3rd Response Submittal to the EPA Enclosure 1

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EPA Comment 

1-23-3 Region ROMPCS 

The Agency agreed to the adopted parameter values used of the panel closure change request to isolate 

the effects and facilitate a comparison of the proposed panel closure design on the baseline PA and, at 

the time of the planned changed request, there was uncertainty in the emplacement technique to be used. 

The Agency would like DOE to address the following comments on several parameters related to panel 

closures. 

1. Identify and technically justify that ranges of porosity and permeability for the ROM salt PCS 

during the time period 0 to 100 years (material PCS_T1) are consistent with initial emplacement 

of the ROM salt without wetting or compaction. 

2. Provide technical justification for applying a capillary pressure model that assumes zero 

threshold pressure to region ROMPCS during time periods 100 to 10,000 years (T2 and T3). 

3. Provide a technical justification for selecting the ranges for the residual brine and gas 

saturations (SAT_RBRN and SAT_RGAS) during time periods T2 and T3; the justification should 

include adopting a zero value as the low end. 

4. Provide technical justification for using the same value for the bulk compressibility of ROM salt 

during the T1, T2, and T3 time periods (from 0 to 100, 100 to 200, and 200 to 10,000 years). 

DOE Response 

The responses to EPA’s four comments are as follows: 

1. The ranges of porosity and permeability assumed for the run-of-mine (ROM) salt panel closure 

system (ROMPCS) for use in the PCS-2012 Performance Assessment (PA) were discussed in 

considerable detail in Camphouse et al. (2012a), as well as the exhaustive discussion of porositypermeability correlations in the U.S. Department of Energy’s (DOE’s) response to an EPA 

comment dated June 7, 2012, regarding the ROMPCS Planned Change Request (DOE 2012). 

These parameters were agreed to by EPA in an email from Tom Peake to Russ Patterson dated 

June 19, 2012. As discussed below, these values are consistent with the planned initial 

emplacement of the ROM salt, and DOE is not aware of any additional information which would 

give reason to modify them. 

The main component of the ROMPCS at the Waste Isolation Pilot Plant (WIPP) is 100 feet of 

ROM salt, which will be produced by ongoing mining operations, stored at convenient locations 

in the mine, and then installed in multiple lifts. Underground testing has demonstrated that frontend loaders and other existing equipment can push the ROM salt against the ribs and back of the 

panel access drifts, thereby filling the drift (Zimmerly et al. 2012). 

DOE does not intend to establish criteria for the initial condition of the salt pile or to monitor the 

as-emplaced conditions in the ROM salt. The grain size distribution of the ROM salt, its moisture 

content, and the degree of initial compaction will not be measured or controlled during 

installation. It is noted that the ROM salt will contain some moisture from inclusions in the 

grains and absorbed from humidity in the ventilation air, which may vary depending on the time 

of year it is emplaced. There are no plans to compact the salt in the pile, although there is 

expected to be some compaction of lower lifts from the multiple passes of emplacement 

equipment, such as front-end loaders. In this situation, the initial conditions of the ROM salt are 

uncertain. 
3rd Response Submittal to the EPA Enclosure 1

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After installation, the ROM salt pile will consolidate due to closure of the panel access drifts. The 

rate of this consolidation, and hence of the change in porosity and permeability over time, will 

vary depending on a number of factors. Moisture content may vary depending on the time of year 

and the varying humidity of the ventilation air. Closure rates of the panel access drifts will vary 

between panels depending on the local loading conditions and the time that the panel entries have 

been open before emplacing the salt. These factors add additional uncertainty to the timing of the 

reconsolidation process for ROM salt in the ROMPCS. 

Given these uncertainties, DOE chose an appropriate range of initial porosities for the ROM salt 

for the PCS-2012 PA. As described in Camphouse et al. (2012a), the range of initial porosity 

chosen had a minimum of 20% and a maximum of 35%. The maximum initial porosity of 35% is 

assumed from typical data for unconsolidated granular materials such as sand or gravel (e.g., Bear 

1972, Table 2.5.1). The minimum initial porosity of 20% is intended to represent ROM salt with 

a higher level of moisture content and with some compaction during the emplacement process, 

and represents a lower bound established using engineering judgment. 

As discussed in Camphouse et al. (2012a), the porosity of the ROM salt during the first time 

period of 0 to 100 years will decrease rapidly due to compaction driven by closure of the entries. 

A series of JAS3D calculations has been run to estimate the porosity as a function of time for 

different initial values (Herrick 2012). Given the rapid change in porosity, it was considered 

reasonable to define the range of porosity for this time period based upon the calculated values at 

the mid-point, or 50 years. For an assumed initial porosity range of 20% to 35%, the 50-year 

values calculated by JAS3D are 6.6% to 18.7%. No new data or analyses are available, so there 

are no reasons to modify this range of values at this time. 

The permeability of the ROM salt during the T1 period, from 0 to 100 years, is based on 

laboratory data for crushed salt cores from WIPP and from the Asse mine in Germany 

(Camphouse et al. 2012a, Section 5.1.2 and Tables 3 and 4; DOE 2012). The range of 

permeability during the T1 period is based on the porosity range at the midpoint of the T1 period 

(50 years) described above of 6.6% to 18.7%. The corresponding range of permeability based on 

the laboratory data is 1×10-12 m2

 to 2×10-19 m2 (Camphouse et al. 2012a, Table 5 for PCS_T1). 

This range of permeability is consistent with the assumed initial porosity range of the ROM salt, 

captures the uncertainties in the initial state and reconsolidation process, and is appropriate for 

performance assessment. No new data are available, so again there is no reason to modify these 

values at this time. 

2. The capillary threshold pressure model used for the PCS-2012 PA is discussed by Camphouse in 

his June 7 memorandum (2012b). As he explains, values for threshold pressure can be estimated 

using a best-fit power curve to capillary threshold pressure data for several types of consolidated 

rock (Vaughn 1996): 

 PT = (5.6×10-7 [MPa])k

-0.346, (1) 

where PT is the capillary threshold pressure [MPa] and k is the intrinsic permeability in the xdirection [m2

] (see also Hurtado 1997, Section 3.2.1.1). Equation (1) has been included in the 

BRAGFLO code since the Compliance Certification Application (CCA) (Vaughn 1996) and 

provides a dynamic dependence of capillary threshold pressure on permeability. Using this 

relationship, separate values for the threshold pressure can be set for times T1, T2 and T3 based 

on their respective sampled values for permeability. 

 
3rd Response Submittal to the EPA Enclosure 1

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However, as explained in Camphouse (2012b), in BRAGFLO: 

“Instantaneous changes in permeability, due to material changes in a grid region, cause 

difficulty in numerically satisfying the convergence criterion for the capillary pressure 

constraint equation. When the convergence criterion cannot be satisfied, the capillary 

pressure model is disabled for the responsible materials so that a convergent solution can 

be obtained from BRAGFLO. The flag for this is to set PCT_A = 0, which results in the 

capillary pressure component to be disabled.” 

He goes on to note that: 

“BRAGFLO grid regions used to represent the ROM salt panel closures in the PCS-2012 

will undergo instantaneous changes in permeability. Specifically, the permeability 

prescribed to these BRAGFLO grid regions will change instantaneously at 100 and 200 

years as closure materials change from PCS_T1 to PCS_T2 and from PCS_T2 to PCS_T3 

(Camphouse et al. 2012).”1

Because of these numerical issues, the capillary pressure model was disabled in the PCS-2012 

PA. 

It should be noted that the capillary threshold pressure is not a sensitive parameter for the flow of 

gases through the ROMPCS for the following reasons: 

 In the higher permeability range, from 10-16 m2

 to 10-18 m2, capillary threshold pressure 

calculated from Equation (1) varies between 0.19 MPa (28 psi) and 0.95 MPa (140 psi). 

These low values of threshold pressure will have minimal impact on hydrologic response 

because typical repository gas pressures are almost always greater than 0.95 MPa (140 

psi). For example, waste panel pressures in the S1, S2, and S4 scenarios are almost 

always greater than 1 MPa in the performance assessment for CRA-2014 (DOE 2014, 

Appendix PA-2014, Figures PA-35, PA-50, and PA-56). In this case, setting PT to zero 

has no impact on hydrologic response because gas pressure almost always exceeds the 

threshold pressure and gas can therefore flow into and through the ROM salt. 

 In the lower permeability range, from 10-19 m2

 to 10-22 m2, the capillary threshold pressure 

calculated from Equation (1) varies between 2.1 and 23 MPa, and could provide a 

significant impediment to gas penetrating the ROMPCS. However, hydrologic flow rates 

for brine or gas through any material with intrinsic permeability less than 10-19 m2

 are 

sufficiently low that the material is essentially impermeable. In this situation, the gas 

flow through the ROMPCS is insignificant for any value of PT, and setting PT to zero has 

no impact on the hydrologic response. 

                                                           

1

 The quoted reference corresponds to Camphouse et al. (2012a) in this response.
3rd Response Submittal to the EPA Enclosure 1

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3. The residual saturations for brine and gas, which have been used since the CCA when they were 

established for use in the shaft seals, are based on extensive data from a literature search for 

geologic materials. The literature search and resulting parameter values are described by Hurtado 

et al. (1997, Section 3.2.2) and the relevant information is repeated here. It should be noted that 

calculated repository performance is not sensitive to these parameters, as discussed below. 

Residual liquid saturations for geologic materials were found in four references: Brooks and 

Corey 1964; Lappala et al. 1987; Parker et al. 1987, and Rawls et al. 1982. Brooks and Corey 

(1964) determined residual saturations for five unconsolidated samples based on measured values 

of liquid saturation as a function of capillary pressure. Lappala et al. (1987) determined residual 

moisture content for 11 soils by obtaining best fits to measured moisture content versus pressure 

head data using three models. The residual moisture contents from the three models were then 

averaged and divided by the reported porosity to determine residual liquid saturation for each 

soil. Parker et al. (1987) fit their saturation-pressure relationship to observed data to obtain 

residual saturations for a sandy and clayey porous medium. Residual water contents reported by 

Rawls et al. (1982) for 11 soil texture classes were divided by the reported porosity to obtain 

residual saturation. 

The values of the residual saturation from the literature search are summarized in graphical form 

in Figure 1 (from Hurtado et al. 1997, Figure 3-2). All values in Figure 1 fall within the range of 

0.0 to 0.6 and all but two values fall within the range of 0.0 to 0.4. Hurtado et al. (1997, Section 

3.2.2.2) recommended an expected value of 0.2 and a range of 0.0 to 0.6 for the residual liquid 

saturation for all shaft seal materials, including crushed salt. For compliance calculations, this has 

been represented as a cumulative distribution with a minimum value of 0.0, a maximum value of 

0.6, and a mode of 0.2 at the 50th percentile (DOE 2004, Appendix PA, Attachment PAR, 

Parameter 62). This is the recommended distribution for the ROM salt in the ROMPCS and has 

been used in the PCS-2012 PA and for the CRA-2014 PA. The lower value for this distribution 

of 0 comes from a “Sandy Porous Media” reported as 0.000 by Parker et al. (1987). The upper 

bound of 0.6 comes from two samples and could be interpreted as too high since most data fall 

below 0.4. However, given the natural uncertainties and variation in the residual brine saturation 

and the fact that PA is not sensitive to it (as discussed next), the value of 0.6 is retained. 

