Analysis of Hydrologic Properties Data REV 00

ANL-NBS-HS-000042

October 2004 


1. PURPOSE 
This analysis report describes the methods used to determine hydrologic properties based on the 
available field data from the unsaturated zone (UZ) at Yucca Mountain, Nevada. The technical 
scope, content, and management of this analysis report are described in the planning document 
Technical Work Plan for: Unsaturated Zone Flow Analysis and Model Report Integration (BSC 
2004 [DIRS 169654], Sections 2, 4, and 8). Fracture and matrix properties are developed by 
analyzing available survey data from the Exploratory Studies Facility (ESF), the Enhanced 
Characterization of Repository Block (ECRB) Cross-Drift, and/or boreholes; air-injection testing 
data from surface boreholes and from boreholes in the ESF; and data from laboratory testing of 
core samples. In addition, the report Geologic Framework Model (GFM2000) (BSC 2004 
[DIRS 170029]) also serves as a source report by providing the geological framework model of 
the site. This report is a revision of the model report under the same title (BSC 2003 [DIRS 
161773]), which in turn superceded the analysis report under the same title (BSC 2001 [DIRS 
159725]). 
The principal purpose of this work is to provide representative uncalibrated estimates of fracture 
and matrix properties for use in the model report Calibrated Properties Model. The term 
uncalibrated is used to distingush the properties or parameters estimated in this report from 
those obtained from the inversion modeling used in Calibrated Properties Model. The present 
work also provides fracture geometry properties for generating dual-permeability grids as 
documented in the scientific analyses report, Development of Numerical Grids for UZ Flow and 
Transport Modeling. 
The following reports also use the output (hydrologic properties of tuffs) of this report as direct 
input: 
 Multiscale Thermohydrologic Model 
 Drift-Scale THC Seepage Model 
 Seepage Calibration Model and Seepage Testing Data 
 UZ Flow Models and Submodels 
 Mountain-Scale Coupled Processes 
 Drift-Scale Radionuclide Transport 
 Drift Scale THM Model 
 Particle Tracking Model and Abstraction of Transport Process. 
The fracture, matrix, and fault properties developed in this report include: 
 Fracture properties (frequency, permeability, van Genuchten a and m parameters, 
aperture, porosity, and interface area) for each UZ Model layer 
 Matrix properties (porosity, permeability, and van Genuchten aand m parameters) for 
each UZ Model layer 
 Fault properties for each major hydrogeologic unit (TCw, PTn, TSw, and CHn/CFu, as 
defined in Table 6-1). 
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Analysis of Hydrologic Properties Data 
These properties incorporate the available measurement data, as applicable. 
A list of relevant features, events, and processes (FEPs) is presented in Section 6. 
Constraints and limitations are as follows: the fracture permeability, van Genuchten fracture a 
and m, matrix permeability, and van Genuchten matrix a and m reported here are not calibrated 
to the real system, the UZ. The parameters developed in this report are subject to additional 
uncertainty because of a lack of measured data for certain rock layers. Therefore, they should be 
used only after careful evaluation. At least some degree of calibration of the numerical model 
against measured data of a given system is required. In many cases, the values obtained from 
this report serve as good initial estimates in the Calibrated Properties Model of the UZ. 
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Analysis of Hydrologic Properties Data 
2. QUALITY ASSURANCE 
Development of this analysis report has been determined to be subject to the Yucca Mountain 
Projects quality assurance (QA) program as indicated in Technical Work Plan for: Unsaturated 
Zone Flow Analysis and Model Report Integration (BSC 2004 [DIRS 169654], Section 8.1). 
Approved QA procedures identified in the technical work plan (BSC 2004 [DIRS 169654], 
Section 4) have been used to conduct and document the activities described in this analysis 
report. The TWP also identifies the methods used to control the electronic management of data 
(BSC 2004 [DIRS 169654], Section 8.4) during the modeling and documentation activities. 
This analysis report provides uncalibrated values for hydrologic properties of identified natural 
barriers that are classified in the Q-List (BSC 2004 [DIRS 168361]) as Safety Category, 
because they are important to waste isolation, as defined in AP-2.22Q, Classification Analyses 
and Maintenance of the Q-List. The report contributes to the analysis and modeling data used to 
support the Total System Performance Assessment (TSPA). The conclusions of this analysis 
report do not affect the repository design or engineered features important to safety, as defined in 
AP-2.22Q. 
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3. USE OF SOFTWARE 
No software is used in this study except for standard Excel spreadsheets and visual display 
graphics programs (Excel 97 SR-1 and Tecplot V7.0), which are not subject to software quality 
assurance requirements. All information needed to reproduce the work using these standard 
software programs is included in this report, with references specified (See Appendix A). Names 
of files based on these programs are given in Section 6. (Excel files involving computations are 
specified in Sections 6.1 and 6.2.) A detailed description of these files is presented in 
Appendix A. 
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4. INPUTS 
Fracture properties are developed based on available fracture survey data from the ESF, ECRB 
Cross-Drift, and boreholes and air-injection testing data from vertical boreholes and ESF 
alcoves. Matrix properties are determined by combining core and small-scale matrix property 
data. Properties are determined by computing means, standard deviations, and standard errors 
for each UZ Model layer (BSC 2004 [DIRS 169855]) for each property. Fracture porosities are 
determined based on the analyses of gas tracer data from the ESF. When no data for a specific 
layer are available, analogs are identified and used to assign properties. The data used in this 
report are appropriate for this study because they are site-specific data from the UZ at Yucca 
Mountain. The appropriateness of the data is also discussed in Section 6 when they are used for 
developing UZ properties. 
4.1 DIRECT INPUTS 
The input data used in property-set development include the following: 
 Previously developed fracture properties (i.e., Fracture frequency, interface area, and the 
van Genuchten m) based on the fracture data (including spatially varying frequency, 
length, dips, and strikes) from the detailed line survey (DLS) along drifts and the 
fracture frequency data from boreholes (DTN: LB990501233129.001 [DIRS 106787]). 
This data set is the technical product output (TPO) of a superseded document [historical 
TPO, Analysis of Hydrologic Properties Data (BSC 2001 [DIRS 159725])]. The use of 
these fracture property data can be justified as follows (according to the criteria stated in 
AP-SIII.9Q): 
 The source is reliable because (1) the data set was qualified previously; (2) the 
approaches used to generate these data are defensible and well documented (see 
Section 6.1.2); and (3) the Input sources to the historical TPO are also qualified. The 
DTNs of the related input sources to this historical TPO are as follows: 
GS960708314224.008 [DIRS 105617] 
GS960708314224.010 [DIRS 106031] 
GS960808314224.011 [DIRS 106029] 
GS960908314224.014 [DIRS 106033] 
GS960908314224.018 [DIRS 106067] 
GS960908314224.020 [DIRS 106059] 
GS970308314222.001 [DIRS 106075] 
GS970808314224.008 [DIRS 106049] 
GS970808314224.010 [DIRS 106050] 
GS970808314224.012 [DIRS 106057] 
GS970808314224.014 [DIRS 106069] 
GS971108314224.020 [DIRS 105561] 
GS971108314224.021 [DIRS 106007] 
GS971108314224.022 [DIRS 106009] 
GS971108314224.023 [DIRS 106010] 
GS971108314224.024 [DIRS 106023] 
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Analysis of Hydrologic Properties Data 
GS971108314224.025 [DIRS 106025] 
GS971108314224.026 [DIRS 106032] 
GS971108314224.028 [DIRS 106047] 
GS981108314224.005 [DIRS 109070] 
GS990408314224.001 [DIRS 108396] 
GS990408314224.002 [DIRS 105625] 
TM000000SD12RS.012 [DIRS 105627] 
 These data were generated by a highly qualified organization, Lawrence Berkeley 
National Laboratory. 
 These data were used in previous site recommendation documents (e.g., BSC 2004 
[DIRS 169855]) and peer-reviewed journal papers (e.g., Wu et al. 2002 
[DIRS 160195]). 
 The sole reason for superseding the report is to include new technical content (i.e., the 
validation activities of the Active Fracture Model). 
 Air-injection testing data (from vertical boreholes) used for fracture permeability 
estimates (DTNs: GS960908312232.013 [DIRS 105574] through LB980120123142.005 
[DIRS 114134] in Table 4-1). 
 Air-injection and/or gas tracer data from the Upper Tiva Canyon, Bow Ridge fault, and 
Upper Paintbrush contact alcoves, the Single Heater Test (SHT) area, and the Drift 
Scale Test (DST) area used for fracture permeability and porosity 
estimates (DTNs: LB980912332245.002 [DIRS 105593] and GS990883122410.002 
[DIRS 135230]). 
 Measured properties (including effective porosity, bulk density, porosity, particle 
density, hydraulic conductivity, matrix van Genuchten a and m values, and residual 
saturation) and field variables (including volumetric water content, saturation, and water 
potential) from core samples, as well as stratigraphic descriptions for samples from 
boreholes used for developing matrix properties for UZ model layers 
(DTNs: MO0109HYMXPROP.001 [DIRS 155989] through GS940208314211.008 
[DIRS 145581] in Table 4-1). 
Specific input data sets and the associated Data Tracking Numbers (DTNs) are provided in 
Table 4-1. Equations that are direct input are discussed in the context of model development 
in Section 6 with appropriate citations to their sources. 
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Analysis of Hydrologic Properties Data 
Table 4-1. Data Tracking Numbers for Input Data Used 
Data Description DTN Data Use a 
Matrix saturation, water potential, and 
hydrologic property data MO0109HYMXPROP.001 [DIRS 155989] 6.1.3.3 
App. A 
Physical properties and water potential 
for borehole samples from USW WT-24 GS980708312242.010 [DIRS 106752] App. A 
Physical properties and water potential 
for borehole samples from USW SD-6 GS980808312242.014 [DIRS 106748] App. A 
Physical properties and hydraulic-
conductivity measurements from USW GS980708312242.011 [DIRS 107150] App. A 
WT-24 
Physical properties and saturated-
hydraulic-conductivity measurements GS980908312242.038 [DIRS 107154] App. A 
from USW SD-6 
Physical properties and saturated-
hydraulic-conductivity measurements 
from boreholes USW SD-7, USW SD-9, GS980908312242.041 [DIRS 107158] App. A 
USW SD-12, USW UZ-14 and UE-25 
UZ#16 
Measured physical and hydraulic 
properties of core samples from Busted 
Butte boreholes 
GS990308312242.007 [DIRS 107185] 
GS990708312242.008 [DIRS 109822] 
App. A 
Physical properties and saturated 
hydraulic conductivity of cores from 
surface samples from the ESF main drift GS971008312231.006 [DIRS 107184] App. A 
29+00m to 57+00m 
Water-retention data of borehole samples 
and surface samples from ESF north GS980908312242.037 [DIRS 107180] App. A 
ramp 
Unsaturated hydraulic properties of 
borehole samples from the PTn exposure GS980408312242.008 [DIRS 107161] App. A 
in the ESF north ramp 
Physical properties and saturated 
hydraulic conductivity measurements of 
core samples from boreholes in the ESF GS980908312242.040 [DIRS 107169] App. A 
north ramp 
Physical properties of borehole samples 
from the PTn exposure in the ESF north GS980308312242.005 [DIRS 107165] App. A 
ramp 
Unsaturated water-retention data for 
samples from USW SD-6 GS980908312242.039 [DIRS 145272] App. A 
Moisture-retention data for samples from 
boreholes USW SD-7, USW SD-9, USW GS960808312231.003 [DIRS 147590] App. A 
SD-12 and UE-25 UZ#16 
Unsaturated hydraulic properties from 
USW WT-24 GS980808312242.012 [DIRS 149375] App. A 
Moisture-retention data from boreholes 
USW UZ-N27 and UE-25 UZ#16. GS950608312231.008 [DIRS 144662] App. A 
Unsaturated hydraulic conductivity and 
water potential in Busted Butte volcanic GS010608312242.001 [DIRS 160822] App. A 
tuff cores 
Lithostratigraphic classification of core 
samples for the Busted Butte Phase 2 LA0207SL831372.001 [DIRS 160824] App. A 
test block 
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Table 4-1. Data Tracking Numbers for Input Data Used (Continued) 
Data Description DTN Data Use a 
Lithostratigraphic information and 
chemical analyses from drill cores LAJF831222AQ98.014 [DIRS 160825] App. A 
collected in ESF 
Stratigraphic description and data for the 
Yucca Mountain tuff in boreholes 
NRG#2B, NRG-7/7A, SD-9, UZ-14, GS950108314211.009 [DIRS 152556] App. A 
UZ#16, UZ-N11, UZ-N33, UZ-N34, 
UZ-N53, UZ-N54, UZ-N55 
USW UZ-7a shift drilling summaries, 
lithologic logs, structural logs, weight logs, 
and composite borehole log from 0.0 to TM000000UZ7ARS.001 [DIRS 160826] App. A 
770.0 
Table of contacts in borehole USW 
UZ-N35 GS940208314211.007 [DIRS 155533] App. A 
Table of contacts for the Tiva Canyon tuff 
in borehole USW UZ-N36 GS940308314211.018 [DIRS 145589] App. A 
Lithostratigraphic data for Paintbrush 
Group bedded tuff units in boreholes 
USW UZ-N11, USW UZ-14, USW NRG-
7/7A, USW SD-9, USW UZ-N37, USW GS950108314211.008 [DIRS 152558] App. A 
NRG-6, UE-25 NRG#2B, USW UZ-N31, 
USW UZ-N32, USW SD-12, UE-25 
UZ#16, USW UZ-N54, USW UZ-N53 
Stratigraphic descriptions of the Pah 
Canyon tuff in boreholes UE-25 NRG#2B, 
UE-25 NRG#4, USW NRG-6, 
USW NRG-7/7A, USW SD-9, USW SD-GS950708314211.028 [DIRS 160827] App. A 
12, USW UZ-14, USW UZ-N31, USW 
UZ-N32, and USW UZ-N37 
Tables of contacts in boreholes USW 
UZ-N57, UZ-N58, UZ-N59, and UZ-N61 GS940208314211.008 [DIRS 145581] App. A 
Developed fracture hydrologic properties 
for UZ model layers (FY99) LB990501233129.001 [DIRS 106787] 
6.1.2 
6.1.3.1 
6.1.3.3 
Air permeability data from vertical 
boreholes GS960908312232.013 [DIRS 105574] 
Section 6.1.1 
Figure 6-2 
Table 6-4 
App. A 
Air permeability data from Alcoves 1,2,3 GS970183122410.001 [DIRS 105580] Table 6-4 
App. A 
Air-injection and permeability data-SHT 
area LB960500834244.001 [DIRS 105587] 
Figure 6-2 
Table 6-4 
App. A 
Air-injection and permeability data-DST 
area 
LB970600123142.001 [DIRS 105589] 
LB980120123142.004 [DIRS 105590] 
LB980120123142.005 [DIRS 114134] 
Figure 6-2 
Table 6-4 
App. A 
Air-injection, tracer test, and fracture 
porosity data LB980912332245.002 [DIRS 105593] 
6.1.3.1 
6.1.3.2 
6.1.3.3 
Detailed Line Survey and Full-Periphery 
Geotechnical Map, and Comparative GS960908314224.020 [DIRS 106059] App. A 
Geological Cross Section 
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Table 4-1. Data Tracking Numbers for Input Data Used (Continued) 
Data Description DTN Data Use a 
Ghost Dance fault permeability GS990883122410.002 [DIRS 135230] 6.3 
Geologic Framework Model (GFM2000) MO0012MWDGFM02.002 [DIRS 153777] 6.3 
App. A 
a 
Sections where the data used are described in detail. 
DST=Drift Scale Test; ESF = Exploratory Studies Facility; FY=Fiscal Year; 
PTn= Upper Paintbrush non-welded vitric; SHT=Single Heater Test 
4.2 CRITERIA 
The general requirements to be satisfied by Total System Performance Assessment (TSPA) are 
stated in 10 CFR 63.114 [DIRS 156605] (Requirements for Performance Assessment). 
Technical requirements to be satisfied by TSPA are identified in the Yucca Mountain Project 
Requirements Document (Canori and Leitner 2003 [DIRS 166275]). 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, Final Report 
(YMRP) (NRC 2003 [DIRS 163274]). The pertinent criteria and subcriteria for this analysis 
report are, from Criteria 1 through 3, contained in Section 2.2.1.3.6.3 Acceptance Criteria (for 
Section 2.2.1.3.6, Flow Paths in the Unsaturated Zone), which are based on meeting the 
requirements of 10 CFR 63.114(a)(c) and (e)(g) [DIRS 156605], relating to flow paths in the 
unsaturated zone model abstraction (Table 4-2). 
Table 4-2. Acceptance Criteria Applicable to This Analysis Report 
Requirement 
Number a Requirement Title a 10 CFR 63 Link 
YMRP Acceptance 
Criteriab 
PRD 002/T-015 Requirements for 
Performance Assessment 
10 CFR 63.114 (a)-(c) and 
(e)-(g) 2.2.1.3.6.3, Criteria 1 to 3 
ab 
from Canori and Leitner (2003 [DIRS 166275]) 
from NRC (2003 [DIRS 163274]) 
YMRP=Yucca Mountain Review Plan
The pertinent acceptance criteria from Section 2.2.1.3.6.3 of the YMRP (NRC 2003 
[DIRS 163274]) are included below. In cases where subsidiary criteria are listed in the YMRP 
for a given criterion, only the subsidiary criteria addressed by this scientific analysis are listed 
below. Where a subcriterion includes several components, only some of those components may 
be addressed. How these components are addressed is summarized in Section 7.2 of this report. 
Acceptance Criteria from Section 2.2.1.3.6.3, Flow Paths in the Unsaturated Zone 
Acceptance Criterion 1: System Description and Model Integration Are Adequate. 
(1) The total system performance assessment adequately incorporates, or bounds, 
important design features, physical phenomena, and couplings, and uses consistent and 
appropriate assumptions throughout the flow paths in the unsaturated zone abstraction 
process. Couplings include thermal-hydrologic-mechanical-chemical effects, as 
appropriate; 
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Analysis of Hydrologic Properties Data 
(2) The aspects of geology, hydrology, geochemistry, physical phenomena, and couplings 
that may affect flow paths in the unsaturated zone are adequately considered. 
Conditions and assumptions in the abstraction of flow paths in the unsaturated zone 
are readily identified and consistent with the body of data presented in the description; 
(3) The abstraction of flow paths in the unsaturated zone uses assumptions, technical 
bases, data, and models that are appropriate and consistent with other related U.S. 
Department of Energy abstractions. For example, the assumptions used for flow paths 
in the unsaturated zone are consistent with the abstractions of quantity and chemistry 
of water contacting waste packages and waste forms, climate and infiltration, and flow 
paths in the saturated zone (Sections 2.2.1.3.3, 2.2.1.3.5, and 2.2.1.3.8 of the Yucca 
Mountain Review Plan [DIRS 163274], respectively). The descriptions and technical 
bases are transparent and traceable to site and design data; 
(7) Average parameter estimates used in process-level models are representative of the 
temporal and spatial discretizations considered in the model; 
(9) Guidance in NUREG1297 (Altman et al. 1988 [DIRS 103597]) and NUREG1298 
(Altman et al. 1988 [DIRS 103750]), or other acceptable approaches for peer review 
and data qualification is followed. 
Acceptance Criterion 2: Data Are Sufficient for Model Justification. 
(1) Hydrological and thermal-hydrological-mechanical-chemical values used in the 
license application are adequately justified. Adequate descriptions of how the data 
were used, interpreted, and appropriately synthesized into the parameters are provided; 
(2) The data on the geology, hydrology, and geochemistry of the unsaturated zone, are 
collected using acceptable techniques; 
Acceptance Criterion 3: Data Uncertainty is Characterized and Propagated Through the 
Model Abstraction. 
(6) Uncertainties in the characteristics of the natural system and engineered materials are 
considered. 
4.3 CODES, STANDARDS, AND REGULATIONS 
No codes, standards, or regulations other than those identified in the Project Requirements 
Document (Canori and Leitner 2003 [DIRS 166275], Table 2-3) and determined to be applicable 
in Table 4-2, were used in this report. 
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5. ASSUMPTIONS 
The assumptions made to determine hydrologic properties, in the absence of direct confirmation 
data or evidence, are as follows: 
1. No air-injection data are available for calculating the fracture permeability values for 
the Prow Pass (pp), Bullfrog (bf), and Tram (tr) units. Therefore, analogues, based on 
the similarity of matrix properties, the degree of zeolitic alteration, and degree of 
welding, are assumed to be appropriate for calculating the fracture permeability values 
for those units. This can be justified based on the following two considerations. First, 
this report only provides the initial guesses of the fracture permeability for the 
calibrated properties model, and the UZ flow simulations use the calibrated 
permeability values from the calibrated properties model. Therefore, using 
assumptions in calculating the initial guesses of the permeability shall not significantly 
affect the final UZ flow simulations that feed results to TSPA. Second, the geological 
similarity is a reasonable basis for the analogue approach described above. 
2. An upper limit of 1.5 orders-of-magnitude upscaling is assumed to be appropriate for 
calculating upscaled matrix permeability. This is based mainly on the following 
considerations. First, the upscaling law (Equation 6-28) was developed for a porous 
medium (single continuum) and can only be considered as an approximation for a 
dual-continuum system. For example, the existence of fractures, which may act as a 
capillary barrier, can increase tortuosity of liquid water flow in the matrix and 
therefore reduce the effective permeability compared to the case without fractures. 
Second, this report only provides the initial guesses of the matrix permeability for the 
calibrated properties model and the UZ flow simulations use the calibrated 
permeability values from the calibrated properties model. Therefore, using 
assumptions in calculating the initial guesses of the permeability shall not significantly 
affect the final UZ flow simulations that feed results to TSPA. Third, the use of the 
upper limit for upscaling is practically necessary given the uncertainty resulting from 
both the approximation nature of the upscaling law (developed for porous media) and 
the sparseness of data available for calculating the permeability variance that is used 
for determining the upscaled permeability. 
Other scientific analysis assumptions are described in Section 6 of this analysis report where they 
are used. 
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6. SCIENTIFIC ANALYSIS DISCUSSION 
In this section, the methodologies and data used to determine representative estimates of the 
fracture and matrix properties for the UZ Model layers are discussed. Table 6-1 shows the 
relationships between the lithostratigraphy of the Geologic Framework Model (GFM2000) 
(BSC 2004 [DIRS 170029]) and the UZ Model layers, as documented in a scientific analysis 
report describing development of numerical grids for UZ flow and transport modeling 
(BSC 2004 [DIRS 169855], Table 6-5). Note that the relationship between major units and 
hydrogeologic units in Table 6-1 is slightly different from Table 1 of Characterization of 
Hydrogeologic Units Using Matrix Properties, Yucca Mountain, Nevada (Flint 1998 
[DIRS 100033]). A detailed discussion of these differences is documented in Sections 6.3 and 
6.4 as well as Table 6-5 of Development of Numerical Grids for UZ Flow and Transport 
Modeling (BSC 2004 [DIRS 169855]). Most fracture and matrix properties or parameters 
estimated in this report are used as inputs in the inversion modeling studies documented in the 
model report Calibrated Properties Model (BSC 2004 [DIRS 169857]). The key scientific 
notebooks (with relevant page numbers) used for this study are listed in Table 6-2. Two 
assumptions are used in this section, as presented in Section 5. The intended use of the output 
data, developed using approaches documented in this section, is given in Section 1. 
In this report, the heterogeneity of the Yucca Mountain UZ is modeled by a number of layers, 
each of which has homogeneous and isotropic hydrologic properties, based on the following 
considerations: First, the overall behavior of flow and transport processes in the Yucca 
Mountain UZ is mainly determined by relatively large-scale heterogeneities introduced by 
stratification of the tuffs (Zhou et al. 2003 [DIRS 162133]). Second, the complexity of models 
for heterogeneity and anisotropicity needs to be consistent with the available data while the 
available data are too sparse to characterize the detailed heterogeneity and anisotropicity within 
each UZ model layer. Third, this layered approach is supported by field observations, such as 
matrix water saturation distributions. For a given geologic unit, measured matrix saturation 
distributions can be very similar in different boreholes (Flint 1998 [DIRS 100033], pp. 24 to 30, 
Figures 5 to 9), indicating that matrix flow behavior and effective hydraulic properties should be 
similar within the unit. Further discussion of this issue is provided in a model report, Conceptual 
Model and Numerical Approaches for Unsaturated Zone Flow and Transport (BSC 2004 
[DIRS 170035], Section 6.3.4). 
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Analysis of Hydrologic Properties Data 
Table 6-1. Correlation of GFM2000 Lithostratigraphy, UZ Model Layer, and Hydrogeologic Unit 
Major Unit 
(Modified from 
Montazer and Wilson 
1984 [DIRS 100161]) 
GFM2000 
Lithostratigraphic 
Nomenclature 
UZ Model Layer 
(BSC 2004 
[DIRS 169855], 
Table 6-5) 
Hydrogeologic Unit 
(Flint 1998 
[DIRS 100033], Table 1) 
Tiva Canyon Welded Tpcr tcw11 CCR, CUC 
(TCw) Tpcp tcw12 CUL, CW 
TpcLD 
Tpcpv3 tcw13 CMW 
Tpcpv2 
Paintbrush nonwelded Tpcpv1 ptn21 CNW 
(PTn) Tpbt4 ptn22 BT4 
Tpy (Yucca) 
ptn23 TPY 
ptn24 BT3 
Tpbt3 
Tpp (Pah) ptn25 TPP 
Tpbt2 ptn26 BT2 
Tptrv3 
Tptrv2 
Topopah Spring welded Tptrv1 tsw31 TC 
(TSw) Tptrn 
tsw32 TR 
Tptrl, Tptf tsw33 TUL 
Tptpul, RHHtop 
Tptpmn tsw34 TMN 
Tptpll tsw35 TLL 
Tptpln tsw36 TM2 (upper 2/3 of 
Tptpln) 
tsw37 TM1 (lower 1/3 of 
Tptpln) 
Tptpv3 tsw38 PV3 
Tptpv2 tsw39 (vit, zeo) PV2 
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Table 6-1. Correlation of GFM2000 Lithostratigraphy, UZ Model Layer, and Hydrogeologic Unit 
(Continued) 
Major Unit 
(Modified from 
Montazer and Wilson 
1984 [DIRS 100161]) 
GFM2000 
Lithostratigraphic 
Nomenclature 
UZ Model Layer 
(BSC 2004 
[DIRS 169855], 
Table 6-5) 
Hydrogeologic Unit 
(Flint 1998 
[DIRS 100033], Table 1) 
Calico Hills nonwelded Tptpv1 ch1 (vit, zeo) BT1 or BT1a (altered) 
(CHn) Tpbt1 
Tac (Calico) ch2 (vit, zeo) CHV (vitric) or CHZ 
(zeolitic)ch3 (vit, zeo) 
ch4 (vit, zeo0 
ch5 (vit, zeo) 
Tacbt (Calicobt) ch6 (vit, zeo) BT 
Tcpuv (Prowuv) pp4 PP4 (zeolitic) 
Tcpuc (Prowuc) pp3 PP3 (devitrified) 
Tcpmd (Prowmd) pp2 PP2 (devitrified) 
Tcplc (Prowlc) 
Tcplv (Prowlv) pp1 PP1 (zeolitic) 
Tcpbt (Prowbt) 
Tcbuv (Bullfroguv) 
Crater Flat Tcbuc (Bullfroguc) bf3 BF3 (welded) 
undifferentiated (CFu) Tcbmd (Bullfrogmd) 
Tcblc (Bullfroglc) 
Tcblv (Bullfroglv) bf2 BF2 (nonwelded) 
Tcbbt (Bullfrogbt) 
Tctuv (Tramuv) 
Tctuc (Tramuc) tr3 Not Available 
Tctmd (Trammd) 
Tctlc (Tramlc) 
Tctlv (Tramlv) tr2 Not Available 
Tctbt (Trambt) and 
below 
Source: BSC (2004 [DIRS 169855], Table 6-5) 
Table 6-2. Scientific Notebooks 
Lawrence Berkeley 
National Laboratory 
Scientific Notebook ID 
Management and 
Operations Contractor 
Scientific Notebook ID Relevant Pages Citation 
YMP-LBNL-GSB-1.1.2 SN-LBNL-SCI-003-V1 9394, 117127, 145-146 Ahlers 2000 [DIRS 155853] 
YMP-LBNL-GSB-LHH-3 SN-LBNL-SCI-215-V1 3553, 101 Wang 2003 [DIRS 161654] 
YMP-LBNL-UZ-CFA-1 SN-LBNL-SCI-003-V2 5783 Wang 2003 [DIRS 161654] 
The selected FEPs for this report (Table 6-3) are those taken from the license application (LA) 
FEP list (DTN: MO0407SEPFEPLA.000 [DIRS 170760]) and are associated with the subject 
matter of this report. Consideration of the license application FEP list is in accordance with the 
activities represented in the TWP (BSC 2004 [DIRS 169654], Table 2.1.5-1). The discussion in 
ANL-NBS-HS-000042 REV 00 6-3 October 2004 

