing Data 
2 
LAx_zoneY_setZ: simulates liquid-release test in borehole x, zone Y, set Z 
TIMBC----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
ROCKS----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
FRACT 2650. .0096 2.640E-11 2.640E-11 2.640E-11 -1000. 
0.00 
500.0 
0.01 
2.57 
0.9999 1.000E-08 1.000E-08 1.000E-08 
1.0000 1.000E-08 1.000E-08 1.000E-08 
2650. 
2650. 
0
2 
11 
11 
DRIFT 
EVAPO 
0.900E+00 0.000E+00 3 
.5000 1.000E-08 1.000E-08 1.000E-08 
.9900 1.000E-08 1.000E-08 1.000E-08 
2650. 
2650. 
.9900 1.000E-08 1.000E-08 1.000E-08 
20.0000 1.000E+03 1.000E-03 4.400E-10 
2650. 
1.0E5 
0
0
0
0 
19 
BOREH 
BOUND 
DRAIN 
rEFCO 
RPCAP----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
3 0.01 
0.00 0.00 1 1.00 
PARAM----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
9000100000100020000400005000 2.13E-05 6-29000 
-1.7200E+5 1.000E+04 
1.000E-04 
0.01 
10 
MOMOP----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
2
SOLVR----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
5 Z0 O0 2.500E-03 1.000E-06 
GENER----1----*----2----*----3----*-- 13.6 mm/year ---*----6----*----7----*----8 
TOP99INF 0 0 COM1 6.3700E-06 
BOR 0INJ 2 COM1 
0.0 
2993032.0 
-1.0E+50 
2984607.0 
1.0E50 
0.0 2.625000E-04 2.873900E-04 
3387587.0 
0.0 
0.0 2.909100E-04 2.967000E-04 
0.0 
0.0 
0.0 
ENDCY----1----*----2----*----3----*----4----*----5----*----6----*----7----*----8 
Figure VII-3. Representative TOUGH2 input file LAx_zoneY_setZ (as input to iTOUGH2 V5.0) used 
to simulate liquid release test, solving the forward problem 
1.0 
10.00 
3018835.0 
MDL-NBS-HS-000004 REV02 
U0080 
1000. 
-1000. 
-1000. 
-1000. 
-1000. 
-1000. 
1.80 
9.81 
2958968.0 
3361935.0 
April 2003 Attachment VII-4 U0080 Seepage Calibration Model and Seepage Testing Data 
Generic command: 
itough2 -v 5.0 -m LAx_zoneY.mesj -i LAx_zoneY.inc -tvsp LAx_zoneY_setZ.bc \ 
LAx_zoneY_setZi LAx_zoneY_setZ 9 
> parameters 
>> capillary pressure 
>>> material: FRACT 
>>>> annotation: log(1/alpha) 
>>>> index: 2 
>>>> step: 0.2 
>>>> logarithm 
>>>> variation: 1.0 
<<<< 
<<< 
<< 
> observation 
>> time: 275 equally spaced 
1.44E4 3.96E6 
>> liquid flow rate 
>>> connections: DRI99 BL1_1 DRI99 D21_1 DRI99 BL2_1 DRI99 D22_1 & 
DRI99 D23_1 DRI99 BL4_1 DRI99 D24_1 DRI99 BL5_1 & 
..... ..... ..... ..... ..... ..... ..... ..... & 
DRI98 CAC26 DRI98 CBC26 DRI98 CCC26 DRI98 CDC26 & 
DRI98 CFC26 DRI98 CGC26 DRI98 CHC26 DRI98 CIC26 
>>>> factor: 8.3333E-6 (ml/min -- kg/sec; divide by 2 for symmetry) 
>>>> header: 2 
>>>> data file: LAx_zoneY_setZ.dat 
>>>> deviation: 0.1 
<<<< 
<<< 
<< 
> computation 
>> stop 
>>> ignore WARNINGS 
>>> uphill: 6 
>>> iterations: 6 
<<< 
>> jacobian 
>>> perturb: 0.2 % 
<<< 
<< 
< 
Figure VII-4. Excerpt from representative iTOUGH2 input file LAx_zoneY_set2i used to solve the 
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! 
ESTIMATED PARAMETER V/L/F ROCKS PAR INITIAL GUESS BEST ESTIMATE STANDARD DEVIATION 
log(1/alpha) LOG10 FRACT 2 0.26990E+01 0.26758E+01 0.164E-02 
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! 
Figure VII-5. Reformatted excerpt from representative iTOUGH2 output file LAx_zoneY_set2i.out 
inverse problem 
showing estimated parameter 
April 2003 Attachment VII-5 MDL-NBS-HS-000004 REV02