Repository performance is not sensitive to the residual brine saturation or the residual gas 

saturation of the ROMPCS, as confirmed by the sensitivity study for the CRA-2014 PA (Kirchner 

2013). More specifically, PCS_Ti:SAT_RBRN and PCS_Ti:SAT_RGAS (i = 1, 2, or 3) are not 

identified as correlated with mean normalized release for Replicates 1, 2, or 3 of the CRA-2014 

PA (Kirchner 2013, Tables 6 through 13), with a single exception. The exception is for 

PCS_T1:SAT_RBRN, which explains 2% of the variability for Culebra releases in Replicate 3 

(only) (Kirchner 2013, Table 13). This correlation is not important because it only enters the 

stepwise ranked regression analysis for one of the three replicates, and because Culebra releases 

are not significant to overall performance of the repository. 
3rd Response Submittal to the EPA Enclosure 1

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Source: (Hurtado et al. 1997, Figure 3-2)

Figure 1. Distribution of residual liquid saturation values by geologic material

Literature values for residual gas saturation of geologic materials were not found by Hurtado et 

al. (1997). A single value of 0.18 was found for normal concrete. Given the lack of data, the 

expected value was set at 0.2 and the recommended range was 0.0 to 0.4 with a uniform 

distribution. This is the recommended distribution for the ROM salt in the ROMPCS and has 

been used in the PCS-2012 PA and for the CRA-2014 PA. 

4. The recommended value for the bulk compressibility of the ROM salt is 8×10-11 Pa-1 during the 

T1 (0-100 years), T2 (100-200 years), and T3 (200-10,000 years) time periods (Camphouse et al. 

2012a, Section 5.1.5 and Table 8). It is appropriate to use this value for all time periods because 

BRAGFLO only uses bulk compressibility to compute changes in storativity due to changes in 

pore pressure, and those changes are not significant during the T1, T2, or T3 time periods. 

Changes in porosity due to external loading are calculated separately using fully mechanistic 

modeling with JAS3D (Herrick 2012). Given this use of the bulk compressibility, the use of a 

constant value of 8×10-11 Pa-1 is appropriate because it is representative in all time periods. A 

more detailed explanation follows. 

The recommended value is based on a nonlinear model relating bulk modulus to fractional 

density (Hurtado et al. 1997, pages 2-20 and 2-21) that was originally developed by Sjaardema 

and Krieg (1987): 
3rd Response Submittal to the EPA Enclosure 1

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( . MPa )e ,

K Ae ,

( . )

B





14 10  0 0176

 (2) 

where K is the bulk modulus,  is the fractional density, and A and B are fitting parameters. The 

value of 8x10-11 Pa-1 is appropriate for a porosity of 0.05, or fractional density as defined by 

Hurtado et al. (1997) (equation 2-10) of 0.956. The porosity of 0.05 corresponds to the mean 

porosity for ROM salt during the T2 time period and is slightly less than the lower end of the 

porosity distribution during the T1 time period, and slightly less than the upper end of the 

porosity distribution for ROM salt during the T3 time period (Camphouse et al. 2012a, Table 2). 

The resulting value for bulk compressibility of ROM salt is close to the median value for the bulk 

(rock) compressibility of intact halite, 9.75×10-11 Pa-1 (DOE 2004, Chapter 6, Table 6-16). A 

value of 8×10-11 Pa-1 for the bulk compressibility of ROM salt is therefore appropriate for the T1, 

T2, and T3 time periods.

Throughout the regulatory period of 10,000 years, the ROM salt porosity used by BRAGFLO in 

the three time periods is obtained by sampling a porosity range developed from JAS3D 

mechanical calculations, which are used to predict the time-dependent compaction of the ROM 

salt as a function of initial porosity. This process is discussed in Camphouse (2012a) and is noted 

in the answer to the first question. As noted in Camphouse (2012a), the porosity ranges sampled 

will vary by time period. During T1 the range is 6.6% to 18.7%, during T2 2.5% to 7.5%, and 

during T3 0.1% to 5.19%. 

Bulk compressibility in BRAGFLO, and its related value of pore volume compressibility, is used 

to account for porosity changes due to pore pressure changes in the halite surrounding the waste 

rooms, and thus changes in storativity. The bulk compressibility is defined by Freeze and Cherry 

(1979, page 54): 

, d

dV

V

c

e

T

T 

1   (3) 

where c is the compressibility, VT is the total volume of the medium, and e is the effective stress. 

The BRAGFLO code uses a modified form of Equation (3) to define porosity changes in a porous 

medium: 

  p p . c

exp r





 



   0 0 0

 (4) 

where  is porosity [unitless], p is the brine pressure in the pores [Pa], cr is the bulk 

compressibility [Pa-1], and the subscript 0 denotes initial conditions (DOE 2014, Appendix PA2014, Equations (PA.30) and (PA.37)). This formulation is appropriate for the halite around the 

waste panels, where changes in the external confining stress will be minimal, so the only 

significant change in effective stress comes from changes in pore pressures. 

For the ROM salt in the panel closure both the external loading and the pore pressures will 

change as a function of time, so Equation (4) will have a time-varying effect on the porosity. 

However, it can be shown that this effect is extremely small. During the T1 time period, the 

numerical values for the parameters in Equation (4) are as follows: 
3rd Response Submittal to the EPA Enclosure 1

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 The pore pressure, p, is set to its maximum value, 7×105

 Pa, during the T1 time period. 

 The initial pore pressure, p0, is set to atmospheric pressure, 1.01×105

 Pa. 

 The rock or bulk compressibility, cr, is equal to 8×10-11 Pa-1, as discussed above. 

Table 1 presents the calculated changes in porosity where the initial porosity, 0, is 0.20, 0.25, 

0.30, or 0.35 (Camphouse et al. 2012a, Table 1). 

Table 1. Porosity changes predicted by Equation (3) during the T1 time period 

0 0.20 0.25 0.30 0.35 

0

 1.00024 1.00019 1.00016 1.00014 

% change 0.024% 0.019% 0.016% 0.014% 

The results in Table 1 demonstrate that the porosity changes in time T1 induced by pore 

compressibility are less than 0.03% of the initial porosity for all initial conditions. This 

conclusion is also valid during the T2 and T3 time periods. For example, using the bulk 

compressibility of 8×10-11 Pa-1, the mean porosity for time T2 of 0.05, and a maximum pore 

pressure of 14 MPa, the porosity change induced by pore compressibility is around 1.8% of the 

initial porosity. 

These calculated porosity changes are minimal compared to the changes built into the assumed 

porosity ranges from the JAS3D calculations, so it follows that the porosity changes computed 

from bulk compressibility are not significant during the T1, T2, or T3 time periods, and the use of 

a constant value for rock compressibility of 8×10-11 Pa-1 is appropriate for compliance 

calculations. 

References: 

Brooks, R.H., and A.T. Corey. 1964. Hydraulic Properties of Porous Media. Hydrology Paper 

No. 3. ERMS 241117. Colorado State University, Fort Collins, CO.2

Bear, J. 1972. Dynamics of Fluid Flow in Porous Media. Elsevier, NY, 1972.*

Camphouse, R.C., M. Gross, C.G. Herrick, D.C. Kicker, and B. Thompson. 2012a. 

Recommendations and Justifications of Parameter Values for the Run-of-Mine Salt Panel Closure 

System Design Modeled in the PCS-2012 PA. Memorandum to WIPP Records dated May 3, 

2012. ERMS 557396. Sandia National Laboratories, Carlsbad NM. 

Camphouse, R.C. 2012b. An overview of the BRAGFLO two-phase flow parameters used to 

model the run-of-mine salt panel closures implemented in the PCS-2012 PA. Memorandum to 

WIPP Records dated June 7, 2012. ERMS 557653. Sandia National Laboratories, Carlsbad, NM. 

Freeze, R.A. and J.A. Cherry. 1979. Groundwater. Prentice Hall, Englewood Cliffs, NJ.*

                                                           

2

 Brooks and Corey (1964) was submitted to EPA as a reference for Appendix BRAGFLO of the CCA. 

*

Copyrighted reference not provided in Enclosure 2. 
3rd Response Submittal to the EPA Enclosure 1

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Herrick, C.G. 2012. JAS3D Calculations Performed in Support of the PCS-2012 PA Parameters 

Selections. April 30, 2012. ERMS 557354. Sandia National Laboratories, Carlsbad, NM. 

Hurtado, L.D., M.K. Knowles, V.A. Kelly, T.L. Jones, J.B. Ogintz, and T.W. Pfeifle. 1997. 

WIPP Shaft Seal System Parameters Recommended to Support Compliance Calculations. 

SAND97-1287. Sandia National Laboratories, Albuquerque, NM. 

Kirchner, T. 2013. Sensitivity of the CRA-2014 Performance Assessment Releases to 

Parameters. May 17, 2013. ERMS 560043. Sandia National Laboratories, Carlsbad, NM. 

Lappala, E.G., R.W. Healy, and E.P. Weeks. 1987. Documentation of Computer Program VS2D 

to Solve the Equations of Fluid Flow in Variably Saturated Porous Media. Water-Resources 

Investigations Report 83-4099. U.S. Geological Survey, Denver, CO. 

Parker, J. C., R.J, Lenhard, and T. Kuppusamy. 1987. A Parametric Model for Constitutive 

Properties Governing Multiphase Flow in Porous Media. Water Resources Research. Vol. 23, 

no. 4, 618-624.*3

Rawls, W.J., D.L. Brakensiek, and K.E. Saxton. 1982. Estimation of Soil Water Properties. 

Transactions of the ASAE (American Society of Agricultural Engineers). Vol. 25, no. 5, 1316-

1320 and 1328.*

Sjaardema, G.D. and R.D. Krieg. 1987. A Constitutive Model for the Consolidation of WIPP 

Crushed Salt and Its Use in Analyses of Backfilled Shaft and Drift Configurations. SAND88-

1977. Sandia National Laboratories, Albuquerque, NM. 

U.S. Department of Energy (DOE). 2004. Title 40 CFR Part 191 Compliance Recertification 

Application for the Waste Isolation Pilot Plant (March). 10 vols. DOE/WIPP 2004-3231. 

Carlsbad Field Office, Carlsbad, NM. 

U.S. Department of Energy (DOE). 2012. Response to EPA Comment Dated June 7, 2012: 

Review of Alternate Data Sets for Defining Permeability of Crushed Salt. Transmitted via EMail from Russell Patterson, DOE, to Tom Peake, EPA, on June 15, 2012. Carlsbad Field Office, 

Carlsbad, NM. 