Analysis of Hydrologic Properties Data 
this and other model and analysis reports form the technical basis for evaluation of the listed 
FEPs. The cross reference for each FEP to the relevant section of this report is given below. 
Table 6-3. FEPs Addressed in this Analysis Report 
FEP No. FEP Name Relevant Section and Tables 
1.2.02.01.0A Fractures 6.1 
1.2.02.02.0A Faults 6.3 
2.2.03.01.0A Stratigraphy 6, Tables 6-1, 6-4, 6-5, and 6-6 
2.2.03.02.0A Rock properties of host rock and other units 6.1, 6.2, and 6.3 
2.2.07.02.0A Unsaturated groundwater flow in geosphere 6.1, 6.2, and 6.3 
2.2.07.08.0A Fracture flow in the UZ 6.1 
FEP=Feature, Event, and Process 
The following subsections present the methods used to determine fracture properties, matrix 
properties, and fault properties. 
6.1 FRACTURE PROPERTIES 
Fracture properties determined in this report include fracture frequency, fracture aperture, 
fracture porosity, fracture interface area, uncalibrated van Genuchten fracture a and m, and 
uncalibrated fracture permeability. The development of fracture properties is documented in a 
Scientific Notebook (Wang 2003 [DIRS 161654], SN-LBNL-SCI-215-V1, pp. 35 to 53). Excel 
files used for calculating fracture properties are listed and described in Appendix A. Excel files 
lecan97.xls, UTCA_BRFA.xls, drift.xls, and airk.xls are used for calculating fracture permeability 
values, and Fpor.xls is used for determining fracture porosity values. 
6.1.1 Fracture Permeability 
The fracture permeabilities calculated here for the UZ Model layers are based on air 
permeabilities inferred from air-injection tests performed in vertical boreholes and in ESF 
alcoves. Permeabilities inferred from air-injection tests in boreholes are representative of fracture 
absolute permeabilities because the fractures were dry during the tests. These permeabilities 
were determined based on pneumatic-pressure data and are calculated using a modified version 
of Hvorslevs (Hvorslev 1951 [DIRS 101868], p. 30, Case 8) solution for steady-state ellipsoidal 
flow (LeCain 1995 [DIRS 101700], p. 10). The determined permeability values are combined 
here to determine effective fracture permeabilities for the UZ Model layers. The geometric 
averaging is one of the most widely used simple upscaling methods (Wen and Gomez-Hernandez 
1996 [DIRS 170239], p. xii to xiii). Therefore, geometric means of these fracture permeabilities 
are considered to reflect upscaling of these permeabilities for use as single values representative 
for each model layer, and can be a good starting point for calibration. There is a theoretical basis 
for the independence of permeability from particular test fluids, as long as the test medium can 
be viewed as a rigid continuum. Thus, fracture permeabilities derived from air-injection tests are 
considered to be applicable to liquid water flow in fractures. 
The data sources available for calculating the fracture permeability values are different for 
different hydrogeologic units as listed in Table (6-4). For the Tiva Canyon welded 
hydrogeologic unit (TCw), fracture permeabilities were based on air-injection tests performed in 
ANL-NBS-HS-000042 REV 00 6-4 October 2004 

Analysis of Hydrologic Properties Data 
boreholes NRG-7a, NRG-6, SD-12, and UZ#16, as well as in the Upper Tiva Canyon, Bow 
Ridge fault, and Upper Paintbrush contact alcoves (Alcoves 1, 2 and 3, respectively). For the 
Paintbrush nonwelded hydrogeologic unit (PTn), the permeability data are from borehole 
NRG-7a and the Upper Paintbrush contact alcove (Alcove 3). For the Topopah Spring welded 
hydrogeologic unit (TSw), the permeability data are from boreholes NRG-7a, NRG-6, SD-12, 
and UZ#16, as well as from the Single Heater Test and Drift Scale Test areas in Alcove 5. For 
the Calico Hills nonwelded hydrogeologic unit (CHn), permeability data are available only from 
a single sampled interval in the borehole UZ#16. The locations of the boreholes are given in 
Figure 6-1. No air-injection data are available for the Prow Pass (pp), Bullfrog (bf), and 
Tram (tr) units. For model layers where no air injection data are available, analogs of other units 
are used, based on the similarity of the matrix properties, the degree of zeolitic alteration and 
degree of welding. These fracture permeabilities are used only as prior information and initial 
estimates for the Calibrated Properties Model (BSC 2004 [DIRS 169857]). 
ANL-NBS-HS-000042 REV 00 6-5 October 2004 

Analysis of Hydrologic Properties Data 
Source: Adapted from BSC (2004 [DIRS 169857], Figure 4-1). 
Figure 6-1. Schematic Showing Locations of Selected Boreholes 
ANL-NBS-HS-000042 REV 00 6-6 October 2004 

Analysis of Hydrologic Properties Data 
Table 6-4 lists the geometric means of the fracture permeabilities for the UZ Model layers. The 
lithostratigraphic units were assigned to the UZ Model layers as listed in Table 6-1. The fracture 
permeabilities were treated as isotropic, and the data from vertical boreholes, and from the 
horizontal and inclined boreholes in the ESF alcoves were combined. The scales of these 
measurements are similar, as discussed later in Section 6.1.1.1. 
Table 6-4. Uncalibrated Fracture Permeabilities for the UZ Model Layers 
UZ 
Model Layer 
Fracture 
Permeability (m2 ) 
Basisa kG 
b log(kG ) slog (kG) 
c Nd 
tcw11 BRFA 3.0E-11 -10.52 -2 
tcw12 
UTCA 
UPCA 
NRG-6 
NRG-7a 
SD-12 
UZ#16 
5.3E-12 -11.28 0.78 80 
tcw13 
UPCA 
NRG-7a 
4.5E-12 -11.35 1.15 3 
ptn21 
UPCA 
NRG-7a 
3.2E-12 -11.49 0.88 12 
ptn22 NRG-7a 3.0E-13 -12.52 0.20 4 
ptn23 NRG-7a 3.0E-13 -12.52 0.20 4 
ptn24 NRG-7a 3.0E-12 -11.52 -1 
ptn25 NRG-7a 1.7E-13 -12.78 0.10 7 
ptn26 NRG-7a 2.2E-13 -12.66 -1 
tsw31 Average TSW 8.1E-13 -12.09 --
tsw32 
NRG-6 
NRG-7a 
SD-12 
UZ#16 
7.1E-13 -12.15 0.66 31 
tsw33 
NRG-6 
NRG-7a 
SD-12 
UZ#16 
7.8E-13 -12.11 0.61 27 
tsw34 
SHT 
DST 
NRG-6 
NRG-7a 
SD-12 
UZ#16 
3.3E-13 -12.48 0.47 180 
alternate tsw34 
SHT 
DST 
NRG-6 
NRG-7a 
SD-12 
UZ#16 
1.5E-13 -12.81 0.75 180 
tsw35 NRG-7a 
UZ#16 9.1E-13 -12.04 0.54 31 
ANL-NBS-HS-000042 REV 00 6-7 October 2004 

Analysis of Hydrologic Properties Data 
Table 6-4. Uncalibrated Fracture Permeabilities for the UZ Model Layers 
(Continued) 
UZ 
Model Layer 
Fracture 
Permeability (m2 ) 
Basisa kG 
b log(kG ) slog (kG) 
c Nd 
tsw36 through 
tsw37 
SD-12 
UZ#16 1.3E-12 -11.87 0.28 19 
tsw38 Average 
TSw 8.1E-13 -12.09 --
tsw39 Average 
TSw 8.1E-13 -12.09 --
ch1Ze ch2Ze 2.5E-14 -13.60 --
ch1VI ptn26 2.2E-13 -12.66 --
ch2VI through 
ch5VI ptn26 2.2E-13 -12.66 --
ch2Ze through 
ch5Ze UZ#16 2.5E-14 -13.60 -1 
ch6 ch2Ze 2.5E-14 -13.60 --
pp4 ch2Ze 2.5E-14 -13.60 --
pp3 ptn26 2.2E-13 -12.66 --
pp2 ptn26 2.2E-13 -12.66 --
pp1 ch2Ze 2.5E-14 -13.60 --
bf3 ptn26 2.2E-13 -12.66 --
bf2 ch2Ze 2.5E-14 -13.60 --
tr3 ptn26 2.2E-13 -12.66 --
tr2 ch2Ze 2.5E-14 -13.60 --
Output DTN: LB0205REVUZPRP.001. 
Source: DTNs: GS960908312232.013 [DIRS 105574]; GS970183122410.001 
[DIRS 105580]; LB970600123142.001 [DIRS 105589]; 
LB980120123142.004 [DIRS 105590]; LB980120123142.005 
[DIRS 114134]; LB960500834244.001 [DIRS 105587]. 
a 
Identifies the corresponding air-injection borehole(s) and/or alcove(s) or analog to another 
model layer(s). UTCA-Upper Tiva Canyon Alcove, BRFA-Bow Ridge fault Alcove, UPCA-
Upper Paintbrush Contact Alcove, and NRG-6, NRG-7a, SD-12, and UZ#16 are vertical 
boreholes. (This column is presented for information only and is not from the cited DTN.) 
b 
Geometric mean 
c 
Standard deviation 
d 
Number of sampled intervals 
- indicates that no data are available 
DST=Drift Scale Test; SHT=Single Heater Test 
2
The mean fracture permeabilities range from 2.5  1014 m2 to 3.0  1011 m. The Tiva Canyon 
welded unit (TCw) has the highest fracture permeabilities. Topopah Spring welded unit (TSw) 
fracture permeabilities are, in general, higher than those for the nonwelded Paintbrush (PTn) and 
Calico Hills (CHn) units. Two fracture permeabilities are shown for the Topopah Spring middle 
nonlithophysal unit (tsw34). These represent two different approaches for weighting the 
available air-injection data. For tsw34, there were 143 sampled intervals in the Alcove 5 heater 
test areas compared to 37 sampled intervals in the four vertical borehole injection tests. For the 
first case, the data from Alcove 5 were weighted with those from the vertical borehole tests 
(k=0.8 kG,vertical boreholes + 0.2 kG,Alcove 5), considering that the boreholes are distributed over a much 
larger area (i.e., sparser sampling) than that the Alcove covers (i.e., denser sampling). In the 
alternate tsw34 case, each sampled interval was weighted equally. 
ANL-NBS-HS-000042 REV 00 6-8 October 2004 

Analysis of Hydrologic Properties Data 
The uncertainty and variability of fracture permeabilities for the UZ Model layers are reflected 
by the standard deviations reported in Table 6-4. These standard deviations result in 
95 percent confidence intervals covering three orders of magnitude, even for the units that have a 
large number of sampled intervals. The data indicate that fracture permeabilities are highly 
variable. 
6.1.1.1 Scaling Issues 
Scaling issue arises when the fracture permeability is measured at a scale different from the one 
used in numerical simulations. Wen and Gomez-Hernandez (1996 [DIRS 170239]) reviewed the 
techniques for upscaling of block hydraulic conductivities range from the simple averaging of 
the heterogenous values within the block to sophisticated inversions, after obtaining the solution 
of the flow equation at the measurement scale. Renard and de Marsily (1997 [DIRS 170240]) 
provided another review on the scaling issue but focused on the equivalent permeability for 
uniform, single-phase, steady-state flow. For most numerical simulations of real world problems 
such as the UZ, the permeability (or conductivity) is actually defined on the scale of grid blocks. 
That the block permeability (or block conductivity) is not an instrinsic characteristic of the 
medium but subject to the flow conditions is well known (Renard and de Marsily 1997 
[DIRS 170240], p. 255; Wen and Gomez-Hernandez 1996 [DIRS 170239], p. xxvii). For the 
fractured porous rock (i.e., the tuffs in Yucca Mountain), the situations are more complicated 
than heterogeneous porous media. Therefore, when using the permeability values, especially 
fracture permeability values, developed in this report, special attention is needed at the scale at 
which the permeability values have been measured and averaged. In most cases, a proper 
inversion modeling or manual calibration is recommended to obviate the problems of scale 
change (Renard and de Marsily 1997 [DIRS 170240], p. 253). The following paragraph is a 
summary of measuring scales and averaging method used in developing the fracture permeability 
values for each UZ Model layer. 
The permeabilities measured in the vertical boreholes and alcoves were combined to determine 
the fracture permeability for each UZ Model layer. The straddle packer test interval lengths were 
approximately 4 m for vertical boreholes, 1 to 3 m for Alcoves 1, 2, and 3, and 5 to 12 m in the 
Single Heater Test (SHT) and DST areas (Alcove 5). These data were considered to be on the 
same relative scale and representative of the fracture permeability on the scale of the UZ Model, 
using geometric means. Additional air-permeability data on a scale of one-foot intervals are also 
available from air-injection testing in niches in the ESF in the Topopah Spring middle 
nonlithophysal unit (tsw34). The air-injection data from the niche studies are not used here for 
determining mean fracture permeabilities for the model layers, since these data are on a smaller 
scale and may not be representative of larger-scale effective permeability. Figure 6-2 compares 
the geometric means and range of data (mean  standard deviation) for the model layer tsw34 
corresponding to Tptpmn (Table 6-1) (Wang 2003 [DIRS 161654], SN-LBNL-SCI-215-V1, 
p. 101). The data shown for the niche studies are inferred from pre-excavation air-injection 
testing. The ranges of the data overlap, but the geometric means for the measurements from the 
niche studies are generally lower than the other values. 
ANL-NBS-HS-000042 REV 00 6-9 October 2004 

Analysis of Hydrologic Properties Data 
log(K) 
-1 4 .5 
-1 4 .0 
-1 3 .5 
-1 3 .0 
-1 2 .5 
-1 2 .0 
-1 1 .5 
-1 1 .0 
N R G 6 N R G 7a S D-1 2 U Z #16 S H T & D S T Nic he 3566 Niche 3650 Niche 3107 Nic he 4788 
Source: DTNs: GS960908312232.013 [DIRS 105574], LB960500834244.001 [DIRS 105587], 
LB970600123142.001 [DIRS 105589], LB980120123142.004 [DIRS 105590], 
LB980120123142.005 [DIRS 114134], LB990901233124.004 [DIRS 123273] are shown by Wang 
(2003 [DIRS 161654], SN-LBNL-SCI-215-V1, p. 101) and in spreadsheet drift.xls, in Appendix A. 
NOTE: Permeabilities were inferred from air-injection data. The filled circle indicates geometric mean, and range is  
one standard deviation. For details of calculations, see Appendix A, p. A-24. 
Figure 6-2. Fracture Permeabilities for Topopah Spring Middle Nonlithophysal Unit 
6.1.2 Fracture Frequency, Intensity, Interface Area, Aperture, and van Genuchten 
Parameters 
Fracture frequency, interface area, and the van Genuchten m are obtained from qualified fracture 
property data (DTN: LB990501233129.001 [DIRS 106787]) developed from field data. These 
include detailed line survey (DLS) fracture data (collected from the ESF North and South 
Ramps, Main Drift, and ECRB Cross-Drift, providing spatially varying frequency, length, and 
fracture dips and strikes) and fracture frequency data from boreholes. 
For completeness, mathematical equations used for developing these properties in 
DTN: LB990501233129.001 [DIRS 106787] are also described here. 
The mean fracture frequency is calculated as the inverse of the mean spacing obtained from the 
DLS in the ESF and ECRB Cross-Drift. The mean spacing is calculated by: 
nf 
s = 1.(Di - Di-1 ) (Eq. 6-1) 
nf - 1 2 
ANL-NBS-HS-000042 REV 00 6-10 October 2004 

Analysis of Hydrologic Properties Data 
where (Di  Di-1 ) is the spacing between two adjacent fractures whereas Di and Di-1 are defined 
as the distances from the north portal entrance of ESF to the ith and (i-1)th fractures, 
respectively, and nf is the number of fractures. This is the apparent spacing. It is not the normal 
distance between the fracture planes and is therefore a rough estimate of the true spacing. These 
values were not corrected for any possible bias in orientation in the DLS because of lacking 
fracture orientation information. The mean fracture frequency is given by the inverse of the 
mean apparent spacing: 
1
f = (Eq. 6-2) 
s 
Note that the DLS excludes small fractures that are considered not to connect the conductive 
fracture networks in the large scale (e.g., site scale). 
The borehole data are first processed to normalize for core recovery and corrected for bias in 
orientation. To correct for orientation bias in data from vertical boreholes, dip distributions are 
used as follows (modified from Lin et al. 1993 [DIRS 116797], p. 24, Eq. 3-1): 
. fi19 0 , dip . fi39 20 , dip . fi59 40 , dip . fi90 60 , dip
---- 
f
cb = i + i + i + i (Eq. 6-3) 
10cos( ) 30 cos( ) 50cos( ) 75 cos( ) 
where fcb is the borehole fracture frequency corrected for orientation bias and fi is the fracture 
frequency corresponding to the range of dip distribution. Because the borehole data include small 
fractures that are considred not to be connected to the conductive fracture networks in the large 
scale (e.g., site scale), the borehole fracture frequency values calculated above are scaled to 
represent larger length fractures on the scale of those characterized in the ESF. A simple 
correction ratio is used in calculating the final average fracture frequency for each model layer, 
based on comparisons of ESF data with corresponding vertical boreholes for that model layer: 
ff =
corrected = fcbR 
R = ... fESF ..
. 
(Eq. 6-4) 
. fborehole .average 
Two correction factors R were calculated, one for welded units using data for the Topopah 
Spring middle nonlithophysal hydrogeologic unit (tsw34) and one for nonwelded units using data 
for the Pah Canyon Tuff in the Paintbrush hydrogeologic unit (ptn25). These two units were 
selected because they are good representatives of the welded or nonwelded units at the site, 
respectively, and both ESF and borehole data were available for these two units. 
ANL-NBS-HS-000042 REV 00 6-11 October 2004 