U.S. Department of Energy (DOE). 2014. Title 40 CFR Part 191 Subparts B and C Compliance 

Recertification Application-2014 for the Waste Isolation Pilot Plant (March). DOE/WIPP-14-

3503. Carlsbad Field Office, Carlsbad, NM. 

Vaughn, P. 1996. KPT Modeling Feature. Memorandum to Martin Tierney dated February 19, 

1996. ERMS 235271. Sandia National Laboratories, Carlsbad, NM. 

Zimmerly, B., T. Moffatt, and J. Zavicar IV. 2012. Construction Methods Assessment for 

Compacted Salt Panel Closures (December). Nuclear Waste Partnership LLC, Carlsbad, NM.

                                                                                                                                                                                                *

Copyrighted reference not provided in Enclosure 2. 

3

Parker et al. (1987) was submitted to EPA as a reference for Appendix C, Fluid Flow Analysis, which is part of 

Appendix SEAL of the CCA. 
3rd Response Submittal to the EPA Enclosure 1

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EPA Comment 

1-23-4 Region DRZ_PCS 

The Agency would like DOE to address the following comments related to the parameter values adopted 

for the DRZ_PCS: 

1. Provide technical justification for assigning the same sampled value of porosity to the material in 

DRZ_PCS region for both early and late time periods (T2 and T3) when the DRZ is undergoing 

consolidation and healing. 

2. Provide technical justification for the apparent discrepancy created by independently sampling 

the permeability of material DRZ_PCS, representing a healed DRZ, from a distribution that can 

provide a sampled permeability as much as seven orders of magnitude higher than the 

permeability of intact halite. 

3. Provide technical justifications for assigning zero values to the residual brine and gas 

saturations (SAT_RBRN and SAT_RGAS) in CRA-2014 for the region DRZ_PCS during the T3 

time period (200 to 10,000 years). 

4. Provide technical justification for applying a capillary pressure model that assumes zero 

threshold pressure in region DRZ_PCS during the T3 time period (200 to 10,000 years). 

5. Provide technical justification for the value of the bulk compressibility of the DRZ_PCS region, 

and applying that same value during both early and late time periods (T2 and T3) when the 

material in that region is undergoing consolidation. 

DOE Response 

The various items in this comment refer to the region in the BRAGFLO grid identified as DRZ_PCS, 

primarily during the T2 and T3 time periods (100-200 years and >200 years). The DRZ_PCS 

corresponds to the areas above and below the panel closures where the surrounding halite has been 

disturbed during mining, but where, as external stress is applied due to consolidation of the ROMPCS, the 

disturbance, and hence the porosity will be healed. Strictly speaking, the region identified as DRZ_PCS is 

only differentiated in the BRAGFLO grid for the T3 period; for the T1 and T2 periods the regions 

representing the DRZ_PCS have properties that are identical with the DRZ around the waste panels. 

Figures MASS-7, MASS-8, and MASS-9 (DOE 2014, Appendix MASS-2014), reproduced below, 

illustrate the evolution of the DRZ_PCS regions during the T1, T2, and T3 time periods, respectively. In 

the following response, the nomenclature “DRZ_PCS” will be used more loosely to refer to the DRZ 

above and below the panel closures during any of the time periods. 
3rd Response Submittal to the EPA 

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Figure MASS-7. CRA-2014 PA BRAGFLO grid and material map, years 0 to 100 
3rd Response Submittal to the EPA 

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Figure MASS-8. CRA-2014 PA BRAGFLO grid and material map, years 100 to 200 
3rd Response Submittal to the EPA 

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Figure MASS-9. CRA-2014 PA BRAGFLO grid and material map, years 200 to time of intr
3rd Response Submittal to the EPA Enclosure 1 

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The responses to EPA’s five comments are as follows: 

1. The DRZ_PCS region covers the area above and below the panel closure where the surrounding 

halite has been disturbed during mining, but where, as external stress is applied due to 

consolidation of the ROMPCS, the disturbance, and hence the porosity will be healed. The 

porosity of the DRZ around the waste emplacement area is calculated from the porosity of the 

intact halite, which is sampled from a range of 0.1% to 5.19% (Ismail 2007). The DRZ porosity 

is calculated by adding 0.0029 to the sampled value of porosity for intact halite (Vaughn 1996a). 

The value 0.0029 was determined prior to the Compliance Certification Application (CCA) as the 

difference between the median value of intact halite porosity and the median DRZ porosity value 

obtained from the Q-Room experiments (Christian-Frear 1996). 

During times T1 and T2, before the DRZ_PCS is fully loaded due to consolidation of the 

ROMPCS, the porosity of the DRZ_PCS regions are equal to the porosity of the DRZ 

surrounding the waste emplacement areas. During time T3, while it is recognized that the DRZ 

will have experienced some healing due to consolidation of the ROMPCS, the porosity is kept 

unchanged for two primary reasons: 

 There is considerable uncertainty in the porosity values for intact halite and for the DRZ, 

which are available from laboratory and in situ testing. With an assumed range of halite 

porosity of 0.1% to 5.19%, the value of the DRZ porosity has a range of 0.39% to 5.48% 

(Ismail 2007). This range adequately covers the likely porosity both before and after full load 

is applied to the DRZ (i.e., for times T1, T2 and T3). 

 The results of PA calculations are not sensitive to the porosities of the DRZ and DRZ_PCS 

within their given ranges. Both of these values are derived from the sampled value of intact 

halite porosity, as noted above, by adding a constant value of 0.0029. The sensitivity study 

for the CRA-2014 PA (Kirchner 2013) indicates that for total mean normalized release, the 

intact halite porosity contributes 1% of the variability in Replicates 1 and 2 and 3% of the 

variability in Replicate 3 (Kirchner 2013, Tables 6 and 7). Since the DRZ porosity is 

calculated from this sampled value, an identical result also holds for the DRZ porosity. In 

addition, the porosity of the DRZ_PCS during the T1, T2, or T3 time periods is not within the 

top 8 sensitive parameters for Replicates 1, 2, or 3 for mean total normalized release 

(Kirchner 2013, Tables 6 and 7). In this situation, creating and using a time-dependent model 

for porosity of the DRZ or the DRZ_PCS adds no value to the assessment of long-term 

repository performance. 

2. Initially, it is assumed that the DRZ around the PCS will be no different from that around the 

disposal rooms since there will be only a small back stress from the consolidating ROM salt in 

the ROMPCS. Geomechanical calculations for closure of panel entries and consolidation of the 

ROM salt predict that the back stress from the ROM salt does not become appreciable until 

approximately 200 years after the ROM salt is emplaced (Herrick 2012, Section 5.2). While the 

back stress is low, the state of the DRZ surrounding the PCS will be similar to the state of the 

DRZ surrounding the disposal rooms, and the values of porosity and permeability of the 

DRZ_PCS during the T1 (0 to 100 years) and T2 (100 to 200 years) time periods have been set 

equal to those for the disposal room DRZ. The permeability of the DRZ_PCS therefore has a 

range of 10-12.5 m2

 to 10-19.4 m2 for the first 200 years after repository closure. Further details are 

provided in Camphouse et al. (2012a, Section 5.2.1). 

At 200 years (the start of the T3 time period), back stress builds up to values between 6 and 10 

MPa, and fractures in the DRZ above the ROMPCS should begin to heal; by 500 years the back 
3rd Response Submittal to the EPA Enclosure 1 

14

stress reaches about 12 MPa (Camphouse et al. 2012a, Figures 9 and 10 and discussion on pages 

21 and 22). The recommended range of permeability for the DRZ_PCS is 2×10-21 m2

 to 1×10-17

m2

 during the T3 time period. This recommendation is based on permeability measurements for 

cores of crushed salt and the range represents the uncertainty in the degree and timing of 

reconsolidation in the DRZ_PCS. This range is significantly greater than the permeability range 

for intact halite, which is 10-24 m2

 to 10-21 m2, for the following reasons: 

 As noted above, the DRZ begins to heal when the back stress builds up to 6 to 10 MPa 

after 200 years. However, the timing for complete healing of the DRZ is uncertain. The 

JAS3D calculations predict that the back stress approaches 12 MPa by 500 years (Herrick 

2012, Figures 9 through 13) and may slowly increase to full lithostatic stress, 

approximately 14 MPa, thereafter. Full healing of the DRZ may require thousands of 

years to approach the extremely low permeability of intact salt. There is no discrepancy 

if the DRZ, even after some healing, has a permeability somewhat higher than the very 

low values for intact halite strata that have been undisturbed for millions of years. 

 Given the uncertainty in the timing of the healing process, PA represents a range of flow 

rates through the DRZ_PCS. At the high end of the permeability range, 1×10-17 m2

, the 

permeability of the DRZ_PCS is similar to that of concrete. At the low end of the 

permeability range, 2×10-21 m2

, the DRZ_PCS is essentially impermeable (i.e., no flow) 

and similar to the intact salt. This approach provides an appropriate range of hydrologic 

responses for the DRZ_PCS, thereby capturing the uncertainty in the timing of the 

healing process for performance assessment. 

An alternative to this approach is to use the permeability range for intact halite for the 

DRZ during T3. This is not appropriate because DOE does not have data or analyses to 

prove that the DRZ fully heals by 200 years. 

 Independent analytic work by EPA has shown that mean total normalized releases are 

insensitive to the range of DRZ_PCS permeability during the T3 time period. EPA 

performed an independent PA using a revised permeability range for the DRZ_PCS of 

1×10-22 m2

 to 1×10-20 m2 during the T3 time period (Economy 2013). The results of the 

EPA’s independent PA demonstrated that mean total normalized releases are essentially 

equal for the EPA’s or the DOE’s distributions for DRZ_PCS permeability in the PCS2012 PA (Economy 2014). 

3. The residual saturations for brine and gas, which have been used since the CCA when they were 

established for use in the shaft seals, are based on extensive data from a literature search for 

geologic materials. The literature search and resulting parameter values are described by Hurtado 

et al. (1997, Section 3.2.2) and included in the answer to item #3 of our response to Comment 

1-23-3, and are not repeated here. 

All values from this literature search fall within the range of 0.0 to 0.6, and all but two values fall 

within the range of 0.0 to 0.4. For compliance calculations, this has been represented as a 

cumulative distribution with a minimum value of 0.0, a maximum value of 0.6, and a mode of 0.2 

at the 50th percentile (DOE 2004, Appendix PA, Attachment PAR, Parameter 62). This is the 

recommended distribution for the DRZ_PCS during T1, T2, and T3, and has been used in the 

PCS-2012 PA and for the CRA-2014 PA. 

The lower value for this distribution of 0 comes from a “Sandy Porous Media” reported as 0.000 

by Parker et al. (1987), and is the lower bound of the distribution, rather than a fixed value used 
3rd Response Submittal to the EPA Enclosure 1 

15

in the calculations. It should be noted that repository performance is not sensitive to the residual 

brine saturation or the residual gas saturation of the DRZ_PCS during T3, as confirmed by an 

independent PA performed by the EPA. The EPA chose a residual brine saturation of 0.1 and a 

residual gas saturation of 0.05 for the DRZ_PCS during T3 (Economy 2014, Table 1) and 

compared the results to those from the PCS-2014 PA (Camphouse 2012a, Table 11). The results 

of the EPA’s independent PA demonstrated that mean total normalized releases are essentially 

equal for the EPA’s values or the DOE’s values of residual saturation in the DRZ_PCS (Economy 

2014, Figure 4). 

4. The capillary threshold pressure model used for the PCS-2012 PA is discussed by Camphouse in 

his June 7 memorandum (Camphouse 2012b). As he explains, values for threshold pressure can 

be estimated using a best-fit power curve to capillary threshold pressure data for several types of 

consolidated rock (Vaughn 1996b): 

PT = (5.6×10-7 [MPa])k

-0.346, (1) 

where PT is the capillary threshold pressure [MPa] and k is the intrinsic permeability in the 

x-direction [m2

] (see also Hurtado 1997, Section 3.2.1.1). Equation (1) has been included in the 

BRAGFLO code since the CCA (Vaughn 1996b) and provides a dynamic dependence of 

capillary threshold pressure on permeability. Using this relationship, separate values for the 

threshold pressure can be set for times T1, T2 and T3 based on their respective sampled values 

for permeability. 

However, as explained in Camphouse (2012b), in BRAGFLO: 

“Instantaneous changes in permeability, due to material changes in a grid region, cause 

difficulty in numerically satisfying the convergence criterion for the capillary pressure 

constraint equation. When the convergence criterion cannot be satisfied, the capillary 

pressure model is disabled for the responsible materials so that a convergent solution can 

be obtained from BRAGFLO. The flag for this is to set PCT_A = 0, which results in the 

capillary pressure component to be disabled.” 

He goes on to note that: 

“BRAGFLO grid regions used to represent the ROM salt panel closures in the PCS-2012 

will undergo instantaneous changes in permeability. Specifically, the permeability 

prescribed to these BRAGFLO grid regions will change instantaneously at 100 and 200 

years as closure materials change from PCS_T1 to PCS_T2 and from PCS_T2 to PCS_T3 

(Camphouse et al. 2012).”1

Because of these numerical issues, the capillary pressure model was disabled in the PCS-2012 PA 

and in the CRA-2014 PA. 

It should be noted that the capillary threshold pressure is not a sensitive parameter for the flow of 

gases through the DRZ_PCS for the following reasons: 

 In the higher DRZ_PCS permeability range, from 10-18 m2

 to 10-17 m2, capillary threshold 

pressure calculated from Equation (1) varies between 0.19 MPa (28 psi) and 0.95 MPa 

                                                           

1

 The quoted reference corresponds to Camphouse et al. (2012a) in this response.
3rd Response Submittal to the EPA Enclosure 1 

16

(140 psi). These low values of threshold pressure will have minimal impact on hydrologic 

response because typical repository gas pressures are almost always greater than 0.95 

MPa (140 psi). For example, waste panel pressures in the S1, S2, and S4 scenarios are 

almost always greater than 1 MPa in the performance assessment for CRA-2014 (DOE 

2014, Appendix PA-2014, Figures PA-35, PA-50, and PA-56). In this case, setting PT to 

zero has no significant impact on the hydrologic response because gas pressure almost 

always exceeds the threshold pressure and gas can therefore flow into and through the 

DRZ_PCS.

 In the lower permeability range, from 10-21 m2

 to 10-19 m2, the capillary threshold pressure 

calculated from Equation (1) varies between 2.1 and 23 MPa, and could provide a 

significant impediment to gas penetrating the DRZ_PCS. However, hydrologic flow 

rates for brine or gas through any material with intrinsic permeability less than 10-19 m2

are sufficiently low that the material is essentially impermeable. In this situation, the gas 

flow through the DRZ_PCS is insignificant for any value of PT, and setting PT to zero has 

no impact on the hydrologic response.

5. The recommended value for the bulk (or rock) compressibility of the DRZ_PCS is 7.41×10-10 Pa-1

during the T1 (0-100 years), T2 (100-200 years), and T3 (200-10,000 years) time periods (DOE 

2004, Appendix PA, Attachment PAR, Table PAR-33). This value has been used since the CCA 

as noted by Vaughn (1996a), and this bulk compressibility is only used to determine changes in 

storativity in BRAGFLO. 

The permeability of the DRZ_PCS is the dominant parameter in determining flow through the 

DRZ_PCS, not changes in storativity; therefore, since permeability is not affected by 

compressibility effects, the use of a constant value for compressibility is appropriate. Any minor 

changes in porosity from bulk compressibility will not have a significant impact on hydrological 

response of the DRZ_PCS. A more detailed explanation follows. 

Bulk compressibility in BRAGFLO, and its related value of pore volume compressibility, is used 

to account for porosity changes due to pore pressures changes in the halite surrounding the waste 

rooms, and thus changes in storativity. The bulk compressibility is defined by Freeze and Cherry 

(1979, page 54): 

, d

dV

V

c

e

T

T 

1   (2) 

where c is the compressibility, VT is the total volume of the medium, and σe is the effective stress. 

The BRAGFLO code uses a modified form of Equation (2) to define porosity changes in a porous 

medium: 

  p p . c

exp r





 



   0 0 0

 (3) 

where  is porosity [unitless], p is the brine pressure in the pores [Pa], cr is the bulk 

compressibility [Pa-1], and the subscript 0 denotes initial conditions (DOE 2009, Appendix 

PA-2009, Equations (PA.30) and (PA.37)). For the DRZ surrounding the panel closure both the 

external loading and the pore pressures will change as a function of time, so Equation (3) will 
3rd Response Submittal to the EPA Enclosure 1 

17

have a time varying effect on the porosity. However, it can easily be shown that this effect is 

extremely small. 

Table 1 presents the calculated changes in porosity during the T2 and T3 time periods for the bulk 

compressibility of 7.41×10-10 Pa-1 and a maximum pore pressure of 14 MPa, and starting 

porosities covering the range calculated from the intact halite range. The magnitude of the 

porosity changes for initial porosities equal to or greater than 0.01 is less than 0.02 and will not 

have a significant impact on the hydrologic response of the repository. This is clear by 

considering the volume of the DRZ_PCS above and below a panel closure in Figure MASS-9 

(DOE 2014, Appendix MASS-2014; see the fourth page in this response). The DRZ_PCS region 

has an orange color in Figure MASS-9. The combined volume above and below the ROM PCS 

between the south rest-of-repository and the north rest-of-repository is: 

 VDRZ_PCS = (0.69+0.69+2.62+4.53+4.53)(15.48+15.48)(40+40) = 31,850 m3. (4) 

The porosity change for 0 = 0.01 is 0.018 (see Table 1) and the corresponding increase in free 

volume is (31,850 m3

)(0.018) = 570 m3. This increase is not significant for the overall volumes of 

brine and gas in the repository, and will not be important for repository performance. For 

example, the total excavated volume of the repository is 436,000 m3

 (SNL 1992, Section 3.1.1) 

and the approximate volume of a single panel is (0.1)(436,000 m3

) = 43,600 m3, which is much 

greater than the pore volume change in the DRZ_PCS. 

Table 1. Porosity changes predicted by Equation (3) during the T2 and T3 time periods 

0 0.0548 0.03 0.01 0.0038 

0

 1.207 1.410 2.801 15.05 

    0 0.011 0.012 0.018 0.053 

For the minimum initial porosity of 0.0038, the maximum change in porosity is 0.053 and the 

corresponding volume increase is (31,850 m3

)(0.053) = 1,700 m3. Again, this increase is not 

significant for the overall volumes of brine and gas in the repository, and will not be important for 

repository performance.

References: 

Camphouse, R.C., M. Gross, C.G. Herrick, D.C. Kicker, and B. Thompson. 2012a. Recommendations 

and Justifications of Parameter Values for the Run-of-Mine Salt Panel Closure System Design Modeled 

in the PCS-2012 PA. Memorandum to WIPP Records dated May 3, 2012. ERMS 557396. Sandia 

National Laboratories, Carlsbad, NM. 

Camphouse, R.C. 2012b. An overview of the BRAGFLO two-phase flow parameters used to model the 

run-of-mine salt panel closures implemented in the PCS-2012 PA. Memorandum to WIPP Records dated 

June 7, 2012. ERMS 557653. Sandia National Laboratories, Carlsbad, NM. 
3rd Response Submittal to the EPA Enclosure 1 

18

Christian-Frear, T.L. 1996. Salado Parameter Principal Investigator Document Package for: DRZ 

Porosity from Room Q Analysis. Memorandum to SWCF-A Records Center Dated February 13, 1996. 

ERMS 419199. Sandia National Laboratories, Albuquerque, NM. 

Economy, K. 2014. EPA’s Confirmatory PA Analysis of DOE’s Proposed Run-of-Mine Salt Panel 

Closure System for the WIPP. Paper number 14058. Waste Management 2014 Conference, March 2-6, 

2014, Phoenix, AZ.*

Freeze, R.A. and J.A. Cherry. 1979. Groundwater. Prentice Hall, Englewood Cliffs, NJ.*

Herrick, C.G. 2012. JAS3D Calculations Performed in Support of the PCS-2012 PA Parameters 

Selections. April 30, 2012. ERMS 557354. Sandia National Laboratories, Carlsbad, NM. 

Hurtado, L.D., M.K. Knowles, V.A. Kelly, T.L. Jones, J.B. Ogintz, and T.W. Pfeifle. 1997. WIPP Shaft 

Seal System Parameters Recommended to Support Compliance Calculations. SAND97-1287. Sandia 

National Laboratories, Albuquerque, NM. 

Ismail, A.E. 2007. Revised porosity estimates for the DRZ. Memorandum to File Dated April 10, 2007. 

ERMS 545755. Sandia National Laboratories, Carlsbad, NM. 

Kirchner, T. 2013. Sensitivity of the CRA-2014 Performance Assessment Releases to Parameters. 

ERMS 560043. Sandia National Laboratories Carlsbad, NM. 

Parker, J.C., R.J, Lenhard, and T. Kuppusamy. 1987. A Parametric Model for Constitutive Properties 

Governing Multiphase Flow in Porous Media. Water Resources Research. Vol. 23, no. 4, 618-624.*2

Sandia National Laboratories (SNL). 1992. Preliminary Performance Assessment for the Waste Isolation 

Pilot Plant. SAND92-700/3. Vol. 3: Model Parameters. December 1992. Sandia National Laboratories, 

Albuquerque, NM. 

U.S. Department of Energy (DOE). 2004. Title 40 CFR Part 191 Compliance Recertification 

Application for the Waste Isolation Pilot Plant (March). DOE/WIPP 2004-3231, 10 vols. Carlsbad Field 

Office, Carlsbad, NM. 