Analysis of Hydrologic Properties Data 
The fracture intensity is calculated by dividing the trace length of the fracture by the area 
surveyed. The area surveyed was 6 m (3 m above and below the traceline) times the length 
along the tunnel considered for that interval. The average fracture intensity I (m/m2) is given by: 
nf nf 
.ti .ti 
i=1 = i=1
I= 
area ( m6 )( metersinlengthinterval ) (Eq. 6-5) 
where ti is trace length in meters for fracture i. 
Because the survey did not provide the information of the fractures in the third dimension 
(perpendicular to the drift wall), the fracture interface area is calculated by idealizing the 
fractures having a disk-like shape with a radii of one-half the trace length of the fracture. The 
volume for the survey interval is estimated by multiplying the interval length surveyed by the 
square of the geometric mean of surveyed fracture trace length. The average fracture interface 
area per volume Afm (m2/m3) is given by: 
nf nf 
22
.pri .pri 
Afm 
i=1 i=1
== 
2
)(
volume ( lengthstraceofmeangeometriclengthinterval ) 
(Eq. 6-6) 
where r is the radius of fracture i, or one-half the trace length of fracture i. 
Fracture apertures are calculated by the cubic law with the fractures fully connected. The 
fracture aperture b is then given by (Bear et al. 1993 [DIRS 116773], p. 15): 
1
3
. 12k .
b=
. f .
. (Eq. 6-7)
.
where k is the fracture permeability. The fracture aperture determined in this way is an effective 
hydraulic aperture (i.e., an aperture consistent with a given permeability observing the cubic 
law), not a physical aperture. Note that the above equation is modified from Equation 1.2.28 of 
Bear et al. (1993 [DIRS 116773], p. 15). The k here refers to bulk fracture permeability (i.e., the 
permeability of the fracture continuum) rather than permeability in a single discrete fracture as 
defined by Bear et al. (1993 [DIRS 116773], p. 15). 
Fitted parameters are required to utilize the van Genuchten equation relating the effective 
saturation Se and capillary pressure Pc [derived from Equations 2, 22, and 24 of A Closed-Form 
Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils (van Genuchten 1980 
[DIRS 100610], pp. 892 to 895)]: 
1
1 
-1 m - 1) n
P =(S 
(Eq. 6-8a)
ce
a
ANL-NBS-HS-000042 REV 00 6-12 October 2004 

Analysis of Hydrologic Properties Data 
where a, m, and n = 1 are the van Genuchten parameters. The effective saturation is defined 
1 - m 
by: 
Se =
SSs 
-
- 
SSrr 
(Eq. 6-8b) 
where S is total water saturation, Ss is satiated saturation, and Sr is residual saturation. 
A simplified form of the Young-Laplace equation is assumed to directly calculate the van 
Genuchten fracture a(af) from b. Note that the subscript f here and thereafter refers to fractures. 
The resulting relationship is: 
b
af = (Eq. 6-9) 
2ts cos. 
where t
s is the surface tension of pure water at 25C (0.072 N/m) (Lide 2002 [DIRS 160832], 
p. 6-3) and . is the contact angle. Essentially, Equation 6-9 states that van Genuchten acan be 
estimated as the inverse of the air-entry value, which is often used in the soil science literature 
(Wang and Narasimhan 1993 [DIRS 106793], p. 374). The contact angle . is set to zero (Wang 
and Narasimhan 1993 [DIRS 106793], p. 329), since the rock is expected to be hydrophilic, and 
no other specific data are available. 
Fracture aperture is calculated from the data of fracture frequency and permeability using 
Equation 6-7 and the van Genuchten alpha (af) is then calculated based on the fracture aperture 
data using Equation 6-9. The estimated mean apertures are approximately 100 to 400 m except 
for model layer tcw11, which had a relatively high fracture permeability, resulting in a higher 
estimated fracture aperture. The fracture van Genuchten alpha parameters (af) are on the order 
of 10-3 Pa-1. Large uncertainties exist in these values for the Calico Hills formation and lower 
units because little or no fracture permeability and fracture frequency data are available. 
The aperture-size distribution calculated using Equation 6-7 is further used to calculate the data 
set of capillary pressure vesus saturation using the Pruess and Tsangs method (Pruess and Tsang 
1990 [DIRS 170866], Equation (6) for capillary pressure, and Equation (13) for saturation). The 
van Genuchten fracture parameter (mf) is then determined by fitting Equation 6-8a to the data set 
of capillary pressure vesus saturation above. An mf value of 0.633, determined from the above 
method, is given in DTN: LB990501233129.001 [DIRS 106787]. Note that an alternative 
method to estimate mf is not available in the literature. 
The developed fracture properties are given in Table 6-5. 
ANL-NBS-HS-000042 REV 00 6-13 October 2004 

Analysis of Hydrologic Properties Data 
Table 6-5. Fracture Properties for UZ Model Layers 
UZ 
Model Layer 
Permeability (m2) Frequency (m-1) Van Genuchten 
Parameter 
Porosity Afm 
kG log(kG) std N Mean std N a (Pa-1) log(a) m (-) Mean (-) Std (-) 
tcw11 3.0E-11 -10.52 -2 0.92 0.94 76 5.0E-3 -2.30 0.633 2.4E-2 -1.56 
tcw12 5.3E-12 -11.28 0.78 80 1.91 2.09 1241 2.2E-3 -2.66 0.633 1.7E-2 -13.39 
tcw13 4.5E-12 -11.35 1.15 3 2.79 1.43 60 1.9E-3 -2.73 0.633 1.3E-2 -3.77 
ptn21 3.2E-12 -11.49 0.88 12 0.67 0.92 76 2.7E-3 -2.57 0.633 9.2E-3 -1.00 
ptn22 3.0E-13 -12.52 0.20 4 0.46 --1.4E-3 -2.86 0.633 1.0E-2 -1.41 
ptn23 3.0E-13 -12.52 0.20 4 0.57 -63 1.2E-3 -2.91 0.633 2.1E-3 -1.75 
ptn24 3.0E-12 -11.52 -1 0.46 0.45 18 3.0E-3 -2.53 0.633 1.0E-2 -0.34 
ptn25 1.7E-13 -12.78 0.10 7 0.52 0.6 72 1.1E-3 -2.96 0.633 5.5E-3 -1.09 
ptn26 2.2E-13 -12.66 -1 0.97 0.84 114 9.6E-4 -3.02 0.633 3.1E-3 -3.56 
tsw31 8.1E-13 -12.09 --2.17 2.37 140 1.1E-3 -2.96 0.633 5.0E-3 -3.86 
tsw32 7.1E-13 -12.15 0.66 31 1.12 1.09 842 1.4E-3 -2.86 0.633 8.3E-3 -3.21 
tsw33 7.8E-13 -12.11 0.61 27 0.81 1.03 1329 1.6E-3 -2.80 0.633 5.8E-3 -4.44 
tsw34 3.3E-13 -12.48 0.47 180 4.32 3.42 10646 6.7E-4 -3.18 0.633 8.5E-3 2.50E-03 13.54 
Alternate 
tsw34 
1.5E-13 -12.81 0.75 180 
tsw35 9.1E-13 -12.04 0.54 31 3.16 -595 1.0E-3 -2.99 0.633 9.6E-3 -9.68 
tsw36 
tsw37 
1.3E-12 -11.87 0.28 19 4.02 -526 1.1E-3 -2.96 0.633 1.3E-2 -12.31 
tsw38 8.1E-13 -12.09 --4.36 -37 8.9E-4 -3.05 0.633 1.1E-2 -13.34 
tsw39 8.1E-13 -12.09 --0.96 -46 1.5E-3 -2.82 0.633 4.3E-3 -2.95 
ch1Ze 2.5E-14 -13.60 --0.04 -3 1.4E-3 -2.86 0.633 1.6E-4 -0.11 
ch1VI 2.2E-13 -12.66 --0.10 -11 2.1E-3 -2.69 0.633 6.1E-4 -0.30 
ch2VI through 
ch5VI 
2.2E-13 -12.66 --0.14 -25 1.9E-3 -2.73 0.633 7.7E-4 -0.43 
ch2Ze 
through 
ch5Ze 
2.5E-14 -13.60 -1 0.14 -25 8.9E-4 -3.05 0.633 3.7E-4 -0.43 
ch6 2.5E-14 -13.60 --0.04 --1.4E-3 -2.86 0.633 1.6E-4 -0.11 
pp4 2.5E-14 -13.60 --0.14 --8.9E-4 -3.05 0.633 3.7E-4 -0.43 
pp3 2.2E-13 -12.66 --0.20 --1.6E-3 -2.78 0.633 9.7E-4 -0.61 
pp2 2.2E-13 -12.66 --0.20 --1.6E-3 -2.78 0.633 9.7E-4 -0.61 
pp1 2.5E-14 -13.60 --0.14 --8.9E-4 -3.05 0.633 3.7E-4 -0.43 
bf3 2.2E-13 -12.66 --0.20 --1.6E-3 -2.78 0.633 9.7E-4 -0.61 
bf2 2.5E-14 -13.60 --0.14 --8.9E-4 -3.05 0.633 3.7E-4 -0.43 
tr3 2.2E-13 -12.66 --0.20 --1.6E-3 -2.78 0.633 9.7E-4 -0.61 
tr2 2.5E-14 -13.60 --0.14 --8.9E-4 -3.05 0.633 3.7E-4 -0.43 
Output DTN: LB0205REVUZPRP.001. 
k
G = permeability (geometric mean). 
std = standard deviation.
N = number of samples. 
a = fitting parameters for the van Genuchten water potential relationship. 
m = fitting parameters for the van Genuchten water potential relationship. 
Afm = fracture-matrix interface area (m2/m3). 
- indicates that no data are available or dimensionless (in headings). 
ANL-NBS-HS-000042 REV 00 6-14 October 2004 

Analysis of Hydrologic Properties Data 
6.1.3 Fracture Porosity 
6.1.3.1 General Strategy 
Fracture porosity is herein defined as the effective porosity of fractures in which fluid flow and 
solute transport take place. In this study, a combination of porosity data derived from gas tracer 
tests in the ESF, and porosity estimates, based on the geometry of fracture networks, are used to 
develop representative fracture porosities for the UZ Model layers. The calculation of the 
fracture porosity is documented in this section and also in the scientific notebook (Wang 2003 
[DIRS 161654], SN-LBNL-SCI-215-V1, pp. 43 to 53). 
Gas tracer tests were performed in the ESF to obtain estimates of the effective fracture porosity 
for the Topopah Spring middle nonlithophysal welded tuff, corresponding to the tsw34 model 
layer (DTN: LB980912332245.002 [DIRS 105593]). Since gas tracer travel times through the 
fractured rocks are directly related to the storage of the corresponding fracture networks, 
analyses of tracer breakthrough data can provide reliable estimates of fracture porosity for the 
model layer tsw34. The porosity of tsw34 can also be estimated based on the fracture geometry 
observed in the ESF or boreholes using alternative approaches described later. 
The alternative approaches use 1-D borehole data or 2-D mapping data to calculate the fracture 
porosities. The 1-D and 2-D porosities were calculated from the 1-D borehole data and the 2-D 
mapping data, respectively. A 2-D porosity for a model layer can be estimated using the 
aperture and the total fracture length per unit area (fracture intensity). The fracture intensity is 
based on tracer lengths given by the DLS in the ESF and the area enclosing the traces (see 
Equation 6-5). The equation used to calculate the 2-D porosity is: 
f
2-D = bI (Eq. 6-10) 
where I is the fracture intensity (m/m2) (DTN: LB990501233129.001 [DIRS 106787]). When no 
intensity data are available (in cases where the unit does not intersect any portion of the ESF or 
ECRB Cross-Drift) (BSC 2001 [DIRS 159725], Section 6.1.3), the 1-D porosity can be estimated 
as follow: 
f
1-D = fb (Eq. 6-11) 
Note that a large degree of uncertainty exists in the estimates based on Equations 6-10 and 6-11 
for the following reasons. First, the estimated apertures are hydraulic apertures and may be very 
different from the average geometric apertures, since they are estimated based on 
air-permeability data. Second, Equations 6-10 and 6-11 only consider 2-D or 1-D geometric 
features, while actual fracture networks are three-dimensional. Therefore, direct estimates from 
these equations may not be reliable. However, it is reasonable to consider that these estimates 
provide reliable relative ratios of the fracture porosity for different stratigraphic units. Based on 
these considerations, a fracture porosity is determined by using the corresponding estimate from 
these equations to determine a ratio of fracture porosity between units. Because porosity, based 
on analyses of the gas tracer tests, is available for the tsw34 only, this value was used with these 
ratios to estimate fracture porosity for the other units: 
ANL-NBS-HS-000042 REV 00 6-15 October 2004 

Analysis of Hydrologic Properties Data 
f
f
f
x layer model D, -2 (Eq. 6-12) x layer model =ftsw34 f tsw34 D, -2 
or fx layer model=ftsw34 
fx layer model D, -1 
tsw34 D, -1 
where ftsw34 is fracture porosity for tsw34, estimated from the gas tracer data, and f2-D and f1-D 
refer to values calculated using Equations 6-10 and 6-11, respectively. The developed fracture 
porosity values for the UZ Model layers are given in Table 6-5. These values are on the order of 
1 percent. 
Note that the overall strategy is essentially a combination of the two general approaches 
available for estimating fracture porosities in the literature. The first approach is based on field 
tracer transport data. Researchers outside the Yucca Mountain Project have also used similar 
approaches. For example, inverse modeling was used to analyze a radially convergent flow 
tracer test in a fractured chalk formation, resulting in a calibrated fracture porosity of 0.3 percent 
(National Research Council 1996 [DIRS 139151], pp. 292 to 293). The second general approach 
is based on the geometry of a fracture network. This approach assumes the fractures under 
consideration are connected and requires that fracture apertures can be exactly determined. 
Although a large degree of uncertainty exists in fracture porosity values estimated from this 
approach (for several reasons), this approach has often been used when field tracer test data are 
not available. For example, in their review of numerical approaches for modeling multiphase 
flow in fractured petroleum reservoirs, Kazemi and Gilman (1993 [DIRS 147209], pp. 270 to 
271, 312 to 313) discuss the determination of fracture porosity, based on fracture geometry data. 
Considering that gas-tracer-test data are only available for one model layer (tsw34), and a large 
degree of uncertainty exists when the second approach is used, both approaches provide 
significantly better estimates for fracture porosity in units through the UZ. A combination of the 
above two approaches makes the best use of the relevant data. 
6.1.3.2 Fracture Porosity from Gas Tracer Testing Data 
The estimated fracture porosities (DTN: LB980912332245.002 [DIRS 105593]) were developed 
based on several simplifications (Figure 6-3): Flow and transport are two-dimensional; 
dispersion, gas compressibility and matrix diffusion are ignored; and the testing medium is 
homogeneous. The estimations were made using: 
ff * =Qt5.0 (Eq. 6-13) 
prL 
2 L 
where ff* is the estimated fracture porosity, Q is the volumetric withdrawal rate (Qwithdrawal in 
Figure 6-3), t0.5 is the mean travel time of tracer, rL is the distance between the tracer injection 
and withdrawal zones, and L is the length of injection and withdrawal zone. 
ANL-NBS-HS-000042 REV 00 6-16 October 2004

Analysis of Hydrologic Properties Data 
Figure 6-3. A Conceptual Model for Estimating Fracture Porosity Using Gas-Tracer Testing Data 
The average fracture porosity, estimated from Equation 6-13 using gas-tracer data collected from 
the DST block and Niche 3107, is 1.0210-2 (DTN: LB980912332245.002 [DIRS 105593]). 
6.1.3.3 Effects of Several Factors on Fracture-Porosity Estimation, Based on 
Gas-Tracer Testing Data 
The estimation of fracture porosity based on Equation 6-13 does not consider the effects of 
several factors: gas compressibility, heterogeneity, anisotropy, cavities, dispersion, and matrix 
diffusion. The potential effects of these factors on fracture-porosity estimates are discussed 
below. 
Gas compressibility does not have a significant effect on porosity estimation, because 
gas-pressure disturbances introduced by the gas-tracer tests are small (relative pressure changes 
are on the order of several percent), as inferred from Appendix A by Freifeld (2001 
[DIRS 161806]). 
Heterogeneity within the measurement scale was ignored in estimating fracture porosity, based 
on Equation 6-13. Therefore, the fracture porosity obtained from a gas-tracer test is an effective 
porosity of the fracture network within the measurement scale (on the order of several meters). 
Heterogeneity above the measurement scale is captured by standard deviation of the estimates. 
Effects of anisotropy are essentially captured in porosity estimation because different 
configurations (orientations of the source-sink alignments) were used in gas tracer tests 
performed in the Drift Scale Test block and Niche 3107. 
ANL-NBS-HS-000042 REV 00 6-17 October 2004 

Analysis of Hydrologic Properties Data 
Not enough data exist to evaluate the effect of cavities on porosity estimation in detail. 
However, appropriateness of the estimates can be partially demonstrated by comparing them 
with those from the other sites without cavities, which will be discussed later on. A discussion 
of cavity porosities and their estimates for geological units corresponding to the repository 
horizon is given in Thermal Conductivity of the Potential Repository Horizon Model Report 
(BSC 2004 [DIRS 169854], p. 81, Table 7-10). 
While the dispersion process is not expected to significantly affect the average tracer travel time 
used to calculate fracture porosity (Equation 6-13), Moench (1989 [DIRS 101146], Figure 2) 
implies that considering dispersion may result in larger porosity estimates than those determined 
from Equation 6-13 (Wang 2003 [DIRS 161654], SN-LBNL-SCI-215-V1, p. 53). Therefore, 
ignoring dispersion may partially compensate for the effects of cavities. 
The determination of fracture porosity depends on the tracer travel times. Diffusion of tracer 
into the matrix delays the breakthrough and causes overestimation of fracture porosity. The 
effects of matrix diffusion on fracture porosity estimation can be quantified by an analytical 
solution. Based on mass balance, radial tracer transport in a system (with matrix diffusion) like 
that shown in Figure 6-3 can be described by the following differential equation (Wang 2003 
[DIRS 161654], SN-LBNL-SCI-215-V1, pp. 44 to 45): 
.c + 
q fw .c AfmfmSmgDm .cm 
(Eq. 6-14) 
= 
.t ff .rs ff .x 
x =0 
with: 
q =Q (Eq. 6-15) 
fw 
2pL r 
w 
=1 rL 
2 - r 2 
(Eq. 6-16) 
rs 2 rw 
and: 
D =D0t (Eq. 6-17) 
m 
where c is the tracer concentration in fractures at a location with a distance r from the withdrawal 
borehole and at time t, rw is the radius of withdrawal borehole, ff 
is fracture porosity (considering 
matrix diffusion), Afm is the fracture-matrix interface area per unit volume of bulk rock, fm is the 
matrix porosity, Smg is the gas saturation in the matrix, D0 is the molecular-diffusion coefficient 
for gas in air, tis the tortuosity factor, cm is the tracer concentration in the matrix, and x is the 
distance from the fracture-matrix interface. 
Equation 6-14 can be transformed, by defining the lumped parameters (i.e., A0 and T0) as 
Equations 6-18 and 6-19, into the same mathematic form as Equation 4 of Starr et al. (1985 
ANL-NBS-HS-000042 REV 00 6-18 October 2004 

Analysis of Hydrologic Properties Data 
[DIRS 101479]), so that the solution to Equation 6-14 can be obtained from it. Under conditions 
of continuous injection with concentration c0, Starr et al. (1985 [DIRS 101479]) derived the 
solution to their Equation 4 as follows: 
c 
0 T0 <0 (Eq. 6-18)
=
c0 
.
.
. 
. 
A0 
0
T 
.
.
. 
. 
T0 > 0 
(Eq. 6-19)
c 
erfc
=
c0 
where A0 and T0 are functions of 
the relevant transport parameters (Starr et al. 1985 
p 
[DIRS 101479], p. 1044). The corresponding relations between transport parameters here and 
those of Starr et al. (1985 [DIRS 101479]) can be easily obtained by comparing Equation 6-14 
2
with their Equation 4. Based on these relations and using rsw= (rL -rw 
2)/rw . 1/2rL 
2/rw for rw 
<< rL, expressions for A0 and T0 at the withdrawal borehole (r = rw) can be obtained from the 
corresponding expressions of Starr et al. (1985 [DIRS 101479], p. 1044) and Wang (2003 
f 
[DIRS 161654], SN-LBNL-SCI-215-V1, pp. 46 to 47): 
1/ 2( LrL 
2)
Afm mSmgDm
0
A 
(Eq. 6-20) 
=
2Q
p
2 
Q 
0
=
(
t 
f 
-
f 
L 
1/ 2
rL
T 
) 
(Eq. 6-21) 
Note that under continuous (step function) tracer-injection conditions, average tracer travel time 
t0.5 is the time corresponding to 50 percent of the relative tracer concentration in the observed 
breakthrough curve: 
A0
.
.
(
t c
5.0 )
=
erfc
=
5.0 (Eq. 6-22) 
.
.
.
.
T 0(t )
5.0 
c0 
Combining Equations 6-13 with 6-20 through 6-22 yields (i.e., derive ff 
from the relationship, 
A0 / T0 =  at t = t0.5): 
2
f
f 
ff 
S
f fmm 
m 
2
ff 
where  is a constant (0.48) defined by erfc() = 0.5 and determined from Physical and 
Chemical Hydrogeology (Domenico and Schwartz 1990 [DIRS 100569], p. 637). The ff 
and ff* 
are identical if the matrix diffusion does not exist (Dm = 0), as shown in Equation 6-23. This 
equation can be used to correct the porosity estimates from Equation 6-13 to consider the effects 
ANL-NBS-HS-000042 REV 00 6-19 October 2004 
A
.
.
t
5.0 
* 
mg
D
1
- 
(Eq. 6-23) 
=
.
.
.
.
*

Analysis of Hydrologic Properties Data 
of matrix diffusion. Values for Afm and f m (for tsw34) are available from 
DTN: LB990501233129.001 [DIRS 106787]. The fracture porosity, f f*, is calculated using 
Equation 6-13 from DTN: LB980912332245.002 [DIRS 105593]. The average t0.5 is 210 min 
and average f f* is 1.02E-2 (Wang 2003 [DIRS 161654], SN-LBNL-SCI-215-V1, pp. 48 to 49). 
Smg (0.1) is calculated from the average matrix water saturation within tsw34 
(DTN: MO0109HYMXPROP.001 [DIRS 155989]). The value for Dm is calculated from 
Equation 6-17. D0 (2.65E-5 m2/s) is determined from the TOUGH Users Guide (Pruess 1987 
[DIRS 100684], pp. 5 to 6): 
D 0 
. T + 15.273 .. 
D0 = va.. (Eq. 6-24) 
P . 15.273 . 
with the diffusion coefficient in the air, Dva0 = 2.3E-5 m2/s and . =1.80 for a temperature (T) of
 
20 C and an air pressure (P) of 1 bar. The tortuosity for the gas tracer is estimated from the well-
known relation of Millington and Quirk (1961 [DIRS 139143]): 
.
3 7 
/ 
g
t= 
f 2 (Eq. 6-25) 
m 
where . g = f mSmg is the volumetric gas content in the matrix. Substituting the determined 
parameter values (including the average t0.5 and f f* values) into the right hand of Equation 6-23 
yields: 
ff 
= 83.0 (Eq. 6-26) 
*
f f 
This factor is used to consider the effects of matrix diffusion (on average) by multiplying the 
porosity estimates in DTN: LB980912332245.002 [DIRS 105593] by the factor value of 0.83. 
The resultant average fracture porosity for tsw34 is 0.0085, and the corresponding standard 
deviation is 2.5E-3. This porosity value is used in Equation 6-12 for determining fracture 
porosities in other UZ Model layers. The final fracture-porosity estimates are given in Table 6-5. 
Note that uncertainty exists in the estimated porosity value (Equation 6-26). However, it is 
difficult to quantify this uncertainty for the given data because site-specific parameter values for 
calculating this ratio are not available for a tracer test. Nevertheless, as shown in Section 6.1.3.4, 
the fracture porosity values estimated using Equation 6-26 are reasonable compared with values 
determined from other sources in the UZ and from other sites. 
ANL-NBS-HS-000042 REV 00 6-20 October 2004 