U.S. Department of Energy (DOE). 2009. Title 40 CFR Part 191 Compliance Recertification 

Application for the Waste Isolation Pilot Plant (March). DOE/WIPP-09-3424. Carlsbad Field Office, 

Carlsbad, NM. 

U.S. Department of Energy (DOE). 2014. Title 40 CFR Part 191 Subparts B and C Compliance 

Recertification Application-2014 for the Waste Isolation Pilot Plant (March). DOE/WIPP-14-3503. 

Carlsbad Field Office, Carlsbad, NM. 

Vaughn, P. 1996a. Revision to DRZ and TZ properties to be used in the BRAGFLO CCA calculations. 

Memorandum to Margaret Chu Dated January 24, 1996. WPO 32288. Sandia National Laboratories, 

Albuquerque, NM. 

Vaughn, P. 1996b. KPT Modeling Feature. Memorandum to Martin Tierney dated February 19, 1996. 

ERMS 235271. Sandia National Laboratories, Carlsbad, NM. 

                                                           

*

Copyrighted reference not provided in Enclosure 2. 

2

Parker et al. (1987) was previously submitted to EPA as a reference for Appendix C, Fluid Flow Analysis, which is 

part of Appendix SEAL of the CCA. 
3rd Response Submittal to the EPA Enclosure 1 

19

EPA Comment 

1-23-6 Probability of Encountering a Castile Brine Pocket. Please address the following comments: 

1. TDEM results are site specific and indicate the presence of potentially large volumes of brine 

beneath some waste panels. Explain why TDEM data is not used in DOE’s proposed approach 

for estimating PBRINE. 

2. DOE’s approach ignored the presence of high electrical conductivity zones identified beneath 

four of the ten WIPP waste panels. Please explain how this omission affected the comparison of 

the TDEM approach with DOE’s newly derived drilling data approach. 

3. ERMS 558724 asserts that brine encounters of sufficient size to impact the repository would be 

noticed and logged by a driller. The approach does not acknowledge the potential of 

encountering a low yield and high volume brine pocket which would not be noticed by the driller 

in calculating PBRINE. Please address the basis for not considering the low yield, high volume 

brine pockets. 

4. DOE reported the same count of 34 brine intrusions out of 678 Castile wells in 2008. It is 

unclear whether 2008 was the last time a brine intrusion was observed at the time of collecting 

data for the CRA-2014 or if 2008 was the cut-off date for recoding a brine intrusion. Please 

clarify. 

5. The circular regions in Figure 5 of ERMS 558724 were selected to include a known brine pocket 

encounter. Please provide information as to whether this radius would bias the results and the 

sensitivity of the results to the radius size. 

6. Provide information as to how the well depths, for each well that did and did not encounter a 

brine pocket, were incorporated into the drilling data analysis. 

7. The ratios in Table 2 of ERMS 558724 include double-counting of many wells. Please provide 

information as to how this affected the results. 

8. ERMS 558724 states that pressurized brine is associated with near-vertical fractures. However, 

WIPP-12 yielded large volumes of brine that is assumed to have been stored and transmitted 

through the extensive and primarily interconnected horizontal to sub-horizontal fractures. Please 

provide an explanation as to how the near-vertical fracture model adopted by DOE’s modified 

PBRINE parameter is consistent with evidence that WIPP-12 releases are attributed to horizontal 

and sub-horizontal fractures. 

DOE Response 

1. The goal in estimating parameters for use in the WIPP PA is, to the extent feasible, to provide the best 

estimate of the parameter based on empirical evidence and to represent the uncertainty on those 

estimates by assigning a distribution to the parameter. The form and magnitude of dispersion 

represented by the distribution ideally could be determined from the empirical data, but in practice, 

additional sources of uncertainty must be considered as, for example, when the empirical data are few 

or not entirely representative of the site in question. In some cases uncertainties on parameters can be 

ignored, as when the parameter has little influence on the result or when the uncertainty is negligible. 

In some cases parameters must be estimated by expert elicitation, drawing on the experience of 

knowledgeable experts to subjectively define a distribution for a parameter. Since the goal in risk 

assessment generally is to minimize the chance of a false-negative conclusion, parameters deemed 

low-influence or well-known can be assigned conservative (risk maximizing) values with no 

uncertainty. In a probabilistic risk assessment, like that employed in WIPP PA, the use of 

conservative assumption for parameters must be weighed carefully since excessive conservatism will 

transform the results from the best estimates with uncertainties that capture the possible range of 

outcomes, to conservative estimates with uncertainties that likely range into regions of highly 

improbable or impossible outcomes. In addition, implausible predictions from a probabilistic model 

can cast doubt on its overall credibility. 
3rd Response Submittal to the EPA Enclosure 1 

20

This update of the probability of encountering a pressurized brine pocket (PBRINE) is consistent with 

the requirement in 40 CFR 194.15(a)(2), which states that recertification applications include “...all 

additional monitoring data, analysis, and results.” The monitoring data collected by the Delaware 

Basin Drilling Surveillance Program (DBDSP) show a dramatic increase in drilling activity over the 

last 10 years, with no additional occurrences of pressurized brine within the monitoring area. The 

DOE believes that these new data should be recognized and incorporated as appropriate into the 

CRA-2014, and that the distribution derived from these data is more credible than the distribution 

previously derived using time-domain electromagnetic (TDEM) data (Peake 1998). It will be shown 

below that: 

 the distribution developed from the time-domain electromagnetic data is based on questionable 

assumptions, 

 the assignment of a uniform distribution to introduce conservatism is questionable on theoretical 

grounds, 

 the uniform distribution is a poor representation of the results from a Monte Carlo-based analysis 

conducted by the EPA, and 

 the subjectively assigned uniform distribution could be less conservative than a more realistic 

distribution based on statistical theory. 

Thus the previous uniform distribution of PBRINE mandated by EPA both impacts the credibility of 

the results and impairs their interpretation within the probabilistic framework of the compliance 

assessment. The distribution used in the CRA-2014 is based on a direct measurement of the frequency 

of brine encounters, is consistent with the probabilistic framework of compliance assessment, and 

does not require the use of a conceptual model having many uncertainties to derive the probability of 

encountering brine from the measurements. Furthermore, a subset of the well data from the region 

was used to estimate PBRINE. These data came from a reference region near WIPP that was selected 

because it had a higher than average rate of brine encounters. Thus, the nominal estimate of PBRINE 

used in the CRA-2014 is at least twice as large as the regional rate and more than three times the rate 

encountered in wells around the WIPP site. In addition, the shape of the CRA-2014 distribution is 

derived from statistical theory and reduces the weight associated with low-probability events. Based 

on these features, the DOE considers the CRA-2014 distribution to be the more defensible alternative. 

This conclusion is derived from review of: 

 The data on pressurized brine around the WIPP site 

 The on-site drilling data 

 The TDEM data and their interpretation 

 The theoretical expectation for the form of the distribution 

 Assumptions made in the stochastic simulation of depths 

 Using drilling data to estimate PBRINE 
3rd Response Submittal to the EPA Enclosure 1 

21

Pressurized brine in the region of the WIPP 

The occurrence of pressurized brine in the Castile formation was known at the time that the DOE was 

evaluating sites for the WIPP. The potential for encountering pressurized brine became an issue 

during the site suitability investigation process when a brine release occurred from the WIPP-12 test 

well (Popielak et al. 1983). Of three wells drilled within the WIPP boundary, only WIPP-12 

encountered pressurized brine. The parameter PBRINE is potentially influential because it is the 

influx of brine into the repository that can cause gas pressures to rise and subsequently give rise to 

releases of contaminated brine to the surface. Thus, it is a parameter that one would want to estimate 

as accurately as possible with an appropriate level of uncertainty. However, the actual sensitivity of 

direct brine releases (DBR) to PBRINE is quite low (Fig. 1), as documented in Kirchner (2013). Here 

DBR was only weakly correlated with PBRINE (contributing about 2% to the variability) in one of 

three replicates. This is undoubtedly because it takes only one drilling event where pressurized brine 

is encountered to flood the repository, so additional intrusions into pressurized brine have little or no 

impact. We observed an average of 7.44 drilling intrusions per future in the CRA-2014 simulations. 

This value is stored in an output file from the CCDFGF code, but for verification the expected value 

can be computed as 

 7.43 = 0.00673 intrusions-km–2-yr–1 ൈ 0.1115 km2 ൈ 9900 yr 

where the area of 0.1115 km2

 is the footprint of the repository and 9900 is the number of years 

simulated after the period of institutional controls. Thus, low values of PBRINE can result in no brine 

pockets being penetrated in a future. For example, if PBRINE is 0.01, then the probability of seeing at 

least 1 brine encounter in 7 trials is only about 0.07. If PBRINE is 0.6, that probability is nearly 1 

(0.998). This nonlinear response means that the impact of the change in the distribution cannot be 

judged merely by comparing the ranges of the old and new distribution. It also means that the shape 

of the distribution, particularly the weight in the lower tail, is important. 

Herein we explain why we are more confident in the distribution of PBRINE developed from the 

drilling data than we are in the distribution derived from the TDEM data. Our lack of confidence in 

the TDEM-derived distribution arises from: 

 The lack of any data that could be used to correlate TDEM data with the probability of 

encountering brine 

 The assumption that the proportion of the area of the repository underlain by regions of high 

conductivity is a good estimate of the probability of encountering brine 

 The assumption that the error bar on TDEM depth of ±75 m was one sigma 

 The discounting of expert opinion that brine pockets would be contained within the anhydrite 

 The use of a uniform distribution that ignores both the results obtained from stochastic simulation 

of uncertainties in the depth estimates and the expected distribution for a Bernoulli process 

Each of these observations is explained in the following text. 
3rd Response Submittal to the EPA Enclosure 1 

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Figure 2. Scatter plot of rank direct brine release vs. rank PBRINE for CRA2014-BL and 

CRA2014-TP

The on-site drilling data, TDEM data and flaws in their interpretation 

Given the limitation that direct measurement of the probability of encountering brine in a drilling 

event over the WIPP repository cannot be made, one might consider alternative methods for 

estimating this probability. An ideal experiment would be to find a non-intrusive measurement that 

could be used to predict the rate of pressurized brine encounters, make those measurements over the 

repository, then calibrate the non-intrusive measurements to the probability of encountering 

pressurized brine on a similar off-site area where both the non-intrusive measurements and drilling 

experiments could be conducted. However, this was not an experiment that was conducted. What is 

available are data from non-intrusive TDEM measurements over the repository, data from three wells 

drilled on the WIPP site and well logs from commercial drilling operations in the area surrounding 

the WIPP site. The TDEM measurements can be used to provide a map of regions of high 

conductivity, which are likely associated with the presence of water. The TDEM data can be 

interpreted to estimate the depth of the high-conductivity regions. Thus, the TDEM data were 

valuable in alerting DOE to the possibility of there being pressurized brine pockets beneath the WIPP 

repository. The TDEM data are also valuable in that they detected no areas of high conductivity at 

depths of less than 1000 m (The Earth Technology Corporation 1988). However, TDEM results 

provide a two-dimensional map of areas of high conductivity and cannot be used to estimate the 

volume of brine, particularly at the low levels of resolution that result from the requirement of 

obtaining measurements at the depth of the Castile. Thus, the portion of the question that asserts that 

“the TDEM results ... indicate the presence of potentially large volumes of brine” is not accurate. 

In order to make measurements to the depth of the Castile, the TDEM loop had to be a square with 

the length of the side about equal to the depth of interest. The TDEM loops in this case were 500 m 

GLOBAL:PBRINE

0.0 0.2 0.4 0.6

Direct Brine Release (EPA Units)

1e-4

1e-3

1e-2

1e-1 CRA2014-BL

CRA2014-TP
3rd Response Submittal to the EPA Enclosure 1 

23

by 500 m on a side (The Earth Technologies Corporation 1988). This large size also reduced noise in 

early time channels as compared to smaller sized loops (The Earth Technologies Corporation 1988). 

Thus, these are necessarily low-resolution data and they cannot provide a detailed map of brine 

pockets, which are expected to have cross-sectional areas considerably smaller than 500 m by 500 m, 

nor can TDEM data distinguish pressurized from non-pressurized fluids. Expert opinion is that water 

contained wholly within the anhydrite layers of the Castile formation is likely to be pressurized brine, 

whereas water within the Bell Canyon formation, which permits lateral flow, is unlikely to be 

pressurized (Peake 1998; Sandia 1992 page 5-4; Powers et al. 1996; Powers et al. 1978). The 

conceptual model for the brine pockets is that they were formed within near-vertical cracks in the 

anhydrite of the Castile formation during periods of deformation (Popielak et al. 1983). Borns (1983) 

confirmed the near-vertical orientation of brine-producing fractures through study of core from the 

WIPP-12 borehole. Popielak et al. (1983) found no evidence of hydraulic or chemical connection 

between reservoirs, but did conclude that low permeability microfractures around the large fractures 

contained the majority of the brine. Evidence for the lack of connectivity between reservoirs 

(Popielak et al. 1983) includes: 

 Hydraulic heads that are substantially different between reservoirs 

 The containment of gas by the reservoirs 

 Different brine and gas chemistries among the reservoirs 

 Geographic separation and heterogeneity in the spatial distribution of reservoirs 

 Bulk chemical equilibria between brine, gas and reservoir rock 

This conceptual model provides the foundation for making assumptions to translate the TDEMgenerated map of conductivity into the probability of encountering pressurized brine. In particular, it 

suggests that it is wrong to assume that any well drilled in an area identified by TDEM as being an 

area of high conductivity will necessarily encounter pressurized brine. However, it is probably fair to 

say that a well drilled in an area where TDEM showed no areas of high conductivity within the 

Castile is highly unlikely to encounter a brine reservoir. 

There are two sets of site-specific data: TDEM data showing areas of high conductivity and data from 

three drilling events. The distribution of PBRINE used in the previous CRAs was derived from the 

TDEM data with no consideration of the rates of encounters of pressurized brine pockets observed 

either on the WIPP site or in the area surrounding WIPP. The translation from TDEM measurements 

to a probability of encountering brine relied on stochastic modelling of the uncertainties in the TDEM 

data and formation depths, and some conservative assumptions about the interpretation of the TDEM 

data (Peake 1998). An important consideration in this stochastic modeling was the assumption about 

the location of pressurized brine in the Castile. Two possibilities were considered: that the pressurized 

brine was contained within the anhydrite, so the base of Anhydrite III was the lower bound of depth, 

or that the pressurized brine could extend to the base of the Castile. Both limits were used in the 

analysis and each produced a distribution. These distributions were widely separated from each other, 

having ranges of about 0.02 to 0.06 (base of Anhydrite III) and 0.35-0.58 (base of Castile) based on 

Fig. 5-5 in Peake (1998). A bimodal composite distribution was suggested in Peake (1998) that 

combined the two distributions by assuming each was equally likely (Peake 1998, Fig. 5-5). The 

stochastic modeling also considered the limiting cases of 1) there being no spatial correlations 

between areas associated with high TDEM conductivity measurements and 2) there being very high 

correlation between such areas. These two cases were labeled the random model and the block model, 

where the block model derived its name from the spatial aggregation of areas surrounding each of 36 
3rd Response Submittal to the EPA Enclosure 1 

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measurement points with the aggregate being assigned the measurement value, thus yielding 36 

blocks of elevations. The block model was considered to be more conservative than the random 

model. The block model was chosen to represent the data even though the TDEM measurements 

showed no indication of spatial correlation. 

Peake (1998) notes that “... the TDEM results do not account for the possibility of obliquely oriented 

or oblong-shaped brine pockets...”. Thus, the areas mapped out using the TDEM data do not 

represent areas of high probability of encountering a pressurized brine pocket but rather areas of high 

conductivity in the Castile formation defined at a very low level of spatial resolution. There are no 

data available to use to translate from drilling in an area of high conductivity to the probability of 

encountering pressurized brine, so this important correlation was treated as being perfect, i.e., having 

a coefficient of 1, in spite of the core data that suggest brine resides in nearly vertical cracks. In 1997, 

the EPA mandated that the parameter PBRINE be assigned a uniform distribution over the range 0.01 

to 0.60. The uniform distribution was selected under the assumption that there were no data on which 

to base an expected or modal value and the end points were set subjectively, with the upper end 

primarily based on an interpretation of the TDEM data. This uniform distribution was based on the 

stochastic modeling of the depth of the TDEM conductive layers but ignored the suggestion that a 

bimodal distribution be used. As a result, the uniform distribution assigns non-zero probability to 

values of PBRINE between 0.08 and 0.35 in spite of the lack of any sampled data in this range from 

the stochastic analysis. Furthermore, the equal weighting given to each distribution does not appear to 

be justified by the opinions of the experts (Popielak et al. 1983) that pressurized brine would be found 

primarily, and probably exclusively, in the anhydrite layers. 

The other site-specific data are the drilling data from three wells, one of which encountered 

pressurized brine. EPA has previously argued that the WIPP site’s geology with respect to the 

abundance of brine pockets could be different from that of neighboring areas, based in part on this 

one encounter with pressurized brine. These data are too sparse to derive a correlation between 

TDEM results and the probability of encountering brine. However, encountering pressurized brine 

reservoirs can be assumed to be a Bernoulli process because for each drilling event the probability of 

encountering pressurized brine can be assumed to be independent of previous drilling events. A 90% 

confidence interval on the observed rate of encountering pressurized brine on the WIPP site, 0.33, is 

approximately 0.02 to 0.86 (Hahn and Meeker 1991). This interval represents the range of PBRINE 

that, with 90% confidence, could give rise to exactly 1 out of 3 brine encounters. In Kirchner et al. 

(2012) we showed that the range of PBRINE that could give rise to at least one brine encounter in 

three trials to be 0.02 to 0.63, thus showing that the observed rate of encounters within the WIPP 

boundary was not inconsistent with the average rate of encounters in the vicinity of WIPP. 

Conservatism of the uniform distribution 

The TDEM-based interval has a lower maximum than the observation-based estimate based on the 

three on-site wells, but the uniform distribution has a higher frequency of the lowest values as 

compared to the distribution expected for a Bernoulli process based on data from only three wells 

(Fig. 2). In other words, the distribution derived from the TDEM data and a set of assumptions could 

well be less conservative than a distribution based on the site-specific drilling data in spite of the 

uniform distribution’s smaller range because of the greater influence of low values than high values. 

However, basing an estimate of PBRINE on data from only three wells obviously introduces both a 

coarseness and a high degree of uncertainty on the value; the only possible estimates of PBRINE that 

can be obtained from three trials are 0, 1/3, 2/3 and 1. Furthermore, a rate of 33% far exceeds the rate 

of encounters of pressurized brine in the area surrounding WIPP. Thus, these data were also judged 

to be inadequate for providing a creditable estimate of PBRINE. 
3rd Response Submittal to the EPA Enclosure 1 

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Flaws in the stochastic simulation of uncertainty in depth measurements 

A study of the TDEM analysis report (Peake 1998) also raised questions about the methodology used 

to map areas of high conductivity under the various panels. The method employed a stochastic 

simulation model to try to incorporate the measurement uncertainty, ± 75 m, into the assessment. This 

uncertainty was sampled and applied to the nominal depth measurement values, and then the sampled 

depths were compared to the extent of the Castile to assess whether they could be included or 

excluded as indicators of potential Castile brine pockets. One major concern was the interpretation of 

the measurement uncertainty as representing one sigma. Normally, a measurement uncertainty 

expressed using ± is assumed to represent an absolute limit or two standard deviations (sigma) unless 

specifically noted to be an estimate of dispersion with a specific “coverage factor” (the multiplier on 

sigma) (Taylor and Kuyatt 1994; ANSI 1997). The Earth Technology Corporation (1988) stated that 

“...the accuracy of determining depth to brine in this survey was , ± 75 m,” thus lending credence to 

the interpretation that ± 75 m represented an absolute interval and not a measure of variability or 

dispersion. Furthermore, -75 m and +75 m are explicitly labelled the “minimum depth” and the 

“maximum depth” on the TDEM depth estimates in Borns (1996). If sigma was reduced, then the area 

of regions of high conductivity within the Castile would probably be reduced as well. Presumably, the 

assignment of areas possibly containing brine pockets to panels where the nominal value did not 

indicate brine was related to this interpretation of uncertainty. However, there were insufficient 

details in the report to reproduce this analysis with the interpretation of the measurement error as 

being two-sigma. 

Figure 3. Previous uniform distribution based on a subjective analysis of the TDEM data 

and the distribution of uncertainty based on encountering pressurized brine once in three 

trials 

PBRINE

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Probability

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Observation-based distribution

Subjectively assigned distribution
3rd Response Submittal to the EPA Enclosure 1 

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Estimating PBRINE based on the drilling data 

Given the subsequent increase in the number of commercial wells in the area surrounding WIPP and 

based on the number of encounters of pressurized brine recorded in the well logs for those wells, 

DOE’s position is that the uniform distribution assigned to PBRINE and used prior to the CRA-2014 

fails to properly characterize the probability of encountering brine. On one hand, a rate of 60% of 

wells encountering brine far exceeds the observed rate of brine encounters in the region, even within 

an area where the frequency of encountering brine is high compared to the average rate across the 

region surrounding WIPP (Kirchner et al. 2012). On the other hand, a nominal probability of 0.01 for 

encounters seems low given the drilling data now available. Furthermore, the drilling data provide 

information that can be used to define a “most likely” value to use as the mode of a unimodal 

distribution to replace the uniform distribution, hence reducing the weight in the tails of the 

distribution. 