Analysis of Hydrologic Properties Data 
6.1.3.4 Comparisons with Fracture Porosities Estimated from Other Sources 
To demonstrate the reasonableness of the fracture porosity estimates (given in Table 6-5), these 
estimates were compared with those determined from other sources in the UZ and from other 
sites (as fracture analogues). 
 Fracture porosities were also estimated from water content-data calculated from water 
travel times observed from water-release tests in the Tptpmn (tsw34) of the UZ 
(DTNs: LB980901233124.003 [DIRS 105592]; LB0110LIQR0015.001 
[DIRS 156907]). The mean value of the estimates is ff = 0.018 and the standard 
deviation is 0.014. 
 Seepage Calibration Model and Seepage Testing Data (BSC 2004 [DIRS 171764], 
Section 6.6.3.3) reports fracture porosity estimates (0.7 percent) obtained by inversion of 
the seepage data collected in the Tptpmn unit. The mean and standard deviation are 
0.011 and 0.008, respectively. 
 Fracture porosity was estimated from gas pressure data collected from Apache Leap 
Research Site (Neuman et al. 2001 [DIRS 160849], p. 320). The estimated mean and 
standard deviation are 0.014 and 0.0017, respectively. 
 Fracture porosity for a fractured chalk formation, estimated using inversion modeling of 
a tracer test, was 0.003 (National Research Council 1996 [DIRS 139151], p. 293). 
 Fracture porosities estimated from gas tracer tests in the northern Ghost Dance fault in 
the UZ range were from 0.001 to 0.07 (LeCain et al. 2000 [DIRS 144612], Table 18). 
 Estimates based on water travel times observed from water-release tests in Tptpll 
(tsw35) were 0.013 and 0.067. The smaller one of these porosity values is believed to 
mainly result from the fracture network rather than cavities (BSC 2004 [DIRS 170004], 
Section 6.11.3.1). This value is close to the current estimate for Tptpll (0.0096). 
 The calibrated fracture porosity, based on the Alcove 1 infiltration test data, was about 
0.028 (Liu et al. 2003 [DIRS 162470], Table 1). The test site is located in the upper 
portion of the TCw unit. The calibrated value was close to the current estimate for 
tcw11 (0.024) (Table 6-5). 
These fracture porosity values (obtained using different methodologies, based on different types 
of data and/or from different sites) are consistent with the current estimates (given in Table 6-5) 
that are on the order of 1 percent, indicating the reasonableness of these estimates. 
ANL-NBS-HS-000042 REV 00 6-21 October 2004 

Analysis of Hydrologic Properties Data 
6.2 MATRIX PROPERTIES 
Matrix properties include matrix permeability and van Genuchten (1980 [DIRS 100610]) 
parameters used to describe water retention and relative permeability relations. They were 
determined from laboratory measurements made on core samples from the UZ. Some boreholes 
from which core samples came are shallow, variously penetrating the TCw, PTn, and top 
portions of the TSw. Some deep boreholes from which core samples have been collected and 
analyzed for the entire depth are NRG-6, NRG-7a, SD-7, SD-9, SD-12, UZ-7a, UZ-14, and 
UZ#16. Six of these penetrate into the Calico Hills Formation, five penetrate into the Prow Pass 
Tuff, and one, SD-7, penetrates the Bullfrog and Tram Tuffs. Core samples have also been 
collected from portions of two other deep boreholes: SD-6 and WT#24. The associated DTNs 
and their use can be found in the description of the relevant Excel files in Appendix A of this 
report. 
Sample collection and laboratory measurement methodologies, as well as estimates of 
uncertainty, are described by Flint (1998 [DIRS 100033], pp. 11 to 19) and Rousseau et al. 
(1999 [DIRS 102097], pp. 125 to 153). Core samples are grouped and analyzed according to the 
hydrogeologic units characterized by Flint (1998 [DIRS 100033], pp. 19 to 46) and detailed in a 
Scientific Notebook (Wang 2003 [DIRS 161654], SN-LBNL-SCI-003-V2, pp. 57 to 83). 
Table 6-1 shows these hydrogeologic units in relation to the lithostratigraphy of GFM2000 and 
the UZ Model layers. 
The calculation of matrix properties is described in a scientific notebook (Wang 2003 
[DIRS 161654], SN-LBNL-SCI-003-V2, pp. 57 to 83). Calculated matrix properties are given in 
Table 6-6. The Excel files used to perform these calculations are listed and described in 
Appendix A. The matrix porosity and permeability values are calculated with hydroprops_fin.xls 
(Appendix A). The unsaturated hydraulic properties are calculated with MRC_Q_TCw_fin.xls, 
MRC_Q_PTn_fin.xls, MRC_Q_TSw_fin.xls, MRC_Q_CHCF_fin.xls, vG_Summary_fin.xls, and 
PV2 deep borehole data.xls (Appendix A). 
ANL-NBS-HS-000042 REV 00 6-22 October 2004 

Analysis of Hydrologic Properties Data 
Table 6-6. Matrix Properties Developed from Core Data 
HGU f s N SE 
Upscaled 
k 
[m2] 
Upscaled 
log(k) 
[log(m2)] slog(k) NNd SElog(k) 
1/a 
[Pa] 
log(1/a) 
[log(Pa)] SElog(1/a) m SE Sr . SE 
CCR & CUC 0.241 0.073 124 0.007 4.7E-15 -14.33 0.47 3 0 0.27 8.27E+4 4.918 0.279 0.388 0.085 0.02 3.47 17.88 
CUL & CW 0.088 0.032 694 0.001 6.4E-20 -19.20 2.74 15 25 0.43 5.46E+5 5.737 0.178 0.280 0.045 0.20 12.29 19.35 
CMW 0.200 0.055 96 0.006 1.8E-16 -15.74 2.38 5 1 0.97 2.50E+5 5.398 0.188 0.259 0.042 0.31 6.08 0.00 
CNW 0.387 0.069 104 0.007 4.0E-14 -13.40 2.05 10 0 0.65 2.03E+4 4.308 0.199 0.245 0.032 0.24 -2.58 0.33 
BT4 0.428 0.100 58 0.013 4.1E-13 -12.39 1.41 11 0 0.43 4.55E+3 3.658 0.174 0.219 0.019 0.13 -0.26 1.17 
TPY 0.233 0.057 39 0.009 1.3E-15 -14.90 0.64 2 0 0.46 7.63E+4 4.883 0.379 0.247 0.064 0.07 3.46 16.73 
BT3 0.413 0.082 73 0.010 1.3E-13 -12.87 1.09 11 1 0.31 8.90E+3 3.950 0.088 0.182 0.008 0.14 -0.56 0.49 
TPP 0.498 0.041 159 0.003 1.1E-13 -12.96 0.39 11 0 0.12 2.12E+4 4.325 0.104 0.300 0.023 0.06 0.26 0.42 
BT2 0.490 0.095 176 0.007 6.7E-13 -12.17 1.12 21 0 0.24 1.74E+4 4.239 0.170 0.126 0.013 0.05 -2.64 0.67 
TC 0.054 0.036 75 0.004 4.4E-17 -16.36 3.02 6 5 0.91 2.71E+5 5.432 0.310 0.218 0.054 0.21 6.14 17.21 
TR 0.157 0.030 449 0.001 3.2E-16 -15.50 0.94 46 1 0.14 9.43E+4 4.974 0.116 0.290 0.025 0.07 5.00 17.49 
TUL 0.155 0.030 438 0.001 2.8E-17 -16.56 1.61 37 12 0.23 1.75E+5 5.244 0.111 0.283 0.024 0.12 7.06 17.98 
TMN 0.111 0.020 277 0.001 4.5E-19 -18.34 0.97 74 35 0.09 1.40E+6 6.147 0.108 0.317 0.042 0.19 10.90 19.28 
TLL 0.131 0.031 502 0.001 3.7E-17 -16.44 1.65 51 24 0.19 6.01E+4 4.779 0.521 0.216 0.061 0.12 6.27 17.23 
TM2 & TM1 0.103 0.025 298 0.001 2.3E-20 -19.63 3.67 21 42 0.46 3.40E+6 6.532 0.097 0.442 0.073 0.20 14.48 21.25 
PV3 0.043 0.040 125 0.004 2.9E-18 -17.54 1.57 16 2 0.37 1.00E+6 6.000 0.278 0.286 0.065 0.42 9.04 18.53 
PV2a 0.275 0.096 13 0.027 a a a a a a 2.17E+5 5.336 0.156 0.059 0.007 0.36 5.03 15.63 
PV2v 0.229 0.132 40 0.021 4.3E-13 -12.37 1.38 16 0 0.34 1.94E+4 4.287 0.042 0.293 0.011 0.13 -0.19 0.23 
BT1a 0.285 0.051 46 0.008 3.5E-17 -16.45 2.74 9 1 0.87 4.72E+6 6.674 0.183 0.349 0.073 0.38 7.39 18.61 
BT1v 0.331 0.091 76 0.010 2.1E-13 -12.67 1.11 35 0 0.19 1.35E+4 4.131 0.049 0.240 0.008 0.06 -2.07 0.23 
CHV 0.346 0.049 130 0.004 1.6E-12 -11.81 1.62 46 0 0.24 3.39E+3 3.530 0.094 0.158 0.008 0.06 -3.80 0.23 
CHZ 0.322 0.048 520 0.002 5.2E-18 -17.28 0.91 99 17 0.08 4.45E+5 5.649 0.094 0.257 0.022 0.26 8.30 18.10 
BTa 0.271 0.046 73 0.005 8.2E-19 -18.08 2.05 9 8 0.50 6.42E+6 6.808 0.043 0.499 0.036 0.36 11.87 21.01 
BTv b b b b b b b b b b 5.04E+4 4.703 0.207 0.147 0.020 b -0.87 14.77 
PP4 0.321 0.047 52 0.006 1.5E-16 -15.81 2.74 6 2 0.97 5.00E+5 5.699 0.401 0.474 0.224 0.29 7.13 19.55 
PP3 0.318 0.032 168 0.002 6.4E-15 -14.20 0.75 51 0 0.11 1.32E+5 5.120 0.084 0.407 0.031 0.08 3.37 18.01 
PP2 0.221 0.058 127 0.005 5.4E-17 -16.27 1.18 34 3 0.19 6.22E+5 5.794 0.147 0.309 0.041 0.10 6.69 18.09 
PP1 0.297 0.043 280 0.003 8.1E-17 -16.09 1.52 27 1 0.29 1.13E+5 5.052 0.234 0.272 0.036 0.30 6.05 17.63 
BF3/TR3 0.175 0.104 126 0.009 1.1E-15 -14.95 1.64 7 1 0.58 8.94E+4 4.951 0.931 0.193 0.117 0.11 3.11 16.20 
BF2 0.234 0.049 40 0.008 c c c c c c 8.46E+6 6.927 0.032 0.617 0.070 0.21 8.86 21.17 
Output DTN: LB0207REVUZPRP.002. 
a 
BT1a was used as an analog for permeability because only one permeability data point is available for PV2a. 
b 
BT1v was used as an analog for porosity, residual saturation, and permeability because only one sample is available for BTv. 
PP1 was used as an analog for permeability because only one measurable permeability data point is available for BF2. 
k is permeability.
s is standard deviation. 
n is number of samples. 
f is porosity.
Nd is number of samples with undetectable permeability measurements.
a is fitting parameters for the van Genuchten water potential relationship. 
m 
is fitting parameters for the van Genuchten water potential relationship. 
SE is standard error. 
is residual liquid saturation.
Sr 
. is defined in Equation 6-34. Relation between HGU and UZ model layers is given in Table 6-2. 
HGU=hydrogeologic units. 
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Analysis of Hydrologic Properties Data 
6.2.1 Matrix Permeability 
Matrix permeability was measured on core samples from several boreholes (including SD-6 and 
WT#24) at Yucca Mountain. Measurements are available for layers from the CUC down to the 
BF2 (Table 6-6). Two different permeameters were used to measure permeability, with the 
detection limit of the first higher than the second. Most of the samples were tested using the first 
permeameter; the second was used to test some new samples and retest some old samples 
originally tested using the first permeameter, including some with permeabilities too low to 
measure (nondetect results). When the same sample was tested on both permeameters, the 
permeability measured on the one with the lower detection limit was used since it was expected 
to result in a more reliable measurement. 
The measured data are presented in terms of saturated hydraulic conductivity (m/s), K, which is 
converted to permeability (m2), k, by the following relationship: 
w
k =K 
(Eq. 6-27) 
g.
w 
where w is the viscosity of water (0.001 N s/m2), g is the acceleration of gravity (9.81 m/s2), and 
.w is the density of water (998 kg/m3). These parameter values correspond to a temperature of 
25C (a typical room temperature at which the hydraulic conductivities were measured) 
(Lide 2002 [DIRS 160832], p. 6-3). 
Permeability is considered to be a lognormally-distributed quantity (Gelhar 1993 
[DIRS 101388], p. 2). Therefore, the geometric mean was used to represent the average 
permeability of each model layer. The standard deviation of the log-transformed permeabilities, 
log(k), is used as the basis for uncertainty, which is detailed below. Where there are no 
nondetect measurements in the data set for a layer, the calculation of the average and standard 
deviation of the data is simple. When nondetect measurements are present, they must be taken 
into account, because they may represent important information about the extent of the 
lognormal distribution below the detection limit. They are taken into account as follows: 
 Data points, including nondetects, are ranked and assigned a percentile. 
 The data points are fitted to a lognormal distribution, based on their percentile ranking. 
The fitting parameters are kg, the geometric mean of the permeability data, and slog(k), 
the standard deviation of the log-transformed permeability data. 
The geometric mean permeabilities calculated above represent the average behavior of the 
core-scale samples. For a given model layer, this averaged permeability can be very different 
from the effective matrix permeability used to represent large-scale water flow and solute 
transport due to scale effects (e.g., Paleologos et al. 1996 [DIRS 105736], Figure 4, p. 1337). 
While many upscaling methods are available in the literature, one method for highly 
ANL-NBS-HS-000042 REV 00 6-24 October 2004 

Analysis of Hydrologic Properties Data 
heterogeneous porous media is described by the following expression (Paleologos et al. 1996 
[DIRS 105736], p. 1336): 
2
k =k exp[sln(k )( 
21 
-D ) ] (Eq. 6-28) 
eg 
where ke is the effective permeability, kg is the geometric mean of small (core) scale 
permeability, sln(k)
2 is the variance of the natural log-transformed permeability, and D is a 
function of spatial dimensions (e.g., 2-D and 3-D) and the correlation scale of ln(k). Note that 
the geometric mean permeability is not the same as the effective permeability in a general case. 
For a 3-D isotropic problem, D = 1/3 when the characteristic size of a flow domain under 
consideration (say, a model layer) is much larger than the correlation length (Paleologos et al. 
1996 [DIRS 105736], p. 1336). For a site-scale model layer, these conditions are approximately 
satisfied. In this case, Equation 6-28 can be rewritten as: 
2
log(ke )=log(kg )+38.0 slog() (Eq. 6-29) 
k 
where slog(k)
2 is the variance of the log-transformed permeability. 
In these layers, the amount of upscaling predicted by Equation 6-28 is as large as five orders of 
magnitude. An upper limit of 1.5 orders-of-magnitude upscaling is imposed on layers CUL and 
CW, CMW, CNW, TC, TM2 and TM1, and BT1a and PP4 (Assumption 2, Section 5). For other 
layers, the amount of upscaling predicted by Equation 6-28 is less than 1.5 orders of magnitude. 
Use of this limiting scheme is based mainly on the following consideration: Equation 6-28 was 
developed for a porous medium (single continuum) and can only be considered as an 
approximation for a dual-continuum system. For example, the existence of fractures, which may 
act as a capillary barrier, can increase tortuosity of liquid water flow in the matrix and therefore 
reduce the effective permeability compared to the case without fractures. This situation is not 
considered in Equation 6-28. 
6.2.2 Porosity 
Matrix porosity was also measured on core samples from the UZ. Porosity was determined after 
drying samples in a 105C oven for at least 48 hours to obtain a standard dry weight (Flint 1998 
[DIRS 100033], p. 17). Porosity is considered a normally distributed quantity, so the arithmetic 
mean of core measurements and standard deviation were used to characterize the porosity for a 
model layer. 
6.2.3 Matrix van Genuchten Parameters 
The relationships described by van Genuchten (1980 [DIRS 100610], pp. 892 to 893) were used 
to characterize unsaturated flow in the matrix of Yucca Mountain. Use of the water-potential-
versus-saturation relationship allows the prediction of the relative permeability relationship. The 
predicted relative permeability is compared with permeability data where available. 
The van Genuchten parameters are Ss (satiated saturation), Sr (residual saturation), a, and m. 
Satiated saturation is set to be 1.0 because residual gas saturation in the UZ is negligible. 
Residual saturation is calculated based on two porosity measurements as described below. With 
ANL-NBS-HS-000042 REV 00 6-25 October 2004 

Analysis of Hydrologic Properties Data 
satiated and residual saturation fixed, a and m are adjusted to fit water potential and saturation 
data. 
6.2.3.1 Residual Saturation 
Residual saturation was determined from relative humidity (RH) porosity and total porosity. RH 
porosity was measured after drying a sample for 48 hours in a 60C and 65 percent relative 
humidity oven. This process is designed to remove water from the pores that contributes to flow, 
leaving only bound water and water in the smallest pores (Flint 1998 [DIRS 100033], p. 17). 
Layer average values for RH porosity are calculated in the same manner as total porosity (see 
Section 6.2.2). The layer average values of RH porosity are subtracted from the layer average 
values of total porosity to provide an estimate of residual water content (i.e., the amount of water 
left in the pores and bound to the minerals after relative permeability (or hydraulic conductivity) 
has been reduced to zero). Residual saturation was calculated by dividing the residual water 
content by total porosity. 
6.2.3.2 Matrix a and m 
Desaturation data (water potential and saturation) from a number of samples (at least one for 
each layer) were measured while a core sample was drying. DTNs associated with these data 
and their uses are given in descriptions of Excel files MRC_Q_TCw_fin.xls, 
MRC_Q_PTn_fin.xls, MRC_Q_Tsw_fin.xls, and MRC_Q_CHCF_fin.xls (Appendix A of this 
report). These data were used to calculate the a and m parameters for each layer by fitting to 
Equation 6-8. The best-fit parameters were obtained by minimizing the sum of the squared 
saturation residuals: 
nn ( 
2
. ri2 = .( Si - S.)) (Eq. 6-30) 
i
i = 1i = 1 
where ri is a saturation residual, n is the number of saturation and water potential data pairs for a 
layer, Si is a saturation data point, and S(. i) is the saturation predicted by the van Genuchten 
relationship for water potential, . i. 
The uncertainty or standard error of a and m is given by the diagonal terms of the covariance 
matrix: 
- 1 
C = s0 
2 ( JTJ ) (Eq. 6-31) 
where C is the covariance matrix, s02 is the error variance, J is the Jacobian matrix, and JT 
denotes the transpose of the matrix J. It should be noted that standard error, SE, can be related to 
the standard deviation, s , which is given for other properties, by: 
SE =s (Eq. 6-32) 
N 
where N is the number of samples. 
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Analysis of Hydrologic Properties Data 
6.2.4 Matrix Relative Permeability 
DTNs associated with data (used for calculating relative permeability) and their uses are given in 
descriptions of Excel files MRC_Q_TCw_fin.xls, MRC_Q_PTn_fin.xls, MRC_Q_Tsw_fin.xls, 
MRC_Q_CHCF_fin.xls, and VG_Summary_fin.xls (Appendix A of this report). According to 
van Genuchten (1980 [DIRS 100610], p. 893), relative permeability (kr) can be related to 
effective water saturation (Se) as: 
m 2
Sk =
1/2 1/ m )] }
{[1- (1- S (Eq. 6-33) 
re e 
However, recent studies indicate that a more general expression for relative permeability is 
(Schaap and Leij 2000 [DIRS 160841], pp. 843 to 844): 
m 2
1/ m )] }
k = S .{ [1- (1- S (Eq. 6-34) 
re e 
where . is an empirical constant. Many studies show that . is not 0.5, as assumed by the 
standard van Genuchten (1980 [DIRS 100610]), but varies over quite a large range (Schaap and 
Leij 2000 [DIRS 160841], pp. 843 to 844). This is consistent with the matrix relative 
permeability data collected from the UZ. 
To determine an . estimate for a UZ model layer, the following equation was used to fit the 
unsaturated conductivity (K) data collected within the model layer: 
m 2
( 
1/ m )] }
S K ) S .{[1- (1- S 
(Eq. 6-35) 
ee e
= 
1/ m ]m }2
S K 0)
( S0 
.{[1- (1- S0) 
K(S0) is the conductivity at a saturation S0, which is selected to be close to one. Equation 6-35 is 
derived by writing Equation 6-34 for a general value of Se and for Se=S0. The fitted .values 
are reported in Table 6-6 for different model layers (Wang 2003 [DIRS 161654], 
SN-LBNL-SCI-003-V2, pp. 63 to 83). They range from 2.64 to 14.48, which are consistent 
with those cited by Schaap and Leij (2000 [DIRS 160841], p. 844). Note that directly fitted . 
values are available only for hydrogeologic units CMW, CNW, BT4, BT3, TPP, BT2, PV2v, 
BT1v, and CHV where unsaturated hydraulic conductivity data are collected (Table 6-6). For 
other units, the following empirical relation is used to estimate the . values: 
.= Am - B log(k ) + C (Eq. 6-36) 
and the corresponding standard errors are estimated by: 
SE.= SEAm - SEB log(k ) + SEC (Eq. 6-37) 
where k is absolute permeability and A (8.14), B (1.99), and C (-28.24) are empirical parameters 
determined by fitting Equation 6-36 to . values for hydrogeologic units CMW, CNW, BT4, 
BT3, TPP, BT2, PV2v, BT1v and CHV where unsaturated hydraulic conductivity data are 
ANL-NBS-HS-000042 REV 00 6-27 October 2004 