One advantage of using the drilling data over the TDEM data is that the drilling data do not require 

any consideration of the distribution and geometry of pressurized brine pockets. There are only two 

assumptions that need to be made about the data: 1) the drilling logs identify encounters of 

pressurized brine pockets having characteristics like those modeled in BRAGFLO, and 2) the area 

from which the data are tabulated has an equivalent or higher density of pressurized brine pockets as 

compared to the area under the repository. Having a higher density of brine pockets would lead to a 

conservative estimate of PBRINE. It is our opinion that the commercial drilling data are consistent 

with both of these assumptions. Thus, the drilling data from commercial wells in the vicinity of 

WIPP were judged to give direct measurements for the probability of encountering brine, thus 

eliminating many of the uncertainties and unknowns associated with deriving PBRINE from the 

TDEM data. Arguments in favor of these assumptions were addressed in Kirchner et al. (2012), but 

will be reiterated and expanded upon herein. 

There was an early concern as to whether the frequency of brine pocket intrusions in the region 

around the WIPP site was a suitable estimate for the WIPP site in particular. Powers et al. (1996) 

addressed that concern by doing an extensive geostatistical analysis on the drilling data available at 

that time. They looked for spatial autocorrelations in the data and correlations with factors such as the 

thickness of the formations. Powers et al. (1996) concluded that the probability of encountering 

pressurized brine under the waste panels was 0.08, with no estimate of uncertainty on that value. In 

Kirchner et al. (2012) we selected an area that would maximize the observed rate of brine encounters 

to ameliorate concern about using non-site-specific data. Furthermore, we constructed a confidence 

interval for the estimate of the true probability based on the observed frequency drawing upon 

statistical theory for Bernoulli processes. What we did not do explicitly in that report was to compare 

the rate from the reference area to the rate observed on and in a band around the WIPP site. That 

comparison follows. 

The number of wells on which to base PBRINE can be expanded from the three on the site by using 

wells near the WIPP boundary. For example, using the most recent data on wells within a square 

having borders about 2.5 miles from the WIPP boundary extends the number of wells to 517 (Fig. 3). 

Of these, 18 encountered pressurized brine, giving a value of PBRINE of 0.035, or 3.5%. This is 

lower than the ratio for the region currently used, which is about 5%. However, restrictions on drilling 

imposed by the state to protect potash resources result in some areas near the WIPP showing few or 

no wells. For that reason we chose to reduce the chance of estimating a rate of brine encounters that 

is lower than that which might be encountered on the WIPP site by analyzing a sub-region to the 

northeast of the WIPP (Kirchner et al. 2012). This area showed a rate of brine encounters of 12.7% 

and the distribution employed in CRA-2014 was derived using that rate and the theory of Bernoulli 

processes (Kirchner et al. 2012). Thus, the nominal estimate of PBRINE used in the CRA-2014 is at 
3rd Response Submittal to the EPA Enclosure 1 

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least twice as large as the regional rate and more than three times the rate encountered in wells around 

the WIPP site. We believe that this conservatism, in addition to the uncertainty associated with that 

value, should encompass any tendency to underreport brine encounters. 

Figure 4. Wells in close vicinity to WIPP 
3rd Response Submittal to the EPA Enclosure 1 

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To summarize: 

 The TDEM data only provide a low-resolution, 2-dimensional map of the depth to regions of high 

conductivity 

 The site-specific well data are too sparse to develop a correlation between TDEM results and the 

probability of encountering brine 

 There are no TDEM data in the areas surrounding WIPP to use to derive a correlation between 

encountering brine and being in a TDEM-identified zone of high conductivity in the Castile 

 The assumption that the proportion of the area of the repository underlain by regions of high 

conductivity ignores the near vertical orientation of the brine reservoirs, and thus overestimates 

the correlation between encountering brine and being in a TDEM-identified zone of high 

conductivity in the Castile 

 The stochastic analysis, which expanded the proportion of the area of the repository underlain by 

regions of high conductivity, assumed that the error bar on TDEM depth of ±75 m was one 

sigma, whereas it should have been assumed to be two sigma 

 The composite bimodal distribution derived from the analysis assumed equal weighting for using 

the base of the anhydrite and the base of the Castile, in spite of the expert opinion that brine 

pockets would be contained within the anhydrite 

 The uniform distribution derived from the analysis assigned probabilities to values of PBRINE 

not represented in the results of the stochastic sampling, which yielded a bimodal distribution 

 The uniform distribution has more mass in the left tail than would a modal distribution, like a 

normal distribution, and hence is less conservative than such a distribution would be. 

 The drilling data, in contrast to the TDEM data, provide a direct measurement of the rate of 

encountering brine that does not depend on a conceptual model for brine reservoirs 

 The drilling data, although not site-specific, were selected from an area showing 2 to 3 times the 

rate of encounters of brine as compared to the area immediately surrounding the WIPP site, thus 

providing conservatism 

 The distribution of uncertainty on PBRINE estimated from the drilling data can be derived from 

the theory of Bernoulli processes, and thus is totally objective 

EPA has previously argued that the WIPP site’s geology with respect to the abundance of brine 

pockets could be different from that of neighboring areas, based in part on having an encounter with 

pressurized brine in one of three wells drilled on the site. We have shown that this observed rate has 

an uncertainty, based on statistical theory, which encompasses the much lower rate of brine 

encounters in the region. In the absence of evidence to the contrary, we have no reason to believe that 

the probability of encountering brine on the WIPP site would be greater than that observed in 

neighboring regions and expect it to be considerably lower than that observed in the reference area 

chosen for our derivation of PBRINE. Given this evaluation, we concluded that 1) the TDEM data 

method for estimating PBRINE was less credible than the method involving use of the commercial 

drilling data, and 2) we could see no way that the TDEM data could contribute to improving the 

estimate of PBRINE based on the drilling data. 
3rd Response Submittal to the EPA Enclosure 1 

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2. This comment appears to be about Kirchner et al. (2012), where we attempted to estimate a 

conditional probability of encountering brine given that a well was in an area identified by TDEM as 

having a zone of high conductivity within the Castile. To be clear, that part of the analysis has 

nothing to do with our approach in deriving a new distribution for PBRINE. The reinterpretation of 

the TDEM data was done simply to make the distributions directly comparable, since in our opinion 

the calculation of the previous estimate of PBRINE failed to incorporate a reasonable assumption for 

the conditional probability, and hence was the probability of being in an area of high conductivity 

rather than the probability of encountering brine. Omitting four of the ten panels in our assessment 

was an error, based on a misinterpretation of the text, and including them and their estimates of 

TDEM areas would expand the TDEM-derived distribution to the right and also affect the shape of 

the distribution. However, the Kirchner et al. (2012) analysis also ignored the potential error in 

interpreting measurement uncertainty (the interpretation of ±75 m) since there was no way given the 

available information to reproduce the stochastic analysis with which the panel-specific areas were 

derived. Because the position of the maximum value of the distribution is expected to have little 

influence on releases, as discussed under comment 1, including the area estimates for the four panels 

when properly deriving the TDEM-based distribution would have little impact of a practical nature 

and would not improve the credibility of the TDEM-derived distribution. 

3. A low-yield, high-volume brine pocket originating from the Castile is not consistent with our 

understanding of the characteristics of this formation. Ductile rock units behave plastically and exert 

pressures upon any resident liquids at or approaching lithostatic for that unit (Beauheim and Roberts 

2002). Therefore low-yield (read: low-pressure) brine flows from this unit are not observed or 

reported from drillers in the area. That is, in the rare instances when brine is encountered from the 

Castile, it is always found to be at high pressure. In our opinion the conservatisms in our mean rate (a 

factor of 2-3 larger than the observed rate around the WIPP site) and the uncertainty on that rate 

should encompass any likely truncation of the detection rate of brine pockets. 

4. Although there was a significant increase in the number of wells drilled in the region since 2008, 

none of the new wells encountered brine. The last brine occurrence recorded was in 2004; therefore, 

the count remains at 34. 

5. To be clear, the neighborhood analysis of drilling events with and without brine encounters was not 

used in the development of the distribution of PBRINE in the CRA-2014. The purpose of that 

analysis was to try to derive a conditional probability for being in an area having brine pockets and 

actually encountering brine. The radius of 500 m was shown to maximize the average ratio between 

wells with brine encounters to wells without encounters. It was stated in Kirchner et al. (2012) 

“Although the 1000 m diameter of the circles is somewhat arbitrary, examination of Fig. 5 shows that 

increasing the diameter will most likely add more wells without brine intrusions than wells with 

intrusions, and thus drive the average ratio lower. Circles of a smaller diameter would result in many 

more cases of there being only a single well contained and thus be inadequate for estimating the ratio. 

Finally, smaller circles would not reflect minimum well spacing requirements for drilling in the 

Delaware Basin, and would exclude effectively all neighboring wells.” To specifically answer this 

question, the selection of the radius would have a profound impact on the analysis of the conditional 

probability for the TDEM data, but we are not advocating using the neighborhood analysis to rectify 

problems with the TDEM data. In our opinion combining the TDEM data with this crude estimate of 

the conditional probability linking TDEM areas to the probability of encountering brine would not 

improve the credibility of the resulting distribution given some of the other issues discussed in 

comment 1. 

6. The DBDSP researches the well files of new wells drilled in the New Mexico portion of the Delaware 

Basin each year looking for instances of encounters with pressurized brine. The program also sends 
3rd Response Submittal to the EPA Enclosure 1 

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out an annual survey to operators of new wells asking if they encountered pressurized brine during 

the drilling process. Because stratigraphy changes over the survey area, the depth of brine intercept is 

not as important as the formation in which brine is encountered. Therefore, the specific depths of 

brine intercepts are not incorporated into the analysis. It is also recognized by industry experience 

that pressurized brine flows rarely originate from units deeper than the Castile in the WIPP vicinity. 

Consistent with this, all brine flows reported by area drillers originate from the Castile Formation. 

Therefore, only Castile brine occurrences are counted by the DBDSP, and only these were used in the 

data analysis. The wells that did not encounter pressurized brine were all deep boreholes that 

transcend the Castile to the deeper oil and gas producing zones. 

7. To be clear, the neighborhood analysis of drilling events with and without brine encounters was not 

used in the development of the distribution of PBRINE in the CRA-2014. Table 2 of Kirchner et al. 

(2012) provides data on the frequency of encountering brine in another intrusion within 500 m of a 

known brine intrusion. The assumption is that the drilling/encounter events are independent. The fact 

that a well having a brine intrusion is near two or more wells also having brine intrusions, hence 

being counted twice or more, has no impact on the estimated frequencies. Indeed, if there were strong 

spatial correlations in the locations of wells encountering brine, the existence of multiple neighbors 

having brine would be expected. The motive behind this neighborhood analysis was to try to convert 

the previous TDEM distribution into one that was a better estimate of PBRINE because it included a 

more realistic value for the correlation between PBRINE and TDEM-identified areas of high 

conductivity. However, given the flaws in the TDEM analysis addressed in comment 1 and the large 

uncertainty associated with the estimate of correlation, we do not see this approach as a viable way to 

improve the credibility of the estimate of PBRINE based on the TDEM data. 