Analysis of Hydrologic Properties Data 
collected (Wang 2003 [DIRS 161654], SN-LBNL-SCI-003-V2, pp. 63 to 83). SEA, SEB, and SEC 
are the standard errors for A, B, and C, respectively, and determined from the curve fitting (Wang 
2003 [DIRS 161654], SN-LBNL-SCI-003-V2, p. 82). Values calculated from Equations 6-36 
and 6-37 are reported in Table 6-6. 
A comparison between the currently obtained results based on Equation 6-34 and the van 
Genuchten relative permeability-saturation relation, Equation 6-33 can be easily made with: 
kr (Se ) = Se 
.-5.0 
(Eq. 6-38) 
kVG r (Se )
, 
where subscript VG refers to relative permeability obtained from the van Genuchten relation, 
Equation 6-33. Equation 6-38 is derived from Equations 6-33 and 6-34. Since estimated . 
values were very different from 0.5 for many model layers (Table 6-6), relative permeabilities 
predicted with standard van Genuchten relation, Equation 6-33, have considerable errors, 
especially for low saturations. The errors become insignificant for saturations close to one, 
which is the case for welded units under ambient conditions. Also, note that a large degree of 
uncertainty in estimated . values exists because of data limitations. Therefore, the standard van 
Genuchten relation is still used in flow and transport modeling studies of the UZ. 
6.3 FAULT PROPERTIES 
The UZ Model represents faults as having four layers defined by the major HGUs: TCw, PTn, 
TSw, and CHn/CFu. The constituent sublayers of these HGUs are shown in Table 6-1. Fault, 
fracture, and thermal properties are calculated for these four layers. Each HGU has been 
assumed to be approximately uniform within faults, because data to characterize faults are very 
limited. Matrix hydraulic properties in faults, however, are assigned the same values as those of 
the corresponding HGUs. 
Direct measurements of fault-specific properties were limited to air-injection tests performed in 
Alcoves 2, 6, and 7, which are also called the Bow Ridge fault alcove, the North Ghost Dance 
fault access drift, and the South Ghost Dance fault access drift, respectively. Analysis of 
crosshole tests run in the Bow Ridge fault alcove (LeCain 1998 [DIRS 100052], pp. 21 to 22) 
and the North Ghost Dance fault access drift (DTN: GS990883122410.002 [DIRS 135230]; 
LeCain et al. 2000 [DIRS 144612]) gave the best estimates of fracture permeability in the TCw 
and TSw fault layers, respectively. 
Other fault properties were calculated as averages of nonfault layers. Some layers are much 
thicker than others, and thus the properties of those layers should be weighted more heavily 
when calculating the fault properties. Properties were weighted by their respective average layer 
thickness. Porosity was arithmetically averaged because its differences between model layers 
within each HGU are not significant: 
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Analysis of Hydrologic Properties Data 
n 
. L p 
ii 
p = i=1 (Eq. 6-39) 
an 
. Li 
i=1 
where pa is the weighted arithmetic average property (porosity), n is the number of layers being 
averaged, pi is the property for layer i, and Li is the thickness of layer i. The fracture-matrix 
interface areas are also calculated using Equation 6-39. Because permeability is generally lognormally 
distributed (Gelhar 1993 [DIRS 101388], p. 2), a harmonic averaging method 
(Equation 6-38) is used to calculate the average permeability for each HGU: 
n 
. Li 
=p 
i=1 
(Eq. 6-40) 
hn 
. Li 
i=1 pi 
where ph is the weighted harmonic average property (permeability). Layer thickness is estimated 
as the average (arithmetic) layer thickness over the GFM2000 model 
(DTN: MO0012MWDGFM02.002 [DIRS 153777]) area. Another consideration for using 
Equation 6-40 is that it is exact when the flow direction is perpendicular to interfaces between 
model layers. This is approximately the case for the UZ, because the flow direction is mainly 
vertical. 
In principle, a more rigorous way to estimate the fault (fracture) properties is to correlate them 
with geologic information specific to each fault being modeled and to individual locations within 
each fault, such as amount of fault offset, width of the disturbed zone, and presence of contacts 
with significant property changes. This alternative approach, however, requires developing 
relationships between hydraulic properties and geologic information that cannot be reliably 
estimated with available data pertaining to fault properties. 
Fracture permeability for the TCw and TSw fault layers was derived from by the crosshole 
air-injection tests described above. Permeability for the PTn and CHn/CFu fault layers was 
calculated by scaling the weighted average bulk-rock fracture permeability. As with the fault 
matrix permeability, equivalent fracture permeability was calculated for all four fault layers 
using the weighted harmonic mean of permeabilities for the corresponding nonfault model 
layers. The average (geometric mean) ratio of the measured permeability to the calculated 
equivalent permeability for layers TCw and TSw was calculated (Ahlers 2000 [DIRS 155853], 
pp. 124 to 125). This factor multiplies the calculated equivalent permeability of the PTn and 
CHn/CFu layers to scale them upward. This process is equivalent to the process used to scale 
bulk-rock matrix a, which is explained in Section 6.2. 
Fracture spacing for each major HGU, equal to the inverse of fracture frequency, was calculated 
using the weighted arithmetic mean. Again, it can be shown that the weighted arithmetic mean of 
1/pi is equal to the harmonic mean of pi, so the weighted harmonic mean of frequency is used to 
calculate the equivalent frequency for the faults. 
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Analysis of Hydrologic Properties Data 
Fault fracture aperture was calculated as in Section 6.1.2 (using Equation 6-7), based on the 
cubic law and the fault permeabilities and frequencies. 
Fault fracture porosity was determined by scaling the weighted arithmetic mean of bulk-rock 
fracture porosity, with the scaling factor, the ratio of the above fault fracture aperture to mean 
bulk-rock fracture aperture. The mean bulk-rock fracture aperture was calculated as the weighted 
arithmetic average of fracture aperture. 
The fracture van Genuchten m (mf) is taken as 0.633 as for other fractures (see Section 6.1). The 
fracture van Genuchten a(af) is calculated based on the fracture aperture, using Equation 6-9 as 
documented in Section 6.1.2. 
The fracture-to-matrix connection area for the faults was approximated as the weighted 
arithmetic mean of the bulk-rock fracture-to-matrix connection area. The rationale for the 
development of fault properties is documented in a Scientific Notebook (Ahlers 2000 
[DIRS 155853], pp. 117 to 127, 145 to 146). Table 6-7 presents the calculated fault fracture 
properties. 
Table 6-7. Calculated Fault Fracture Properties 
Permeability Porosity Frequency Interface area 
Major Unit Fault Layer (m2) (-) (m-1) af (Pa-1)mf (-) (m2/m3) 
TCw tcwf 2.7E-11 2.9E-2 1.9 3.8E-3 0.633 12.9 
PTn ptnf 3.1E-12 1.1E-2 0.54 2.8E-3 0.633 1.3 
TSw tswf 1.5E-11 2.5E-2 1.7 3.2E-3 0.633 8.7 
CHn/CFu chnf 3.7E-13 1.0E-3 0.13 2.3E-3 0.633 0.46 
Output DTN: LB0207REVUZPRP.001. 
CFu=Crater Flat undifferentiated hydrogeologic unit; CHn=Calico Hills nonwelded hydrogeologic unit; 
PTn=Paintbrush nonwelded hydrogeologic unit; TCw=Tiva Canyon welded hydrogeologic unit; 
TSw=Topopah Spring welded hydrogeologic unit 
6.4 UNCERTAINTIES, ALTERNATIVE APPROACHES, AND OTHER ISSUES 
Uncertainties of most of these properties are reported using the corresponding standard 
deviations or standard errors (e.g., Tables 6-4 to 6-6) while some properties are subject to 
additional uncertainties due to lack of measured data in certain rock units. Alternative values 
from different sources have been used to verify the estimated properties (Section 6.1.3.4), and 
alternative approaches have been used to provide alternative parameter set (Section 6.2.4). As 
indicated in Section 1, these properties are uncalibrated and intended to serve only as initial 
estimates for the Calibrated Properties Model (BSC 2004 [DIRS 169857]). 
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Analysis of Hydrologic Properties Data 
7. CONCLUSIONS 
7.1 SUMMARY 
Methodologies have been described for providing representative estimates of fracture and matrix 
properties for UZ Model layers, based on the relevant data. The fracture and matrix properties 
developed here were submitted to the TDMS under Output DTNs: LB0205REVUZPRP.001 and 
LB0207REVUZPRP.002, respectively. The supporting data files for developing the fracture 
properties were submitted to the TEMS under Output DTN: LB0408REVUZPRP.001. Fault 
properties developed here were submitted to the TDMS under Output DTN: 
LB0207REVUZPRP.001. Estimated properties are documented in this report for use as prior 
information for the inversion processes within a model report, Calibrated Properties Model 
(BSC 2004 [DIRS 169857]). The resultant fracture geometry properties are important inputs for 
the development of the UZ Model grids. The independent determination of fracture properties, 
based on ESF seepage test results, confirms the appropriateness of the estimated fracture 
properties and the procedures used for the estimation. 
Like many field-scale problems, data availability and limitations in approaches for upscaling 
flow parameters directly from small-scale measurements are major sources of uncertainties in the 
estimated hydraulic properties. It is particularly true for the unsaturated fractured rocks, due to 
the complexity of the flow processes involved. To reduce the uncertainties, model calibrations 
are generally needed. Therefore, it should be emphasized that flow parameter estimates reported 
herein are only developed as inputs into model calibrations, and should not be directly used for 
modeling UZ flow and transport processes without careful evaluation. 
Output DTNs from this report are LB0205REVUZPRP.001, LB0207REVUZPRP.001, 
LB0207REVUZPRP.002, and LB0408REVUZPRP.001. Calibration is discussed in a separate 
model report describing the Calibrated Properties Model (BSC 2004 [DIRS 169857]. 
7.2 HOW THE APPLICABLE ACCEPTANCE CRITERIA ARE ADDRESSED 
The following information describes how this analysis addresses the hydrologic aspects of the 
following acceptance criteria in the Yucca Mountain Review Plan (NRC 2003 [DIRS 163274], 
Section 2.2.1.3.6.3). As stated in Section 4.2, only those acceptance criteria that are applicable 
to this report are discussed. In most cases, the applicable acceptance criteria are not addressed 
solely by this report; rather, the acceptance criteria are fully addressed when this report is 
considered in conjunction with other analysis and model reports that describe flow in the 
unsaturated zone. Where a subcriterion includes several components, only some of those 
components may be addressed. How these components are addressed is summarized below. 
Acceptance Criteria from Section 2.2.1.3.6.3, Flow Paths in the Unsaturated Zone 
Acceptance Criterion 1: System Description and Model Integration Are Adequate. 
Subcriterion (1): Important physical phenomena (i.e., the special flow patterns caused by 
existing of fractures and faults) relating to UZ flow are incorporated by the generation of fracture 
properties (Section 6.1), matrix properties (Section 6.2), and fault properties (Section 6.3) 
provided in this report. This information feeds into the calibrated properties model that provides 
the input for process models and TSPA simulations. 
ANL-NBS-HS-000042 REV 00 7-1 October 2004 

Analysis of Hydrologic Properties Data 
Subcriterion (2): The data synthesized in Sections 6.1, 6.2, and 6.3 of this report adequately 
describe properties of the UZ that affect flow in the fractures and matrix of the unsaturated zone. 
Fracture properties are based upon air-injection tests, gas tracer tests, borehole data, and a survey 
of fracture data (Section 6.1). Matrix properties are based upon laboratory measurements on 
core samples (Section 6.2). Fracture permeability for faults are based on air-injection tests and 
other fracture properties are based on averages of properties of the corresponding non-fault layer 
(Section 6.3). These values are averaged for each hydrologic unit (for the major HGUs in the 
case of the faults). These properties are uncalibrated and serve only as initial estimates in the 
calibrated properties model that provides the input for the process model and TSPA simulations. 
The inverse modeling helps to ensure that the calibrated values for each hydrologic unit are 
appropriate for the UZ model. 
Subcriterion (3): Technical bases and data (e.g., separation of fracture-flow and matrix flow) 
employed in this analysis are appropriate and consistently applied in developing related 
abstractions. In particular, information about fracture and matrix properties from this analysis 
feeds into the calibrated properties model that provides the input for TSPA simulations. 
Subcriterion (7): As shown in Section 6, Table 6-1, the hydrologic units used in this report for 
calculating the average parameters (in this case, parameters related to spatial discretizations in 
the UZ) are consistent with those used in the site-scale flow model. 
Subcriterion (9): This report was developed in accordance with the Quality Assurance 
Requirements and Description (QARD) (DOE 2004 [DIRS 171539]), which commits to 
NUREG-1297 (Altman et al. 1988 [DIRS 103597]) and NUREG-1298 (Altman et al. 1988 
[DIRS 103750]). Moreover, compliance with the DOE procedures, which are designed to ensure 
compliance with the QARD (DOE 2004 [DIRS 171539]), is verified by audits by QA and other 
oversight activities. Accordingly, the guidance in NUREG-1297 (Altman et al. 1988 [DIRS 
103597]) and NUREG-1298 (Altman et al. 1988 [DIRS 103750]) has been followed as 
appropriate. 
Acceptance Criterion 2: Data Are Sufficient for Model Justification. 
Subcriterion (1): Sections 6.1 through 6.3 of this report provide adequate descriptions of the 
scientific basis and the methodologies (e.g., air-injection tests and gas-tracer tests) for 
appropriate synthesis of measured data into hydrological parameters. 
Subcriterion (2): The quality of the data used in this report is assured by the QA program 
(Section 2). Approved QA procedures identified in the TWP (BSC 2004 [DIRS 169654], 
Section 4) have been used to conduct and document the activities described in this analysis 
report. 
Acceptance Criterion 3: Data Uncertainty is Characterized and Propagated Through the 
Model Abstraction. 
Subcriterion (6): Uncertainties of most of the hydrologic properties are reported using the 
corresponding standard deviations or standard errors (e.g., Tables 6-4 to 6-6). Alternative values 
from seven different sources were used to verify the estimated fracture porosities 
(Section 6.1.3.4). 
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8. INPUTS AND REFERENCES 
8.1 DOCUMENTS CITED 
Ahlers, R. 2000. Unsaturated Zone Modeling & Synthesis. Scientific Notebook 155853
YMP-LBNL-GSB-1.1.2. ACC: MOL.20000726.0157. 
Altman, W.D.; Donnelly, J.P.; and Kennedy, J.E. 1988. Peer Review for High-Level 103597
Nuclear Waste Repositories: Generic Technical Position. NUREG-1297. 
Washington, D.C.: U.S. Nuclear Regulatory Commission. TIC: 200651. 
Altman, W.D.; Donnelly, J.P.; and Kennedy, J.E. 1988. Qualification of Existing 103750 
Data for High-Level Nuclear Waste Repositories: Generic Technical Position. 
NUREG-1298. Washington, D.C.: U.S. Nuclear Regulatory Commission. 
TIC: 200652. 
Bear, J.; Tsang, C.F.; and de Marsily, G., eds. 1993. . Flows and Contaminant 116773
Transport in Fractured Rock. San Diego, California: Academic Press. 
TIC: 235461. 
BSC (Bechtel SAIC Company) 2001. Analysis of Hydrologic Properties Data. 159725
ANL-NBS-HS-000002 REV 00 ICN 01. Las Vegas, Nevada: Bechtel SAIC 
Company. ACC: MOL.20020429.0296. 
BSC 2003. Analysis of Hydrologic Properties Data. MDL-NBS-HS-000014 REV 161773
00. Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20030908.0001. 
BSC 2004. Calibrated Properties Model. MDL-NBS-HS-000003, Rev. 02. Las 169857 
Vegas, Nevada: Bechtel SAIC Company. 
BSC 2004. Conceptual Model and Numerical Approaches for Unsaturated Zone 170035 
Flow and Transport. MDL-NBS-HS-000005 REV 01. Las Vegas, Nevada: Bechtel 
SAIC Company. 
BSC 2004. Development of Numerical Grids for UZ Flow and Transport Modeling. 169855 
ANL-NBS-HS-000015, Rev. 02. Las Vegas, Nevada: Bechtel SAIC Company. 
BSC 2004. Geologic Framework Model (GFM2000). MDL-NBS-GS-000002 REV 170029 
02. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20040827.0008. 
BSC 2004. In Situ Field Testing of Processes. ANL-NBS-HS-000005, Rev. 03. 170004 
Las Vegas, Nevada: Bechtel SAIC Company. 
BSC 2004. Q-List. 000-30R-MGR0-00500-000-000 REV 00. Las Vegas, Nevada: 168361 
Bechtel SAIC Company. ACC: ENG.20040721.0007. 
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Analysis of Hydrologic Properties Data 
BSC 2004. Seepage Calibration Model and Seepage Testing Data. MDL-NBS-HS-171764
000004 REV 03. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040922.0003. 
BSC 2004. Technical Work Plan for: Unsaturated Zone Flow Analysis and Model 169654
Report Integration. TWP-MGR-HS-000001 REV 00. Las Vegas, Nevada: Bechtel 
SAIC Company. ACC: DOC.20040701.0005. 
BSC 2004. Thermal Conductivity of the Potential Repository Horizon. MDL-NBS-169854
GS-000005, Rev. 01. Las Vegas, Nevada: Bechtel SAIC Company. 
Canori, G.F. and Leitner, M.M. 2003. Project Requirements Document. 166275
TER-MGR-MD-000001 REV 02. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20031222.0006. 
CRWMS (Civilian Radioactive Waste Management System) M&O (Management & 102679
Operating Contractor) 1998. Geology of the Exploratory Studies Facility Topopah 
Spring Loop. BAB000000-01717-0200-00002 REV 01. Las Vegas, Nevada: 
CRWMS M&O. ACC: MOL.19980415.0283. 
DOE (U.S. Department of Energy) 2004. Quality Assurance Requirements and 171539
Description. DOE/RW-0333P, Rev. 16. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20040907.0002. 
Domenico, P.A. and Schwartz, F.W. 1990. Physical and Chemical Hydrogeology. 100569
New York, New York: John Wiley & Sons. TIC: 234782. 
Flint, L.E. 1998. Characterization of Hydrogeologic Units Using Matrix Properties, 100033
Yucca Mountain, Nevada. Water-Resources Investigations Report 97-4243. 
Denver, Colorado: U.S. Geological Survey. ACC: MOL.19980429.0512. 
Freifeld, B.M. 2001. Estimation of Fracture Porosity in an Unsaturated Fractured 161806
Welded Tuff Using Gas Tracer Testing. Ph.D. thesis. Berkeley, California: 
University of California, Berkeley, Department of Civil and Environmental 
Engineering. TIC: 253904. 
Gelhar, L.W. 1993. Stochastic Subsurface Hydrology. Englewood Cliffs, New 101388
Jersey: Prentice-Hall. TIC: 240652. 
Hvorslev, M.J. 1951. Time Lags and Soil Permeability in Ground-Water 101868
Observations. AEWES Bulletin 36. Vicksburg, Mississippi: U.S. Army Corps of 
Engineers, Waterways Experiment Station. TIC: 238956. 
ANL-NBS-HS-000042 REV 00 8-2 October 2004 

Analysis of Hydrologic Properties Data 
Kazemi, H. and Gilman, J.R. 1993. Multiphase Flow in Fractured Petroleum 147209
Reservoirs. Chapter 6 of Flow and Contaminant Transport in Fractured Rock. 
Bear, J.; Tsang, C-F.; and de Marsily, G., eds. San Diego, California: Academic 
Press. TIC: 235461. 
LeCain, G.D. 1995. Pneumatic Testing in 45-Degree-Inclined Boreholes in Ash-101700
Flow Tuff Near Superior, Arizona. Water-Resources Investigations Report 95-4073. 
Denver, Colorado: U.S. Geological Survey. ACC: MOL.19960715.0083. 
LeCain, G.D. 1998. Results from Air-Injection and Tracer Testing in the Upper Tiva 100052 
Canyon, Bow Ridge Fault, and Upper Paintbrush Contact Alcoves of the Exploratory 
Studies Facility, August 1994 through July 1996, Yucca Mountain, Nevada. 
Water-Resources Investigations Report 98-4058. Denver, Colorado: 
U.S. Geological Survey. ACC: MOL.19980625.0344. 
LeCain, G.D.; Anna, L.O.; and Fahy, M.F. 2000. Results from Geothermal Logging, 144612 
Air and Core-Water Chemistry Sampling, Air-Injection Testing, and Tracer Testing 
in the Northern Ghost Dance Fault, Yucca Mountain, Nevada, November 1996 to 
August 1998. Water-Resources Investigations Report 99-4210. Denver, Colorado: 
U.S. Geological Survey. TIC: 247708. 
Lide, D.R., ed. 2002. CRC Handbook of Chemistry and Physics. 83rd Edition. 160832 
Boca Raton, Florida: CRC Press. TIC: 253582. 
Lin, M.; Hardy, M.P.; and Bauer, S.J. 1993. Fracture Analysis and Rock Quality 116797 
Designation Estimation for the Yucca Mountain Site Characterization Project. 
SAND92-0449. Albuquerque, New Mexico: Sandia National Laboratories. 
ACC: NNA.19921204.0012. 
Liu, H-H.; Haukwa, C.B.; Ahlers, C.F.; Bodvarsson, G.S.; Flint, A.L.; and Guertal, 162470 
W.B. 2003. "Modeling Flow and Transport in Unsaturated Fractured Rock: An 
Evaluation of the Continuum Approach." Journal of Contaminant Hydrology, 62-63, 
173-188. New York, New York: Elsevier. TIC: 254205. 
Millington, R.J. and Quirk, J.M. 1961. Permeability of Porous Solids. 139143 
Transactions of the Faraday Society, 57, (7), 1200-1207. Toronto, Canada: Royal 
Society of Chemistry. TIC: 246707. 
Moench, A.F. 1989. Convergent Radial Dispersion: A Laplace Transform 101146 
Solution for Aquifer Tracer Testing. Water Resources Research, 25, (3), 439-447. 
Washington, D.C.: American Geophysical Union. TIC: 238283. 
Montazer, P. and Wilson, W.E. 1984. Conceptual Hydrologic Model of Flow in the 100161 
Unsaturated Zone, Yucca Mountain, Nevada. Water-Resources Investigations Report 
84-4345. Lakewood, Colorado: U.S. Geological Survey. 
ACC: NNA.19890327.0051. 
ANL-NBS-HS-000042 REV 00 8-3 October 2004 

Analysis of Hydrologic Properties Data 
National Research Council. 1996. Rock Fractures and Fluid Flow, Contemporary 139151
Understanding and Applications. Washington, D.C.: National Academy Press. 
TIC: 235913. 
Neuman, S.P.; Illman, W.A.; Vesselinov, V.V.; Thompson, D.L.; Chen, G.; and 160849
Guzman, A. 2001. Lessons from Field Studies at the Apache Leap Research Site in 
Arizona. Chapter 10 of Conceptual Models of Flow and Transport in the Fractured 
Vadose Zone. Washington, D.C.: National Academy Press. TIC: 252777. 
NRC (U.S. Nuclear Regulatory Commission) 2003. Yucca Mountain Review Plan, 163274
Final Report. NUREG-1804, Rev. 2. Washington, D.C.: U.S. Nuclear Regulatory 
Commission, Office of Nuclear Material Safety and Safeguards. TIC: 254568. 
Paleologos, E.K.; Neuman, S.P.; and Tartakovsky, D. 1996. Effective Hydraulic 105736
Conductivity of Bounded, Strongly Heterogeneous Porous Media. Water 
Resources Research, 32, (5), 1333-1341. Washington, D.C.: American Geophysical 
Union. TIC: 245760. 
Pruess, K. 1987. TOUGH User's Guide. NUREG/CR-4645. Washington, D.C.: 100684
U.S. Nuclear Regulatory Commission. TIC: 217275. 
Pruess, K. and Tsang, Y.W. 1990. On Two-Phase Relative Permeability and 170866
Capillary Pressure of Rough-Walled Rock Fractures. Water Resources Research,
26, (9), 1915-1926. Washington, D.C.: American Geophysical Union. 
TIC: 224853. 
Renard, Ph. and de Marsily, G. 1997. Calculating Equivalent Permeability: A 170240
Review. Advances in Water Resources, 20, (5-6), 253-278. New York, New York: 
Elsevier. TIC: 256209. 
Rousseau, J.P.; Kwicklis, E.M.; and Gillies, D.C., eds. 1999. Hydrogeology of the 102097
Unsaturated Zone, North Ramp Area of the Exploratory Studies Facility, Yucca 
Mountain, Nevada. Water-Resources Investigations Report 98-4050. Denver, 
Colorado: U.S. Geological Survey. ACC: MOL.19990419.0335. 
Schaap, M.G. and Leij, F.J. 2000. Improved Prediction of Unsaturated Hydraulic 160841
Conductivity with the Mualem-van Genuchten Model. Soil Science Society of 
America Journal, 64, (3), 843-851. Madison, Wisconsin: Soil Science Society of 
America. TIC: 253607. 
Starr, R.C.; Gillham, R.W.; and Sudicky, E.A. 1985. Experimental Investigation of 101479
Solute Transport in Stratified Porous Media, 2. The Reactive Case. Water 
Resources Research, 21, (7), 1043-1050. Washington, D.C.: American Geophysical 
Union. TIC: 222358. 
ANL-NBS-HS-000042 REV 00 8-4 October 2004 

Analysis of Hydrologic Properties Data 
van Genuchten, M.T. 1980. A Closed-Form Equation for Predicting the Hydraulic 100610 
Conductivity of Unsaturated Soils. Soil Science Society of America Journal, 44, 
(5), 892-898. Madison, Wisconsin: Soil Science Society of America. TIC: 217327. 
Wang, J.S. 2003. Scientific Notebooks Referenced in Model Report U0090, 161654 
Analysis of Hydrologic Properties Data, MDL-NBS-HS-000014 REV 00 Interoffice 
correspondence from J.S. Wang (BSC) to File, February 28, 2003, with attachments. 
ACC: MOL.20030306.0535. 
Wang, J.S.Y. and Narasimhan, T.N. 1993. Unsaturated Flow in Fractured Porous 106793 
Media. Chapter 7 of Flow and Contaminant Transport in Fractured Rock. Bear, 
J.; Tsang, C-F.; and de Marsily, G., eds. San Diego, California: Academic Press. 
TIC: 235461. 
Wen, X-H. and Gmez-Hernndez, J.J. 1996. Upscaling Hydraulic Conductivities 170239 
in Heterogeneous Media: An Overview. Journal of Hydrology, 183, (1-2), 
ix-xxxii. New York, New York: Elsevier. TIC: 256208. 
Wu, Y-S.; Pan, L.; Zhang, W.; and Bodvarsson, G.S. 2002. Characterization of 160195 
Flow and Transport Processes within the Unsaturated Zone of Yucca Mountain, 
Nevada, Under Current and Future Climates. Journal of Contaminant Hydrology, 
54, (3-4), 215-247. New York, New York: Elsevier. TIC: 253316. 
Zhou, Q.; Liu, H-H.; Bodvarsson, G.S.; and Oldenburg, C.M. 2003. Flow and 162133 
Transport in Unsaturated Fractured Rock: Effects of Multiscale Heterogeneity of 
Hydrogeologic Properties. Journal of Contaminant Hydrology, 60, (1-2), 1-30. 
New York, New York: Elsevier. TIC: 253978. 
8.2 CODES, STANDARDS, REGULATIONS, AND PROCEDURES 
156605 10 CFR 63. Energy: Disposal of High-Level Radioactive Wastes in a Geologic 
Repository at Yucca Mountain, Nevada. 
AP-2.22Q, Rev. 1, ICN 1. Classification Analyses and Maintenance of the Q-List. Washington, 
D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20040714.0002. 
AP-3.15Q, Rev. 4, ICN 5. Managing Technical Product Inputs. Washington, D.C.: U.S. 
Department of Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20040812.0004. 
LP-SI.11Q-BSC, Rev. 0, ICN0. Software Management. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. ACC:DOC.20040225.0007. 
AP-SIII.9Q, REV.1, ICN 7. Scientific Analyses. Washington, D.C.: U.S. Department of Energy, 
Office of Civilian Radioactive Waste Management. ACC: DOC.20040920.0001. 
ANL-NBS-HS-000042 REV 00 8-5 October 2004 

Analysis of Hydrologic Properties Data 
8.3 SOURCE DATA, LISTED BY DATA TRACKING NUMBER 
GS000608314211.003. Stratigraphic Contact for 26 Yucca Mountain Boreholes. 161658
Submittal date: 04/09/2001. 
GS010608312242.001. Unsaturated Hydraulic Conductivity and Matric Potential in 160822
Busted Butte Volcanic Tuff Cores. Submittal date: 08/07/2001. 
GS940208314211.007. Table of Contacts in Borehole USW UZ-N35. 
Submittal date: 02/10/1994. 
GS940208314211.008. Table of Contacts in Boreholes USW UZ-N57, UZ-N58, 145581
UZ-N59, and UZ-N61. Submittal date: 02/10/1994. 
GS940308314211.018. Table of Contacts for the Tiva Canyon Tuff in Borehole 145589
USW UZ-N36. Submittal date: 03/28/1994. 
GS950108314211.008. Lithostratigraphic Data for Paintbrush Group Bedded Tuff 152558
Units TPBT3 and TPBT4 in Boreholes USW UZ-N11, USW UZ-14, USW NRG-
7/7A, USW SD-9, USW UZ-N37, USW NRG-6, UE-25 NRG#2B, USW UZ-N31, 
USW UZ-N32, USW SD-12, UE-25 UZ#16, USW UZ-N54, USW UZ-N53. 
Submittal date: 01/20/1995. 
GS950108314211.009. Stratigraphic Descriptions and Data for the Yucca Mountain 152556
Tuff in Boreholes NRG#2B, NRG-7/7A, SD-9, UZ-14, UZ#16, UZ-N11, UZ-N33, 
UZ-N34, UZ-N53, UZ-N54, UZ-N55. Submittal date: 01/27/1995. 
GS950608312231.008. Moisture Retention Data from Boreholes USW UZ-N27 and 144662
UE-25 UZ#16. Submittal date: 06/06/1995. 
GS950708314211.028. Stratigraphic Descriptions of the Pah Canyon Tuff in 160827
Boreholes UE-25 NRG #2B, UE-25 NRG#4, USW NRG-6, USW NRG-7/7A, USW
SD-9, USW SD-12, USW UZ-14, USW UZ-N31, USW UZ-N32, AND USW
UZ-N37. Submittal date: 07/20/1995. 
GS960708314224.008. Provisional Results: Geotechnical Data for Station 30 + 00 to 105617
Station 35 + 00, Main Drift of the ESF. Submittal date: 08/05/1996. 
GS960708314224.010. Provisional Results: Geotechnical Data for Station 40+00 to 106031
Station 45+00, Main Drift of the ESF. Submittal date: 08/05/1996. 
GS960808312231.003. Moisture Retention Data for Samples from Boreholes 147590
USW SD-7, USW SD-9, USW SD-12 and UE-25 UZ#16. Submittal date: 
08/30/1996. 
GS960808314224.011. Provisional Results: Geotechnical Data for Station 35+00 to 106029
Station 40+00, Main Drift of the ESF. Submittal date: 08/29/1996. 
ANL-NBS-HS-000042 REV 00 8-6 October 2004 

Analysis of Hydrologic Properties Data 
GS960908312232.013. Air-Injection Testing in Vertical Boreholes in Welded and 105574
Non-Welded Tuff, Yucca Mountain, Nevada. Submittal date: 09/26/1996. 
GS960908314224.014. Provisional Results - ESF Main Drift, Station 50+00 to 106033
Station 55+00. Submittal date: 09/09/1996. 
GS960908314224.018. Provisional Results: Geotechnical Data for Alcove 5 106067
(DWFA), Main Drift of the ESF. Submittal date: 09/09/1996.
GS960908314224.020. Analysis Report: Geology of the North Ramp -Stations 4+00 106059
to 28+00 and Data: Detailed Line Survey and Full-Periphery Geotechnical Map - 
Alcoves 3 (UPCA) and 4 (LPCA), and Comparative Geologic Cross Section - 
Stations 0+60 to 28+00. Submittal date: 09/09/1996. 
GS970183122410.001. Results from Air-Injection and Tracer Testing in the Upper 105580
Tiva Canyon, Bow Ridge Fault, and Upper Paintbrush Contact Alcoves of the 
Exploratory Studies Facility, August 1994 through July 1996, Yucca Mountain, 
Nevada. Submittal date: 02/03/1997.
GS970308314222.001. Fracture Data from Natural Outcrops of the Calico Hills 106075
Formation and the Topopah Spring Tuff at 10 Locations in the Vicinity of Prow Pass, 
at the Head of Yucca Wash, North of Yucca MTN, and 2 Locations at the NE End of 
Busted Butte, SE of Yucca MTN. Submittal date: 03/26/1997. 
GS970808314224.008. Provisional Results: Geotechnical Data for Station 65+00 to 106049
Station 70+00, South Ramp of the ESF. Submittal date: 08/18/1997. 
GS970808314224.010. Provisional Results: Geotechnical Data for Station 70+00 to 106050
Station 75+00, South Ramp of the ESF. Submittal date: 08/25/1997. 
GS970808314224.012. Provisional Results: Geotechnical Data for Station 75+00 to 106057
Station 78+77, South Ramp of the ESF. Submittal date: 08/25/1997. 
GS970808314224.014. Provisional Results: Geotechnical Data for Alcove 6 and 106069
Alcove 6 Drill Alcove, Main Drift of the ESF. Submittal date: 08/25/1997. 
GS971008312231.006. Physical Properties and Saturated Hydraulic Conductivity of 107184
Cores from Surface Samples from the ESF Main Drift 29+00 M to 57+00 M. 
Submittal date: 10/06/1997. 
GS971108314224.020. Revision 1 of Detailed Line Survey Data, Station 0+60 to 105561
Station 4+00, North Ramp Starter Tunnel, Exploratory Studies Facility. 
Submittal date: 12/03/1997. 
GS971108314224.021. Revision 1 of Detailed Line Survey Data, Station 4+00 to 106007
Station 8+00, North Ramp, Exploratory Studies Facility. Submittal date: 12/03/1997.
ANL-NBS-HS-000042 REV 00 8-7 October 2004 

Analysis of Hydrologic Properties Data 
GS971108314224.022. Revision 1 of Detailed Line Survey Data, Station 8+00 to 106009
Station 10+00, North Ramp, Exploratory Studies Facility. 
Submittal date: 12/03/1997. 
GS971108314224.023. Revision 1 of Detailed Line Survey Data, Station 10 + 00 to 106010
Station 18 + 00, North Ramp, Exploratory Studies Facility. 
Submittal date: 12/03/1997. 
GS971108314224.024. Revision 1 of Detailed Line Survey Data, Station 18+00 to 106023
Station 26+00, North Ramp, Exploratory Studies Facility. 
Submittal date: 12/03/1997. 
GS971108314224.025. Revision 1 of Detailed Line Survey Data, Station 26+00 to 106025
Station 30+00, North Ramp and Main Drift, Exploratory Studies Facility. 
Submittal date: 12/03/1997. 
GS971108314224.026. Revision 1 of Detailed Line Survey Data, Station 45+00 to 106032
Station 50+00, Main Drift, Exploratory Studies Facility. Submittal date: 12/03/1997.
GS971108314224.028. Revision 1 of Detailed Line Survey Data, Station 55+00 to 106047
Station 60+00, Main Drift and South Ramp, Exploratory Studies Facility. 
Submittal date: 12/03/1997. 
GS980308312242.005. Physical Properties of Lexan-Sealed Borehole Samples from 107165
the PTN Exposure in the ESF North Ramp (ESF Station 7+27 M to ESF Station 
10+70 M). Submittal date: 03/11/1998. 
GS980408312242.008. Unsaturated Hydraulic Properties of Borehole Samples from 107161
the PTN Exposure in the ESF North Ramp (ESF Station 7+27 M to ESF Station 
10+70 M) Measured Using a Centrifuge. Submittal date: 04/17/1998. 
GS980708312242.010. Physical Properties of Borehole Core Samples, and Water 106752
Potential Measurements Using the Filter Paper Technique, for Borehole Samples 
from USW WT-24. Submittal date: 07/27/1998.
GS980708312242.011. Physical Properties and Hydraulic Conductivity 107150
Measurements of Lexan-Sealed Samples from USW WT-24.
Submittal date: 07/30/1998. 
GS980808312242.012. Unsaturated Hydraulic Properties of Lexan-Sealed Samples 149375
From USW WT-24, Measured Using a Centrifuge. Submittal date: 08/05/1998. 
GS980808312242.014. Physical Properties of Borehole Core Samples and Water 106748
Potential Measurements Using the Filter Paper Technique for Borehole Samples from 
USW SD-6. Submittal date: 08/11/1998. 
ANL-NBS-HS-000042 REV 00 8-8 October 2004 

Analysis of Hydrologic Properties Data 
GS980908312242.037. Water Retention Data of Lexan-Sealed Borehole Samples 107180
and Surface Samples from ESF North Ramp Moisture Study. 
Submittal date: 09/23/1998. 
GS980908312242.038. Physical Properties and Saturated Hydraulic Conductivity 107154
Measurements of Lexan-Sealed Samples from USW SD-6. 
Submittal date: 09/22/1998. 
GS980908312242.039. Unsaturated Water Retention Data for Lexan-Sealed 145272
Samples from USW SD-6 Measured Using a Centrifuge. Submittal date: 09/22/1998. 
GS980908312242.040. Physical Properties and Saturated Hydraulic Conductivity 107169
Measurements of Core Plugs from Lexan-Sealed Samples from Boreholes in the ESF 
North Ramp. Submittal date: 09/24/1998. 
GS980908312242.041. Physical Properties and Saturated Hydraulic Conductivity 107158
Measurements of Core Plugs from Boreholes USW SD-7, USW SD-9, USW SD-12,
USW UZ-14, and UE-25 UZ#16. Submittal date: 09/24/1998. 
GS981108314224.005. Locations of Lithostratigraphic Contacts in the ECRB Cross 109070
Drift. Submittal date: 11/30/1998. 
GS990308312242.007. Laboratory and Centrifuge Measurements of Physical and 107185
Hydraulic Properties of Core Samples from Busted Butte Boreholes UZTT-BB-INJ-
1, UZTT-BB-INJ-3, UZTT-BB-INJ-4, UZTT-BB-INJ-6, UZTT-BB-COL-5 and 
UZTT-BB-COL-8. Submittal date: 03/22/1999.
GS990408314224.001. Detailed Line Survey Data for Stations 00+00.89 to 108396
14+95.18, ECRB Cross Drift. Submittal date: 09/09/1999. 
GS990408314224.002. Detailed Line Survey Data for Stations 15+00.85 to 105625
26+63.85, ECRB Cross Drift. Submittal date: 09/09/1999. 
GS990708312242.008. Physical and Hydraulic Properties of Core Samples from 109822
Busted Butte Boreholes. Submittal date: 07/01/1999. 
GS990883122410.002. Qualified Data in Results from Geothermal Logging, Air 135230
and Core-Water Chemistry Sampling, Air-Injection Testing and Tracer Testing in the
Northern Ghost Dance Fault, November, 1996 - August, 1998. 
Submittal date: 08/16/1999. 
LA0207SL831372.001. Lithostratigraphic Classification of Hydrologic-Property 160824
Core-Sampling Depths, Busted Butte Phase 2 Test Block. 
Submittal date: 07/16/2002. 
LAJF831222AQ98.014. Chloride, Bromide, and Sulfate Analyses of Salts Leached 160825
from ESF-NR-Moiststdy Drillcore. Submittal date: 09/09/1998. 
ANL-NBS-HS-000042 REV 00 8-9 October 2004 

Analysis of Hydrologic Properties Data 
LB0110LIQR0015.001. Developed Data for Liquid Release/Seepage Tests and 156907
Systematic Testing. Submittal date: 11/12/2001.
LB960500834244.001. Hydrological Characterization of the Single Heater Test Area 105587
in ESF. Submittal date: 08/23/1996. 
LB970600123142.001. Ambient Characterization of the ESF Drift Scale Test Area 105589
by Field Air Permeability Measurements. Submittal date: 06/13/1997. 
LB980120123142.004. Air Injections in Boreholes 57 through 61, 74 through 78, 105590
185 and 186 in the Drift Scale Test Area. Submittal date: 01/20/1998. 
LB980120123142.005. Hydrological Characterization by Air Injections Tests in 114134
Boreholes in Heated Drift in DST. Submittal date: 01/20/1998. 
LB980901233124.003. Liquid Release and Tracer Tests in Niches 3566, 3650, 3107, 105592
and 4788 in the ESF. Submittal date: 09/14/1998.
LB980912332245.002. Gas Tracer Data from Niche 3107 of the ESF. 105593
Submittal date: 09/30/1998. 
LB990501233129.001. Fracture Properties for the UZ Model Grids and Uncalibrated 106787
Fracture and Matrix Properties for the UZ Model Layers for AMR U0090, Analysis 
of Hydrologic Properties Data. Submittal date: 08/25/1999. 
LB990901233124.004. Air Permeability Cross-Hole Connectivity in Alcove 6, 123273
Alcove 4, and Niche 4 of the ESF for AMR U0015, In Situ Testing of Field 
Processes. Submittal date: 11/01/1999. 
MO0012MWDGFM02.002. Geologic Framework Model (GFM2000). 153777
Submittal date: 12/18/2000. 
MO0109HYMXPROP.001. Matrix Hydrologic Properties Data. 155989
Submittal date: 09/17/2001. 
MO0407SEPFEPLA.000. LA FEP List. Submittal date: 07/20/2004. 170760
TM000000SD12RS.012. USW SD-12 Composite Borehole Log (0.0'-1435.3') and 105627
Weight Logs (1,438.8-2,151.7'). Submittal date: 09/08/1995. 
TM000000UZ7ARS.001. USW UZ-7A Shift Drilling Summaries, Lithologic Logs, 160826
Structural Logs, Weight Logs, and Composite Borehole Log from 0.0' to 770.0'. 
Submittal date: 09/05/1995. 
ANL-NBS-HS-000042 REV 00 8-10 October 2004 

Analysis of Hydrologic Properties Data 
8.4 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER 
LB0205REVUZPRP.001. Fracture Properties for UZ Model Layers Developed from Field Data. 
Submittal date: 05/14/2002. 
LB0207REVUZPRP.001. Revised UZ Fault Zone Fracture Properties. Submittal date: 
07/03/2002. 
LB0207REVUZPRP.002. Matrix Properties for UZ Model Layers Developed from Field and 
Laboratory Data. Submittal date: 07/15/2002. 
LB0408REVUXPRP.001. Pre-Processing - Fracture Properties for UZ Model Layers Developed 
from Field Data. Submittal date: 08/26/2004. 
8.5 SOFTWARE CODES 
N/A 
ANL-NBS-HS-000042 REV 00 8-11 October 2004 

Analysis of Hydrologic Properties Data 
INTENTIONALLY LEFT BLANK 
ANL-NBS-HS-000042 REV 00 8-12 October 2004 

Analysis of Hydrologic Properties Data 
APPENDIX A 
DESCRIPTION OF EXCEL FILES USED 
ANL-NBS-HS-000042 REV 00 October 2004 

Analysis of Hydrologic Properties Data 
ANL-NBS-HS-000042 REV 00 October 2004 

Analysis of Hydrologic Properties Data 
This appendix describes Excel files used for developing uncalibrated hydraulic properties. The 
data mentioned in this appendix were downloaded directly from TDMS unless otherwise noted. 
The Excel files were also submitted to TDMS. The relationships between the output DTNs of 
this report and the Excel files described in Appendix A are as follows: 
LB0207REVUZPRP.002 (matrix properties): hydroprops_fin.xls, MRC_Q_TCw_fin.xls, 
MRC_Q_PTn_fin.xls MRC_Q_TSW_FIN.XLS, 
MRC_Q_CHCF_FIN.XLS, and 
vG_Summary_fin.xls 
LB0408REVUZPRP.001 (fracture properties): lecan97.xls, UTCA_BRFA.xls, drift.xls, 
airk.xls, and Fpor.xls 
hydroprops_fin.xls (Output DTN: LB0207REVUZPRP.002) 
This file was used to develop matrix properties for UZ model layers. 
Worksheet borehole data' 
 Import DTN: MO0109HYMXPROP.001 [DIRS 155989] 
 Import DTN: GS980708312242.010 [DIRS 106752] (WT-24 physical properties, 
corresponding to data files with names staring with zz-sep in the same DTN), and 
GS980808312242.014 [DIRS 106748] (SD-6 physical properties, corresponding to data 
files with names staring with zz-sep in the same DTN) into same columns used in 
MO0109HYMXPROP.001 [DIRS 155989] 
 Import DTNs: GS980708312242.011 [DIRS 107150] (WT-24 high pressure 
permeameter conductivity), GS980908312242.038 [DIRS 107154] (SD-6 high pressure 
permeameter conductivity), and GS980908312242.041 [DIRS 107158] (SD-7, SD-9, 
SD-12, UZ-14, and UZ#16 high pressure permeameter conductivity) into columns AA to 
AD 
 Added column D, depth in ft, converted from column F 
 Added column J, residual water content (RWC), with conditional formatting to highlight 
residual water content = 5 percent 
 Calculated saturation, in column N, for WT-24 and SD-6 
 Added GFM lithostratigraphy from DTN: MO0012MWDGFM02.002 [DIRS 153777] 
file contacts00md.dat to columns S & T. Where contacts00md.dat did not have 
borehole, note in column U indicates source of lithostratigraphy (DTNs also listed in 
rows 5389-5398: 
GS950108314211.009 [DIRS 152556], GS940208314211.007 [DIRS 155533], 
GS940308314211.018 [DIRS 145589], GS950108314211.008 [DIRS 152558], 
GS950708314211.028 [DIRS 160827], GS940208314211.008 [DIRS 145581], 
TM000000UZ7ARS.001 [DIRS 160826]) 
ANL-NBS-HS-000042 REV 00 A-1 October 2004 

Analysis of Hydrologic Properties Data 
Hydrostratigraphy (hydrogeologic unit  HGU) is determined in column V (based on rules of 
Flint (1998 [DIRS 100033], pp. 21-32); groupings indicated below are for UZ Model layers: 
 1 & 2 = CCR & CUC  Tpcrn & Tpcrl, lower contact (l.c.) of CCR where porosity (f) 
> 9 percent, l.c. of CUC where f < 20 percent. Units are combined because greater 
property resolution is not needed at upper margin of UZ Model 
 3 & 4 = CUL & CW  Tpcpul & Tpcpmn & Tpcpll & Tpcpln, l.c. of CUL at 
lithostratigraphic contact (l.c. of Tpcpul of identified in columns P & Q, but contact is 
unimportant for UZ Model hydrostratigraphy), l.c. of CW where f > 15 percent. Units 
are combined because greater property resolution is not needed at upper margin of UZ 
Model 
 5 = CMW  base of Tpcpln & Tpcpv3 & Tpcpv2, l.c. where f > 28 percent 
 6 = CNW  base of Tpcpv2 & Tpcpv1, l.c. at lithostratigraphic contact (l.c. of Tpcpv1) 
 7 = BT4  Tpbt4 & top of Tpy, l.c. where f > 30 percent or at l.c. of Tpy whichever is 
stratigraphically higher 
 8 = TPY  moderately welded interior of Tpy, l.c. where f < 30 percent 
 9 = BT3  base of Tpy & Tpbt3, l.c. at lithostratigraphic contact (l.c. of Tpbt3) (note: if 
Tpbt4 is not present and Tpy f > 30 percent then all Tpy is included in BT3) 
 10 = TPP = Tpp 
 11 = BT2  Tpbt2 & Tptrv3 & Tptrv2, l.c. at lithostratigraphic contact (l.c. of Tptrv2) 
 12 = TC  Tptrv1 & top of Tptrn, l.c. where f > 9 percent 
 13 = TR  Tptrn, l.c. at lithostratigraphic contact (l.c. of Tptrn) 
 14 = TUL = Tptrl & Tptpul 
 15 = TMN = Tptpmn 
 16 = TLL = Tptpll 
 17 & 18 = TM2 & TM1 = Tptpln 
 19 = PV3 = Tptpv3 
 20 = PV2a = altered Tptpv2 (altered vitric rocks defined where residual water content 
= 5 percent) 
 20.1 = PV2v = vitric Tptpv2 
ANL-NBS-HS-000042 REV 00 A-2 October 2004 

Analysis of Hydrologic Properties Data 
 21 = BT1a = altered Tptpv1 & Tpbt1 
 21.1 = BT1v = vitric Tptpv1 & Tpbt1 
 22 = CHV = vitric Tac 
 23 = CHZ = altered (zeolitic) Tac 
 24 = BTa = altered Tacbt 
 24.1 = BTv = vitric Tacbt 
 25 = PP4 = Tcpuv 
 26 = PP3 = Tcpuc 
 27 = PP2  Tcprn & Tcplc, l.c. where residual water content = 5 percent 
 28 = PP1  Tcplv & Tcpbt & Tcbuv, l.c. where residual water content < 5 percent 
 29 = BF3  Tcbuc & Tcbrn & Tcblc, l.c. at lithostratigraphic contact (l.c. of Tcblc) 
 30 = BF2 = Tcblv & Tcbbt & Tctuv 
 31 = TR3 = Tctuc 
Differences between HGU picks from DTN: MO0109HYMXPROP.001 [DIRS 155989] are 
indicated by non-zero values and highlighting in column W. Note that 
DTN: GS000608314211.003 [DIRS 161658] is listed in the work sheet borehole data as 
corroborating information. HGU picks from this corroboration information are the same as those 
from DTN: MO0109HYMXPROP.001 [DIRS 155989] except for a sample in Line 132. For that 
sample, the location identified from DTN: MO0109HYMXPROP.001 [DIRS 155989] is CCR 
while that identified from DTN: GS000608314211.003 [DIRS 161658] is CUC. However, as 
indicated above, both CCR and CUC belong to the same UZ model layer tcw11. As a 
result, this difference will not have any effects on estimated UZ-model-layer-averaged rock 
properties. 
Worksheet hydroprops' 
 Worksheet borehole data is copied and renamed hydroprops 
 Columns D, E, F, H, K, M, O-R, U, and W from borehole data are deleted 
 Columns G, I, H, K, L, J, and N from hydroprops are copied to columns D to J, 
respectively 
 Saturation values greater than one in column J are changed to one 
ANL-NBS-HS-000042 REV 00 A-3 October 2004 

Analysis of Hydrologic Properties Data 
 The logarithm of hydraulic conductivity measurement are collected in column U. Where 
two hydraulic conductivity measurements were made on the same sample the high 
pressure permeameter measurement from column Q is chosen 
 Values are copied from column U to column V 
 Rows 62 to 5387 are sorted by column M (HGU) 
Worksheet 007 Ks 
 Import DTN: GS990308312242.007 [DIRS 107185] (Busted Butte lab measurements of 
hydrologic properties) 
 The logarithm of hydraulic conductivity is calculated in column J 
Worksheet 007 n 
 Import DTN: GS990308312242.007 [DIRS 107185] (Busted Butte lab measurements of 
physical properties) 
Worksheet 98.008 Ks 
 Import DTN: GS990708312242.008 [DIRS 109822] (Busted Butte lab measurements of 
hydrologic properties) 
 The logarithm of hydraulic conductivity is calculated in column G. 
Worksheet 98.008 n 
 Import DTN: GS990708312242.008 [DIRS 109822] (Busted Butte lab measurements of 
physical properties) 
Worksheet 006 Ks 
 Import DTN: GS971008312231.006 [DIRS 107184] (ESF surface sample lab 
measurements of saturated hydraulic conductivity) 
Worksheet Ksat w ND 
 All columns except F, G, and V from hydroprops are copied to Ksat w ND 
 Rows from 62 to 5387 without conductivity values are deleted 
 Rows in HGUs without non-detect conductivity measurements (noted as nf or NF) 
are deleted 
 Hydraulic conductivity, SPC # (i.e., standard Ids for samples), and sample # are copied 
from 006 Ks to HGU #15 columns O, Q, and R, respectively 
ANL-NBS-HS-000042 REV 00 A-4 October 2004 

Analysis of Hydrologic Properties Data 
 Rows within each HGU (or group of HGUs as defined above) are sorted by ascending 
conductivity with non-detects first 
 The conductivity for each remaining HGU is ranked in column T 
 The rank is converted to a percentile in column U, where percentile equals rank divided 
by (total number of measurements plus one) 
 The NORMSINV function is applied to the percentile in column V. This gives (the value 
minus the expected value) divided by the standard deviation for that percentile in a 
normal distribution, which is analogous to plotting the log conductivity values on 
probability paper 
 The intercept and slope of the line fitted through the NORMSINV values (x-axis) and 
the log conductivity values (y-axis) give the expected value and the standard deviation, 
respectively, of the log conductivity data and account for the unknown values of the 
non-detect measurements, which are assumed to be less than the lowest conductivity 
measured 
Worksheet Summary 
Matrix properties for each UZ Model layer are shown. Columns and rows are labeled. 
For relative humidity porosity (f(RH)), porosity (f), saturation (S), bulk density (. bulk), and 
particle density (. particle), the arithmetic mean, standard deviation, number of samples, and 
standard error are given. Standard error is standard deviation divided by the square root of 
number of samples. Minimum and maximum values of saturation are also given. Note: data 
from only one sample are available for the BTv; these data are consistent with the BT1v, so the 
BT1v will be used as an analog for the BTv. 
Residual saturation (Sr), here equal to porosity minus relative humidity porosity, is given in 
column O. Note: again, BT1v should be used as an analog for the BTv. 
For log conductivity, the arithmetic mean, standard deviation, number of samples with a 
measured conductivity, standard error (the standard deviation divided by the square root of the 
number of samples with a measured conductivity), and number of non-detect measurements are 
given in columns X to AB. Where there are non-detect measurements, these values are shown in 
red italics. Note: again BT1v should be used as an analog for the BTv. 
The mean and standard deviation of the log conductivity data for layers with non-detect 
measurements (the intercept and slope of the data in worksheet Ksat w ND) are shown in 
columns AD and AE. The standard error is calculated in column AF as the standard deviation 
divided by the square root of the total number of conductivity measurements including 
non-detects. 
Log conductivity is converted to log permeability in column AI, where permeability equals 
conductivity times water viscosity divided by water density and gravity. Permeability is shown 
ANL-NBS-HS-000042 REV 00 A-5 October 2004 

Analysis of Hydrologic Properties Data 
in column AH. Upscaled log permeability is calculated in column AL, where permeability is 
upscaled by the factor of 0.38 times the variance. Upscaled permeability is shown in column 
AK. Note: again BT1v should be used as an analog for the BTv; additionally, BT1a should be 
used as an analog for the PV2a, and PP1 should be used as an analog for the BF2. 
MRC_Q_TCw_fin.xls (Output DTN: LB0207REVUZPRP.002) 
This file was used to develop matrix properties for UZ model layers. 
Worksheet 037 wc 
 Import DTN: GS980908312242.037 [DIRS 107180] (ESF North Ramp moisture study 
borehole sample water retention water content data) 
Worksheet 037 wp 
 Import DTN: GS980908312242.037 [DIRS 107180] (ESF North Ramp moisture study 
borehole sample water retention water potential data) 
Worksheet 008 wp & wc(g per g) 
 Import DTN: GS980408312242.008 [DIRS 107161] (ESF North Ramp moisture study 
borehole sample water retention data) 
Worksheet 040 Ks 
 Import DTN: GS980908312242.040 [DIRS 107169] (ESF North Ramp moisture study 
borehole sample saturated hydraulic conductivity data) 
Worksheet 040 por + 
 Import DTN: GS980908312242.040 [DIRS 107169] (ESF North Ramp moisture study 
borehole sample physical properties data) 
Worksheet 005 bd 
 Import DTN: GS980308312242.005 [DIRS 107165] (ESF North Ramp moisture study 
borehole sample bulk density data) 
Worksheet 005 105n 
 Import DTN: GS980308312242.005 [DIRS 107165] (ESF North Ramp moisture study 
borehole sample oven dried porosity data) 
Worksheet 005 RHn 
 Import DTN: GS980308312242.005 [DIRS 107165] (ESF North Ramp moisture study 
borehole sample relative humidity oven porosity data) 
ANL-NBS-HS-000042 REV 00 A-6 October 2004 

Analysis of Hydrologic Properties Data 
Worksheet 008 Kr 
 Import DTN: GS980408312242.008 [DIRS 107161] (ESF North Ramp moisture study 
borehole sample relative permeability data) 
 Calculate saturation in column H from water content (column G) by assuming the 
maximum water content for each sample is equal to a saturation of one 
 Calculate saturation in column I from water content (column G) by assuming the 
maximum water content for each sample as measured for the water potential data 
(worksheet 008 wp & wc(g per g) column G) is equal to a saturation of one 
 Calculate saturation in column J from water content (column G) by assuming water 
content equal to the porosity (from either worksheet 040 por + column G rows 39 to 
49 or worksheet 005 105n column B) represents a saturation of one 
 Calculate relative permeability in column K from conductivity (column B) by assuming 
the maximum conductivity for each sample is equal to a relative permeability of one 
 Calculate relative permeability in column L from conductivity (column B) by assuming 
the saturated conductivity (from worksheet 040 Ks column B) is equal to a relative 
permeability of one 
Worksheet 039 wc 
 Import DTN: GS980908312242.039 [DIRS 145272] (USW SD-6 water retention water 
content data) 
 Use data from hydroprops.xls worksheet borehole data to make HGU assignments for 
each sample (column G) 
Worksheet 039 wp 
 Import DTN: GS980908312242.039 [DIRS 145272] (USW SD-6 water retention water 
potential data) 
 Use data from hydroprops.xls worksheet borehole data to make HGU assignments for 
each sample (column G) 
Worksheet in-situ 
 Copy average, minimum, and maximum in-situ saturation from hydroprops.xls 
worksheet summary to columns B, C, and D, respectively for HGUs in column A 
ANL-NBS-HS-000042 REV 00 A-7 October 2004 

Analysis of Hydrologic Properties Data 
 Copy average in-situ water potential from DATAfix_satsum.xls (Wang 2003 
[DIRS 161654], SN-LBNL-SCI-003-V2, p. 65; Ahlers 2000 [DIRS 155853], pp. 93 to 
94) worksheet summary to column E for HGUs in column A. Note that the averaged 
data are used for demonstration and not used for calculations. Therefore, they do not 
have any effect on the determined matrix property 
 Dummy values for plotting in column F 
Worksheet CUC 
1. Import DTN: MO0109HYMXPROP.001 [DIRS 155989] (water retention Hydrologic 
Properties data from File MRCQ, Worksheet-CUCQ) 
2. Assignment of samples to HGU is checked against hydroprops.xls worksheet 
borehole data 
3. Saturation (column D) is (re)calculated assuming the highest measured water content 
for each sample is equivalent to full saturation 
4. Data with water potential values less than approximately 1.4 bars (note: for plotting 
reasons, water potential is expressed here as a positive number rather than the 
conventional negative number) that were acquired with a chilled-mirror psychrometer 
(data from other than borehole USW SD-6 or moisture study boreholes in the ESF 
North Ramp) are moved to the bottom of columns A to E and are excluded from 
further use 
5. Water content is plotted versus water potential with chilled-mirror psychrometer data 
shown in open diamond symbols. Each sample is shown in a different color 
6. van Genuchten parameters satiated saturation, residual saturation, alpha, n, and m are 
labeled and are at the top of columns G and H (note: satiated saturation fixed equal to 
one; residual saturation is fixed to the value calculated in hydroprops_fin.xls 
Summary; m=1-(1/n)) 
7. Saturation, S, is predicted in column G based on the measured water potential and the 
van Genuchten parameters using the following expression, 
-m
n
S = S +(S - S )[1 + (aP )]
rsr c 
where Sr is residual saturation, Ss is satiated saturation, Pc is water potential, and a, n, 
and m are van Genuchten parameters 
8. The squared error (difference) between the predicted saturation and the measured 
saturation is calculated in column H and summed in cell H29 
9. The solver function of Excel is used to estimate values for aand n by minimizing the 
sum of the squared error (cell H29). Note: all optional solver settings are 
default; where necessary the following constraints are added: 
a= 0 n = 1 
ANL-NBS-HS-000042 REV 00 A-8 October 2004 

Analysis of Hydrologic Properties Data 
10. Saturation is calculated in column J based on the van Genuchten water retention 
function, the estimated parameters, and a range of water potential values in column I. 
The results are plotted as a red line 
11. The Jacobian matrix is calculated numerically in columns L to M using the 
perturbed parameter values given in cells M26:M28 
J 
ij 
.zi
= 
.pj 
is an element of the Jacobian matrix where zi is the ith predicted value (of saturation for 
j
th
this problem), and pj is the parameter. Note because n and m are dependent, 
Jacobian elements for parameter n are not evaluated 
12. The parameter covariance matrix, evaluated in cells P32:Q33, is 
2 T -1
C 
pp = s0 (J J ) 
where s02 is the sum of the squared error divided by the degree of freedom (# of data 
points - # of parameters) and J is the Jacobian matrix 
13. The uncertainty (analogous to the standard error calculated for other hydrologic 
parameters in hydroprops.xls worksheet Summary) of the estimated parameters is 
calculated in cells P36:P37 as the square root of the diagonal elements of Cpp 
14. The 95 percent error band (two standard errors) on the fitted van Genuchten curve are 
calculated in columns R and S and plotted as gray lines 
Worksheet CUL & CW 
1. Import DTN: MO0109HYMXPROP.001 [DIRS 155989] (water retention Hydrologic 
Properties data from File MRCQ, Worksheet-CULQ and Worksheet CWQ). Note that 
USW UZ-Na7 data are from SEP Table s01144_003 and the UZ-25 and UZ#16 data 
from SEP Table s01144_004 
1a. Appropriate data from worksheets 039 wc and 039 wp are added to columns B, 
C, and E 
2. Same as step 2 above 
2a. Sample N27 61.9r is not within either the CUL or CW and is removed 
3. Same as step 3 above 
4. Same as step 4 above 
4a. Data with water potential values of 0.0 bars that were acquired with a centrifuge 
(data from borehole USW SD-6 or moisture study boreholes in the ESF North 
Ramp) are moved to the bottom of columns A to E and are excluded from further 
use 
ANL-NBS-HS-000042 REV 00 A-9 October 2004 

Analysis of Hydrologic Properties Data 
5. Same as step 5 above 
5a. Centrifuge data are shown as filled circles. Each centrifuge sample is shown in a 
different color that is not necessarily different from the colors used for the chilled-
mirror psychrometer data 
6. Same as step 6 above 
7. Same as step 7 above 
8. Same as step 8 above 
9. Same as step 9 above 
10. Same as step 10 above 
11. Same as step 11 above 
12. Same as step 12 above 
13. Same as step 13 above 
14. Same as step 14 above 
15. Average in situ water potential and saturation data from worksheet in-situ is plotted 
with 2 bar error bars 
Worksheet CMW 
1. Import DTN: MO0109HYMXPROP.001 [DIRS 155989] (water retention Hydrologic 
Properties data from File MRCQ, Worksheet-CMWQ) 
1a. Appropriate data from worksheets 037 wc and 037 wp are identified by the 
lithostratigraphy in DTN: LAJF831222AQ98.014 [DIRS 160825] are added to 
columns B, C, and E 
1b. Appropriate data from worksheet 008 wp & wc(g per g) are identified as in step 
1a above are added to columns B, C, and E 
1c. Appropriate data from worksheets 039 wc and 039 wp are added to columns B, 
C, and E 
2. Same as step 2 above 
3. Same as step 3 above 
3a. The saturation for the data from 1a is calculated assuming the highest water 
content from either worksheet 008 wp & wc(g per g) or 008 Kr for that sample 
represents the water content at full saturation 
ANL-NBS-HS-000042 REV 00 A-10 October 2004 

Analysis of Hydrologic Properties Data 
4. Same as step 4 above 
4a. Same as step 4a above 
5. Same as step 5 above 
5a. Same as step 5a above 
6. Same as step 6 above 
7. Same as step 7 above 
8. Same as step 8 above 
9. Same as step 9 above 
10. Same as step 10 above 
10a. Plotting the estimated function shows that the shape of the curve does not match 
well with the data. The parameters (aand n) are adjusted by hand to improve the 
subjective match between the shape of the curve and the data. This adjustment 
results in an increase of 0.22 (9 percent) in the sum of the squared error 
11. Same as step 11 above 
12. Same as step 12 above 
13. Same as step 13 above 
14. Same as step 14 above 
15. Same as step 15 above 
16. Appropriate unsaturated conductivity data from worksheet 008 Kr are identified as in 
step 1a above, added to columns V, W, and X, and are plotted as circles connected by 
a dashed line. As in 3a, the saturation is calculated assuming the highest water content 
measured for the sample represents full saturation (column W is linked to either 
column H or I in 008 Kr) 
2
m
S . 
rwe e
(1 1 m )]where . and m are fitting parameters 
17. Relative permeability is k =()[1 - - S 
(S -S )
r
S = 
e
sr
and (S -S )where S is saturation, Sr is residual saturation, and Ss is satiated 
saturation. Use of a match point, S0, that is near, but not at, full saturation is 
recommended to avoid problems with identification of full saturation and large changes 
in unsaturated conductivity very near saturation due to macropores. Relative 
permeability can then be redefined in terms of the conductivity at the match point: 
ANL-NBS-HS-000042 REV 00 A-11 October 2004 

Analysis of Hydrologic Properties Data 
1 m ) 2
.
m .
K (). Se .
.. 
.
. 1 -( 1 - S
S
we e
m
1 m 
) .
. 
Kw ( Se0 , ) = ..
Se0 , .. 1 -( 1 - S
. e0 , . 
where Se,0 is the effective saturation at the match point and Kw(Se,0) is the conductivity 
at the match point. A saturation match point, Se,0, of 0.95 is used for the CMW. The 
unsaturated conductivity at the match point, Kw(Se,0), is calculated in column Z for 
each sample by linear interpolation between the nearest saturation and log conductivity 
data points 
18. The redefined relative permeability, left side of last equation in step 17, is calculated 
in column Y 
19. The relative permeability predicted from the saturation data (column W), as expressed 
on the right side of the last equation in step 17, is calculated in column AA. 
Parameters m and Sr are the same as for the water retention function 
20. The squared error (difference) between the predicted relative permeability and the 
measured relative permeability is calculated in column AB and summed in cell AB31 
21. The solver function of Excel is used to estimate ., cell X29, by minimizing the sum of 
the squared error (cell X23, which is linked to cell AB31). Note: all optional solver 
settings are default 
22. The Jacobian matrix is calculated numerically in column AC using the perturbed . 
value given in cell AC29. The variance and standard error of . are calculated in cells 
AD34 and AE34, respectively 
23. Relative permeability is calculated in column U for a range of saturation values in 
column T. The results are plotted as an orange line 
24. The average, minimum, and maximum in-situ saturation are plotted as a gray circle 
and error bars 
ANL-NBS-HS-000042 REV 00 A-12 October 2004 

Analysis of Hydrologic Properties Data 
MRC_Q_PTn_fin.xls (Output DTN: LB0207REVUZPRP.002) 
This file was used to develop matrix properties for UZ model layers. 
Worksheets in-situ, 037 wc, 037 wp, 008 Kr, 040 por +, 005 bd, 005 105n, 005 
RHn, 008 wp & wc(g per g), 039 wc, 039 wp are prepared as for MRC_Q_TCw_fin.xls with 
the exception of relative permeability calculations documented in steps 16 - 23 below which are 
carried out in worksheet 008 Kr. 
Worksheets CMW, BT4, TPY, BT3, TPP, and BT2 
1. Import DTN: MO0109HYMXPROP.001 [DIRS 155989] (water retention Hydrologic 
Properties data from File MRCQ, Worksheet-CNWQ, Worksheet-BT4Q, Worksheet-
TPYQ, Worksheet-BT3Q, Worksheet-TPPQ, Worksheet-BT2Q,) 
1a. Same as step 1a above except that no data are identified for TPY 
1b. Same as step 1b above except that no data are identified for TPY 
1c. Same as step 1c above except that no data are identified for TPY 
2. Same as step 2 above. This results in sample UZ16 171.7r begin reassigned from TPY 
to BT4 and sample SD9 74.1 being removed from BT3 (it is already assigned correctly 
to CNW) 
3. Same as step 3 above 
3a. Same as step 3a above 
4. Same as step 4 above 
4a. Same as step 4a above 
5. Water content is plotted vs. water potential on worksheets PTn curves and PTn 
curves (2) for HGU groups CNW, BT4, and TPY and BT3, TPP, and BT2, 
respectively, with chilled-mirror psychrometer data shown in open diamond symbols. 
Each sample is shown in a different color 
5a. Centrifuge data are shown as filled circles. Each centrifuge sample is shown in a 
different color that is not necessarily different from the colors used for the 
chilled-mirror psychrometer data. Note: no centrifuge data for TPY exist 
6. Same as step 6 above 
7. Same as step 7 above 
8. Same as step 8 above 
ANL-NBS-HS-000042 REV 00 A-13 October 2004 

Analysis of Hydrologic Properties Data 
9. Same as step 9 above 
10. Same as step 10 above. Results are plotted in worksheets PTn curves and PTn 
curves (2) 
11. Same as step 11 above 
12. Same as step 12 above 
13. Same as step 13 above 
14. Same as step 14 above. Results are plotted in worksheets PTn curves and PTn 
curves (2) 
15. Same as step 15 above. Results are plotted in worksheets PTn curves and PTn 
curves (2) 
16. Appropriate unsaturated conductivity data in worksheet 008 Kr are identified as in 
step 1a above and are plotted as circles connected by a dashed line in worksheets PTn 
curves and PTn curves (2). As in 3a, the appropriate saturation data are identified 
and highlighted in either column H or I in 008 Kr by assuming that the highest water 
content measured for the sample represents full saturation 
17. Same as step 17 above except that the saturation match points are 
CNW: S0 = 0.85 
BT4: S0 = 0.65 
BT3: S0 = 0.95 
TPP: S0 = 0.80 
BT2: S0 = 0.83 
and no relative permeability data for TPY exist 
18. Same as step 18 above except the calculation is carried out in worksheet 008 Kr in 
column M. 
19. Same as step 19 above except the calculation is carried out in worksheet 008 Kr in 
column N 
20. In worksheet 008 Kr, the squared error (difference) between the predicted relative 
permeability and the measured relative permeability is calculated in column X and 
summed in cells W18:W22 for each of the HGUs identified in cells V18:V22 
21. In worksheet 008 Kr, the solver function of Excel is used to estimate ., cells 
Z18:Z22, for each HGU identified in cells V18:V22 by minimizing the sum of the 
ANL-NBS-HS-000042 REV 00 A-14 October 2004 

Analysis of Hydrologic Properties Data 
squared error for the same HGU, cells W18:W22. Note: all optional solver settings 
are default 
22. In worksheet 008 Kr, the Jacobian matrix is calculated numerically in column Y 
using the perturbed . value given in cells AA18:AA22. The variance and standard 
error of . are calculated in cells AB18:AB22 and AC18:AC22, respectively 
23. In worksheet 008 Kr, relative permeability is calculated in columns Q:U for a range 
of saturation values in column P. The results are plotted as an orange line in 
worksheets PTn curves and PTn curves (2) 
24. The average, minimum, and maximum in situ saturation are plotted as a gray circle 
and error bars in worksheets PTn curves and PTn curves (2) 
MRC_Q_TSW_FIN.XLS (Output DTN: LB0207REVUZPRP.002) 
This file was used to develop matrix properties for UZ model layers. 
Worksheets in-situ, 037 wc, 037 wp, 008 wp & wc(g per g), 039 wc, 039 wp are 
prepared as for MRC_Q_TCw_fin.xls. 
Worksheet 007 S wp 
 Import DTN: GS990308312242.007 [DIRS 107185] (Busted Butte water retention data) 
 Use data from DTN: LA0207SL831372.001 [DIRS 160824] to make HGU assignments 
for each sample (column F) 
Worksheet 007 Ks 
 Import DTN: GS990308312242.007 [DIRS 107185] (Busted Butte hydraulic 
conductivity data) 
Worksheet 007 S K 
 Import DTN: GS990308312242.007 [DIRS 107185] (Busted Butte relative permeability 
data) 
 Use data from DTN: LA0207SL831372.001 [DIRS 160824] to make HGU assignments 
for each sample (column F) 
 In column G, calculate relative permeability from conductivity in column E assuming 
the saturated conductivity in worksheet 007 Ks column H represents a relative 
permeability of one. Note: no saturated conductivity measurement for sample INJ-4-
16.8B exists, so the highest conductivity measured is assumed to equal a relative 
permeability of one, and relative permeability is calculated in column H 
ANL-NBS-HS-000042 REV 00 A-15 October 2004 

Analysis of Hydrologic Properties Data 
Worksheet 99.008 S wp 
 Import DTN: GS990708312242.008 [DIRS 109822] (Busted Butte water retention data) 
 Use data from DTN: LA0207SL831372.001 [DIRS 160824] to make HGU assignments 
for each sample (column G) 
Worksheet 99.008 Ks 
 Import DTN: GS990708312242.008 [DIRS 109822] (Busted Butte hydraulic 
conductivity data) 
Worksheet 99.008 S K 
 Import DTN: GS990708312242.008 [DIRS 109822] (Busted Butte relative permeability 
data) 
 Use data from DTN: LA0207SL831372.001 [DIRS 160824] to make HGU assignments 
for each sample (column G) 
 In column H, calculate relative permeability from conductivity in column E assuming 
the saturated conductivity in worksheet 007 Ks column H represents a relative 
permeability of one 
Worksheet 012 wc 
 Import DTN: GS980808312242.012 [DIRS 149375] (USW WT-24 water retention 
water content data) 
 Use data from hydroprops.xls worksheet borehole data to make HGU assignments for 
each sample (column G) 
Worksheet 012 wp 
 Import DTN: GS980808312242.012 [DIRS 149375] (USW WT-24 water retention 
water potential data) 
 Use data from hydroprops.xls worksheet borehole data to make HGU assignments for 
each sample (column G) 
Worksheet 95.008 wc 
 Import DTN: GS950608312231.008 [DIRS 144662] (USW UZ-N27 and UE-25 UZ#16 
water retention water content data). Note: for the most part, these data are already 
included under DTN: MO0109HYMXPROP.001 [DIRS 155989], however, some 
additional data under this DTN exist 
ANL-NBS-HS-000042 REV 00 A-16 October 2004 

Analysis of Hydrologic Properties Data 
Worksheet 95.008 wp 
 Import DTN: GS950608312231.008 [DIRS 144662] (USW UZ-N27 and UE-25 UZ#16 
water retention water potential data). Note: for the most part, these data are already 
included under DTN: MO0109HYMXPROP.001 [DIRS 155989], however, some 
additional data under this DTN exist 
Worksheets TC, TR, TUL, TMN, TLL, TM2 & TM1, PV3, PV2a, and PV2v 
1. Import DTN: MO0109HYMXPROP.001 [DIRS 155989] (water retention Hydrologic 
Properties data from File MRCQ, Worksheet-TCQ, Worksheet-TRQ, Worksheet-
TULQ, Worksheet-TMNQ, Worksheet-TLLQ, Worksheet-TM2Q, Worksheet-TM1Q, 
Worksheet-PV3Q, Worksheet-PV2Q). Note: Data from Worksheet-TM2Q and 
Worksheet-TM1Q are combined in worksheet TM2 & TM1 
1a. Appropriate data from worksheets 037 wc and 037 wp are identified by the 
lithostratigraphy in DTNs: LAJF831222AQ98.014 [DIRS 160825] and 
GS960908314224.020 [DIRS 106059] (columns B, C, and E of worksheets TC 
and TR). ESF station of contacts from Table 2 in Geology of the Exploratory 
Studies Facility Topopah Spring Loop (CRWMS M&O 1998 [DIRS 102679]) are 
used to confirm the lithostratigraphy information provided in the above two DTNs 
1b. Appropriate data from worksheet 008 wp & wc(g per g) are identified as in step 
1a above are added to columns B, C, and E of worksheet TC 
1c. Appropriate data from worksheets 039 wc and 039 wp are added to columns B, 
C, and E of worksheets TC, TR, TM2 & TM1, and PV3 
1d. Appropriate data from worksheets 007 S wp and 99.008 S wp are added to 
columns B, D, and E of worksheet PV2v 
1e. Appropriate data from worksheets 012 wc and 012 wp are added to columns B, 
C, and E of worksheet PV2a 
1f. Appropriate data from worksheets 95.008 wc and 95.008 wp are added to 
columns B, C, and E of worksheets TLL and PV3 
2. Same as step 2 above 
2a. Sample SD9-1440.5r is not within the PV2 and is removed 
3. Same as step 3 above except for worksheet PV2v where data are given in terms of 
saturation rather than water content 
4. Same as step 4 above 
4a. Same as step 4a above 
ANL-NBS-HS-000042 REV 00 A-17 October 2004 

Analysis of Hydrologic Properties Data 
5. Same as step 5 above 
5a. Same as step 5a above 
6. Same as step 6 above 
7. Same as step 7 above 
8. Same as step 8 above 
9. Same as step 9 above 
10. Same as step 10 above 
10a. Plotting the estimated function for PV3 shows that the shape of the curve does not 
match well with the data. The parameters (a and n) are adjusted by hand to 
improve the subjective match between the shape of the curve and the data. This 
adjustment results in an increase of 0.14 (16 percent) in the sum of the squared 
error 
11. Same as step 11 above 
12. Same as step 12 above 
13. Same as step 13 above 
14. Same as step 14 above 
15. Same as step 15 above 
16. In worksheet PV2v only, appropriate unsaturated conductivity data from worksheets 
007 S K and 99.008 S K are identified as in step 1d above, added to columns V, W, 
and X, and are plotted as circles connected by a dashed line 
17. In worksheet PV2v only, same as step 17 under spreadsheet MRC_Q_TCw_fin.xls, 
worksheet CMW, except Se,0 = 0.9 
18. In worksheet PV2v only, same as step 18 under spreadsheet MRC_Q_TCw_fin.xls, 
worksheet CMW 
19. In worksheet PV2v only, same as step 19 under spreadsheet MRC_Q_TCw_fin.xls, 
worksheet CMW 
20. In worksheet PV2v only, same as step 20 under spreadsheet MRC_Q_TCw_fin.xls, 
worksheet CMW 
21. In worksheet PV2v only, same as step 21 under spreadsheet MRC_Q_TCw_fin.xls, 
worksheet CMW 
ANL-NBS-HS-000042 REV 00 A-18 October 2004 

Analysis of Hydrologic Properties Data 
22. In worksheet PV2v only, same as step 22 under spreadsheet MRC_Q_TCw_fin.xls, 
worksheet CMW 
23. In worksheet PV2v only, same as step 23 under spreadsheet MRC_Q_TCw_fin.xls, 
worksheet CMW 
24. In worksheet PV2v only, same as step 24 under spreadsheet MRC_Q_TCw_fin.xls, 
worksheet CMW 
MRC_Q_CHCF_FIN.XLS (Output DTN: LB0207REVUZPRP.002) 
This file was used to develop matrix properties for UZ model layers. 
Worksheets in-situ, 039 wc, 039 wp, 007 S wp, 007 Ks, 007 S K, 99.008 S wp, 
99.008 Ks, 99.008 S K, 012 wc, 012 wp, 95.008 wc, and 95.008 wp are prepared as for 
MRC_Q_TSw_fin.xls. 
Worksheet 001 wc wp 
 Import DTN: GS010608312242.001 [DIRS 160822] (Busted Butte water retention data) 
 Use data from DTN: LA0207SL831372.001 [DIRS 160824] to make HGU assignments 
for each sample (column F) 
Worksheet 001 wc K 
 Import DTN: GS010608312242.001 [DIRS 160822] (Busted Butte relative permeability 
data) 
 Use data from DTN: LA0207SL831372.001 [DIRS 160824] to make HGU assignments 
for each sample (column G) 
 In column I, calculate the saturation from water content in column D assuming that the 
highest water content listed for the same sample in worksheet 001 wc wp (if measured) 
is the water content at full saturation 
 In column J, calculate the saturation from water content in column D assuming the 
highest water content listed for each sample is the water content at full saturation 
 In column K, calculate relative permeability from conductivity in column E assuming 
the highest conductivity for each sample is the saturated conductivity 
Worksheet 96.003 wp wc 
 Import DTN: GS960808312231.003 [DIRS 147590] (USW SD-7, USW SD-9, USW 
SD-12, and UE-25 UZ#16 water retention data). Note: for the most part, these data are 
already included under DTN: MO0109HYMXPROP.001 [DIRS 155989], however, are 
some additional data under this DTN exists 
ANL-NBS-HS-000042 REV 00 A-19 October 2004 

Analysis of Hydrologic Properties Data 
Worksheets BT1v, BT1a, CHV, CHZ, BTv, BTa, PP4, PP3, PP2, PP1, BF3, 
and BF2 
1. Import DTN: MO0109HYMXPROP.001 [DIRS 155989] (water retention Hydrologic 
Properties data from File MRCQ, Worksheet-BT1aQ, Worksheet-CHZQ, Worksheet-
BTQ, Worksheet-PP4Q, Worksheet-PP3Q, Worksheet-PP2Q, Worksheet-PP1Q, 
Worksheet-BF3Q, Worksheet-BF2Q). Note: Data from Worksheet-BTQ are assigned 
to HGU BTa; no data are identified in this DTN for HGUs BT1v, CHV, and BTv 
1a. Appropriate data from worksheets 039 wc and 039 wp are added to columns B, 
C, and E of worksheets BT1v, CHV, BTv, PP4, PP3, and BF3 
1b. Appropriate data from worksheet 99.008 S wp are added to columns B, D, and E 
of worksheets BT1v and CHV 
1c. Appropriate data from worksheet 007 S wp are added to columns B, D, and E of 
worksheet BT1v 
1d. Appropriate data from worksheets 001 wc wp are added to columns B, C, and E 
of worksheets BT1v and CHV 
1e. Appropriate data from worksheets 012 wc and 012 wp are added to columns B, 
C, and E of worksheets BT1a and CHZ 
1f. Appropriate data from worksheets 95.008 wc and 95.008 wp are added to 
columns B, C, and E of worksheets CHZ, PP4, PP2, and PP1 
1g Appropriate data from worksheet 96.003 wc wp are added to columns B, C, and 
E of worksheet CHV 
2. Same as step 2 above 
2a. Sample SD9-1440.5r, which was not within PV2 (see step 2a above) is within the 
BT1v and is added 
3. Same as step 3 above except for data from worksheets 007 S wp and 99.008 S wp 
where data are given in terms of saturation rather than water content 
3a. The saturation for the data from 1d is calculated assuming that the highest water 
content from either worksheet 001 wc wp or 001 wc K for that sample 
represents the water content at full saturation 
4. Same as step 4 above 
4a. Same as step 4a above 
5. Same as step 5 above 
5a. Same as step 5a above 
ANL-NBS-HS-000042 REV 00 A-20 October 2004 

Analysis of Hydrologic Properties Data 
6. Same as step 6 above 
7. Same as step 7 above 
8. Same as step 8 above 
9. Same as step 9 above 
10. Same as step 10 above 
10a. Plotting the estimated function for PP4 shows that the shape of the curve does not 
match well with the data. The parameters (a and n) are adjusted by hand to 
improve the subjective match between the shape of the curve and the data. This 
adjustment results in an increase of 0.951 (65 percent) in the sum of the squared 
error 
11. Same as step 11 above 
12. Same as step 12 above 
13. Same as step 13 above 
14. Same as step 14 above 
15. Same as step 15 above 
16. In worksheets BT1v and CHV only, appropriate unsaturated conductivity data from 
worksheets 99.008 S K, 007 S K, and 001 wc K are identified as in steps 1b, 1c, 
and 1d above, added to columns V, W, and X, and are plotted as circles connected by a 
dashed line 
16a. As in step 3a above, the saturation for the data from 001 wc K is calculated 
assuming that the highest water content from either worksheet 001 wc wp or 
001 wc K for that sample represents the water content at full saturation 
17. In worksheets BT1v and CHV only, same as step 17 above 
18. In worksheets BT1v and CHV only, same as step 18 above 
19. In worksheets BT1v and CHV only, same as step 19 above 
20. In worksheets BT1v and CHV only, same as step 20 above 
21. In worksheets BT1v and CHV only, same as step 21 above 
22. In worksheets BT1v and CHV only, same as step 22 above 
23. In worksheets BT1v and CHV only, same as step 23 above 
24. In worksheets BT1v and CHV only, same as step 24 above 
ANL-NBS-HS-000042 REV 00 A-21 October 2004 

Analysis of Hydrologic Properties Data 
vG_Summary_fin.xls (Output DTN: LB0207REVUZPRP.002) 
This file was used to develop matrix properties for UZ model layers. 
Note: This spreadsheet contains links to hydroprops_fin.xls, MRC_Q_TCw_fin.xls, 
MRC_Q_PTn_fin.xls, MRC_Q_TSw_fin.xls, and MRC_Q_CHCF_fin.xls; these spreadsheets 
must be open at the same time this spreadsheet is open. 
Worksheet vG Summary 
Values shown in columns C, D, E, G, H, and J are linked to the spreadsheets (above) where they 
are estimated. 
. (columns L and M) for CMW, CNW, BT4, BT3, TPP, BT2, PV2v, BT1v, 
and CHV are those estimated by fitting relative permeability data. Other values of . and s.are 
estimated as 
Values of . and s
k 
s
.= Am - B log()+ C 
and 
.=(A +s )m -(B +s )log(k )+(C +s )-.
AB C 
where m is the van Genuchten parameter, k is upscaled permeability, and A, B, and C are fitting 
parameters. Note: the minus sign before B is because . is correlated to log(k-1). The fitting 
parameters are estimated in worksheet fitted kr. 
Worksheet fitted kr 
For each layer, column A, where ., column D, has been estimated from relative permeability 
data, the estimates of upscaled permeability, column B, and the van Genuchten parameter m, 
column C, are given. 
The parameter . is predicted in column E using the equation given above and the parameters in 
cells F1:F3. The squared difference between the two values of . is calculated in column F and 
summed in cell F4. 
The Jacobian matrix (see step 11 under spreadsheet MRC_Q_TCw_fin.xls worksheet CUC) is 
calculated in columns G to I using the perturbed parameter values in cells G1:G3. The 
covariance matrix (see step 12 under spreadsheet MRC_Q_TCw_fin.xls worksheet CUC) is 
calculated in cells K5:M7. The standard error (see step 13 under spreadsheet 
MRC_Q_TCw_fin.xls worksheet CUC) is calculated in cells K1:K3. The parameter values 
perturbed by one standard error are given in cells N1:N3. 
lecan97.xls (Output DTN: LB0408REVUZPRP.001) 
This file was used for estimating fracture parameters. 
In this spreadsheet, only the workbook New Layers was used to calculated fracture 
permeability for UZ model layers that have been documented in the Model Report. Therefore, 
the documentation is limited to this workbook. 
ANL-NBS-HS-000042 REV 00 A-22 October 2004 

Analysis of Hydrologic Properties Data 
In this spreadsheet, columns A, B, and C contain data from DTN: GS960908312232.013 
[DIRS 105574]. Column D corresponds to log of air permeability calculated from column C. 
Columns H, I, J contain total number of air k measurements, average of log of air permeability 
and standard deviation of log(air permeability) for each geologic unit within a single borehole, 
respectively. Columns L, M, N contain total number of air k measurements, average of log of air 
permeability and standard deviation of log(air permeability) for each geologic unit for the 
boreholes, respectively. 
UTCA_BRFA.xls (Output DTN: LB0408REVUZPRP.001) 
This file was used for estimating fracture parameters. 
This spreadsheet contains two notebooks UPCA and UTCA_BRFA. In UPCA, columns A-E 
contain data from Alcove 3 (DTN: GS970183122410.001 [DIRS 105580]). Column F 
corresponds to log of air permeability calculated from column C. Columns H, I and J contain 
total number of air k measurements, average of log of air permeability and standard deviation of 
log(air permeability) for each geologic unit within a single borehole (labeled as location), 
respectively. Columns M, N and O contain total number of air k measurements, average of log of 
air permeability and standard deviation of log(air permeability) for each geologic unit for the 
boreholes, respectively. 
In UTCA_BRFA, columns C-E contain data from Alcove 1 (DTN: GS970183122410.001 
[DIRS 105580]). Column F corresponds to log of air permeability calculated from column E. 
Columns H, I, J, K contain total number of air k measurements, geometric mean of air k, log of 
geometric mean of air permeability and standard deviation of log(air permeability) for each 
geologic unit within a single borehole (labeled as location), respectively. Columns V, W and X 
contain total number of air k measurements, average of log of air permeability and standard 
deviation of log(air permeability) for each geologic unit for the boreholes, respectively. 
drift.xls (Output DTN: LB0408REVUZPRP.001) 
In this spreadsheet, column D contains air permeability data from DTNs: LB970600123142.001 
[DIRS 105589], LB980120123142.004 [DIRS 105590], LB980120123142.005 [DIRS 114134], 
and LB960500834244.001 [DIRS 105587]. Column E corresponds to log of permeability values 
calculated from column D. Columns J and K contain total number of air permeability 
measurements, geometric mean of log of air permeability and standard deviation of log(air 
permeability), respectively. 
airk.xls (Output DTN: LB0408REVUZPRP.001) 
This file was used for estimating fracture parameters. 
Since the equations used in the spreadsheet are simple standard functions of MS Excel, the 
supplementation needed here is a description of the specific cells that contain the input, output 
and calculation used in the spreadsheet application. A description of the equations is provided. 
This spreadsheet is linked to lecan97.xls, drift.xls and UTCA_BRFA.xls that discussed above. 
ANL-NBS-HS-000042 REV 00 A-23 October 2004 

Analysis of Hydrologic Properties Data 
In this spreadsheet, only the workbook New Layers was used to calculated fracture 
permeability for UZ model layers that has been documented in the Model Report. Therefore, the 
documentation is limited to this workbook. This spreadsheet calculates layer-averaged fracture 
permeability information based on air k data contained in lecan97.xls, UTCA_BRFA.xls and 
drift.xls. 
In the workbook New Layers, columns A, B, C, and D contain model layer name, total number 
of air k measurements from different sources, mean of log(air permeability), and the standard 
deviation of log(air permeability), respectively. 
To demonstrate the calculation procedure, model layer tcw12 is used as an example. In this 
discussion subscripts 1, 2, 3 refer to data from Lecan97.xls, UTCA (UTCA_BRFA.xls) and 
UPCA (UTCA_BRFA.xls), respectively. 
1. Cell B5 contains the total number of measurements, denoted by N, which was 
calculated as follows: Cells J4-J6 contain the number of measurements from the three 
data sources (N1, N2 and N3), respectively, by linking with the relevant cells in 
lecan97.xls and UTCA_BRFA.xls). The total number is given in Cell J7 calculated by 
N=N1+N2+N3 
The value in Cell J7 was then assigned to B5 
2. Cell C5 contains the mean of log(air permeability) (Xm) that was calculated as follows: 
Cells K4-K6 contain the means from the three data sources (Xm1, Xm2 and Xm3), 
respectively, by linking with the relevant cells in lecan97.xls and UTCA_BRFA.xls. 
Values in cells P4-P6 are calculated as N1Xm1, N2Xm2, and N3Xm3. Cell P7 summates 
values in the three cells. Then, the mean Xm was stored in cell K7 and calculated by 
Xm = (N1Xm1+N2Xm2+N3Xm3)/N= (the value in cell P7)/(the value in cell J4) 
The value in K7 was assigned to C5 
3. Cell D5 contains standard deviation of log(air permeability) (s) that was calculated as 
follows: Cells L4-L6 contain the standard deviation values from the three data sources 
( s1, s2 and s3), respectively, by linking with the relevant cells in lecan97.xls and 
UTCA_BRFA.xls. Variances in cells N4-N6 (s12, s22 and s32) were then calculated 
from cells L4-L6. Cells Q4 was calculated by 
N1
(X N 1m )2 +s 2 N1(N1 -1)=. xi 
2
11 
N1 i =1 
where xi refers to log(air permeability) for measurement i. Similar calculations were 
performed for the other two data sources. Cell Q7 summates values in the three cells 
ANL-NBS-HS-000042 REV 00 A-24 October 2004 

Analysis of Hydrologic Properties Data 
Q4-Q6. The value in Q7 corresponds to 
N 
. xi2
i =1
where N is the total number of measurements from the three data sources. If using the 
cell names to represent values in them, N7 was calculated as 
NN 
Q J 7 - (P7)2 N . xi 
2 - (NX m )2 . (xi - Xm )2 
7 = i =1 = i =1
N 7 = 
(
J 7(J 7 - 1)N N - 1)N - 1 
By definition, N7 is the overall variance of log(air permeability) for air k data from the 
three data sources. L7 contains the corresponding standard deviation calculated from 
N7. Its value was assigned to D5. 
A similar procedure was used for the model layers that have measurement from 
different sources. If a model layer only has data from a single source (lecan97.xls, 
drift.xls, and UTCA_BRFA.xls), the above calculation procedure was not needed. The 
relevant value can be directly obtained from the data source. Also in the spreadsheet, 
some standard deviation values were assigned to model layers that only contain one 
measurement. These values were not used 
Fpor.xls (Output DTN: LB0408REVUZPRP.001) 
This file was used for estimating fracture parameters. 
Sheet 1 contains fracture porosity values calculated from other sources (Section 6.1.3.4). The 
input sources and calculations are explicitly indicated in the workbook. 
In sheet 2, Column A contains names of UZ model layers and Column C contains the 
corresponding aperture values (output DTN: LB0205REVUZPRP.001). Column E contains van 
Genuchten acalculated using Equation 6-9. Column G contains fracture intensity or frequency 
values (DTN: LB990501233129.001 [DIRS 106787]). Column I contains fracture porosity 
values calculated from Equation 6-12. Column M contains log(a) values. Below Row 32 was 
used for estimating fracture porosity for tsw34. The input sources and calculations are explicitly 
indicated in the workbook for this estimation. 
ANL-NBS-HS-000042 REV 00 A-25 October 2004 

Analysis of Hydrologic Properties Data 
INTENTIONALLY LEFT BLANK 
ANL-NBS-HS-000042 REV 00 A-26 October 2004