8. With regard to the EPA’s assertion that WIPP-12 brine is assumed to have been transmitted via 

horizontal to sub-horizontal fractures, we respectfully request the source of this information, as it 

directly conflicts with information and analyses presented in Popeilak et al. (1983) and Borns (1983), 

which are the primary sources of Castile brine characterization. We are not aware of any 

characterization data that conflict or refute the current understanding that brine in the Castile is within 

near-vertical, high-angle fractures. 

However, the modified distribution for PBRINE is based on a direct observation of the rate of brine 

encounters and does not depend on a conceptual model of the orientation of brine pockets nor the 

presence of horizontal or sub-horizontal fractures. PBRINE is not related to the volume of brine 

encountered, it is just the probability of encountering brine by wells drilled through the Castile. 

Indeed, one advantage of using the drilling data is that these data are used to measure PBRINE based 

on whatever the system of fractures is, rather than a model of what those fractures are likely to be. 

We have not attempted to alter the conceptual model for pressurized brine within performance 

assessment, although many of the assumptions used in the pressurized brine conceptual model are 

quite conservative, and could benefit from more realism. However, changes of this nature 

(conceptual model changes) go beyond what we understand to be allowable through the 

recertification process. Therefore, we have attempted to stay within the content constraints for 

recertification applications, and have limited changes to an update of the parameter PBRINE. This 

parameter update is based on our obligation to comply with 40 CFR 194.15(a)(2), where it states that 

recertification applications include “...all additional monitoring data, analysis, and results.” The 

monitoring data collected by the DBDSP show a dramatic increase in drilling activity, but no 

additional occurrences of pressurized brine within the monitoring area over the last 10 years. The 

DOE believes that these new data should be recognized and incorporated as appropriate into the 

CRA-2014. 
3rd Response Submittal to the EPA Enclosure 1 

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References: 

American National Standards Institute (ANSI). 1997. American National Standard for Expressing 

Uncertainty – U.S. Guide to the Expression of Uncertainty in Measurement. ANSI/NCSL Z540-2-1997. 

American National Standards Institute, NY.*

Beauheim, R.L. and R.M. Roberts. (2002). Hydrology and hydraulic properties of a bedded evaporite 

formation. Journal of Hydrology 259 (2002): 66-88.*

Borns, D.J. 1983. Petrographic Study of Evaporite Deformation Near the Waste Isolation Pilot Plant 

(WIPP). SAND83-0166. June 1983. Sandia National Laboratories, Albuquerque, NM. 

Borns, D.J. 1996. Proportion of the waste panel area, WIPP site, that is underlain by brine reservoirs in 

the Castile Formation as Inferred from Transient Electromagnetic Method (TEM or TDEM) Surveys. 

WPO # 39121. Sandia National Laboratories, Albuquerque, NM. 

Hahn, G.J. and W.Q. Meeker. 1991. Statistical Intervals: A Guide for Practitioners. 392 pp. Wiley and 

Sons, NY.*

Kirchner, T.B., T. Zeitler and R. Kirkes. 2012. Evaluating the data in order to derive a value for 

GLOBAL:PBRINE. ERMS 558724. Sandia National Laboratories, Carlsbad, NM. 

Kirchner, T.B. 2013. Sensitivity of the CRA-2014 performance assessment releases to parameters. 

ERMS 560043. Sandia National Laboratories, Carlsbad, NM. 

Peake, T. 1998. Technical Report Review of TDEM Analysis of WIPP Brine Pockets. Prepared for U.S. 

Environmental Protection Agency, Office of Radiation and Indoor Air, 401 M. Street, S. W., Washington, 

DC. 

Popielak, R.S., Beauheim, R.L., Black, S.B., Coons, W.E., Ellingson, C.T., and R.L. Olsen. 1983. Brine 

Reservoirs in the Castile Formation, Waste Isolation Pilot Plant (WIPP), Project Southeastern New 

Mexico. TME-3153. Vols. 1 and 2. Westinghouse Electric Corporation, Carlsbad, NM. 

Powers, D.W., Lambert, S.J., Shaffer, S-E., Hill, L.R., Weart, W.D. (eds.). 1978. Geological 

Characterization Report Waste Isolation Pilot Plant (WIPP) Site. Southeastern New Mexico. SAND78-

1596, Volume II. Sandia National Laboratories, Albuquerque, NM. 

Powers, D., J.M. Sigda and R.M. Holt. 1996. Probability of intercepting a pressurized brine reservoir 

under the WIPP. ERMS 523414. Sandia National Laboratories Albuquerque, NM. 

Sandia. 1992. Preliminary performance assessment for the Waste Isolation Pilot Plant, December 1992. 

Volume 3: Model Parameters. SAND92-0700/3. Sandia National Laboratories, Albuquerque, NM. 

Taylor, B.N. and C.E. Kuyatt. 1994. Guidelines for Evaluating and Expressing the Uncertainty of NIST 

Measurement Results, NIST Technical Note 1297. U.S. Department of Commerce, National Institutes of 

Standards and Technology, Gaithersburg, MD.*

The Earth Technologies Corporation. 1988. Final Report for Time Domain Electromagnetic (TDEM) 

Surveys of the WIPP Site. SAND87-7144. Sandia National Laboratories, Albuquerque, NM. 

                                                           

*

Copyrighted reference not provided in Enclosure 2. 
3rd Response Submittal to the EPA Enclosure 1 

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EPA Comment 

1-23-8 Fluid Flow in Repository Operations and Experimental Areas. There have been numerous 

refinements of conceptual and numerical models of repository fluid flow since the 1994-95 time frame as 

well as changes to the panel closure system that may also change repository fluid flow. Please provide 

updated technical justifications for the following parameter values adopted for the experimental and 

operations areas: 

1. Setting the permeability of the operations and experimental rooms to a constant value of value 

10-11

 m

2

 throughout the modeled period. 

2. Setting the porosity of the operations and experimental rooms to a constant 18% throughout the 

modeled period. 

3. Setting the porosity and permeability of the DRZ adjacent to the operations and experimental 

room to the same sampled value as the DRZ surrounding a waste panel throughout the modeled 

period. 

DOE Response 

1. To remain consistent with previous, peer-reviewed conceptual models for the repository and for 

the Salado, performance assessment assigns constant porosity and permeability to the operations 

and experimental areas. Constant values for porosity and permeability in the experimental and 

operations areas are based on the concept that it is conservative in terms of releases if these areas 

have high permeability and low porosity. High permeability ensures that these regions do not 

impede brine and gas flow that might contribute to a borehole release and low porosity minimizes 

the storage capacity for gas in these regions, thus resulting in higher pressures in the waste-filled 

regions of the repository. The operational and experimental regions in the CRA-2014 PA are 

assigned a permeability of 10-11 m2

 and a porosity of 0.18 for the duration of the 10,000-year 

regulatory period, the same values established and used in the CCA, as well as the CRA-2004 and 

CRA-2009. 

Repository performance has been repeatedly shown to be insensitive to dynamic closure in the 

experimental and operations areas: 

1. During the development of the CCA, the DOE investigated whether it was important to 

include a dynamic model of creep closure in the experimental and operations areas. 

Calculations demonstrated that performance was quite insensitive to whether dynamic 

closure in these areas was included or not (Vaughn 1996). 

2. In response to a similar comment from the EPA (C-23-4), supplemental calculations to 

the CRA-2004 submittal demonstrated that the assignment of constant porosity and 

permeability in the experimental and operations areas remained a conservative 

assumption (Detwiler 2004). 

3. Following the CRA-2009 PABC, an impact assessment was undertaken to investigate the 

impact of additional mined volume in the WIPP experimental region on repository 

performance. An additional 60,335 m3

 were added to the CRA-2009 PABC BRAGFLO 

representation of the WIPP experimental region. It was found that increased volume in 

the experimental region had no impact on regulatory compliance curves obtained in the 

CRA-2009 PABC (Camphouse et al. 2011). 

4. The Salado flow analysis performed for the CRA-2014 PA compared results from the 

CRA-2009 PABC, the PCS-2012 PA, and Case CRA14-BL. In other words, it compared 
3rd Response Submittal to the EPA Enclosure 1 

33

Salado flow baseline results where the Option D PCS was implemented, results where the 

Option D PCS was replaced by the ROMPCS, and results where the ROMPCS was 

implemented with 60,335 m3 of additional excavated volume added to the experimental 

region in BRAGFLO. Waste region pressure and brine saturation results for intrusion 

scenarios were found to be similar in all three cases (Camphouse 2013). 

There have been no new conditions or changes that render the current representation inadequate 

or inconsistent with our current understanding of repository behavior. There is no reason at this 

time to modify the constant porosity and permeability values assigned to the operations and 

experimental areas. 

2. The response to item 2 is contained in the response to item 1.

3. Parameter values for the DRZ adjacent to waste panels, and the operations and experimental 

regions, are defined for two time periods. The first time period corresponds to the time associated 

with waste emplacement in a fresh panel, and endures for 5 years prior to repository closing (-5 to 

0 years). The second time period corresponds to the sealed repository time period from 0 to 

10,000 years. At the start of the first time period (the instant the excavation is made), the DRZ is 

assumed to be fully brine-saturated and in hydrostatic equilibrium with the rest of the Salado 

Formation. For the second time period, the DRZ is assumed to be a well-developed region 

characterized by vertical fractures. Because of gas generation and the consequently increasing 

pressure in waste panels, the DRZ above and below repository waste regions is assumed not to 

heal. The effect of gas pressure is to reduce back stress applied by the waste. Moreover, pressure 

is gradually transmitted from the repository waste panels to the northern operations and 

experimental regions. As a result, the DRZ above and below the operations and experimental 

regions is also assumed not to heal. As increasing pressure is the driving mechanism inhibiting 

healing of the DRZ, and pressure increase is seen in repository waste regions as well as the 

northern operations and experimental areas, the porosity and permeability of the DRZ adjacent to 

the operations and experimental regions are set to the same sampled values as the DRZ 

surrounding waste panels. This implementation remains consistent with previous, peer-reviewed 

conceptual models for the repository and for the DRZ. There is no reason to modify these values 

at this time. 

References: 

Camphouse, R.C. 2013. Analysis Package for Salado Flow Modeling Done in the 2014 Compliance 

Recertification Application Performance Assessment (CRA-2014 PA). ERMS 559980. Sandia National 

Laboratories, Carlsbad, NM. 

Camphouse, R.C., D.C. Kicker, T.B. Kirchner, J.J. Long, and J.J. Pasch. 2011. Impact Assessment of 

SDI Excavation on Long-Term WIPP Performance. ERMS 555824. Sandia National Laboratories, 

Carlsbad, NM. 

Camphouse, R.C., D.C. Kicker, T.B. Kirchner, J.J. Long, B. Malama, and T.R. Zeitler. 2012. Summary 

Report and Run Control for the 2012 WIPP Panel Closure System Performance Assessment. ERMS 

558365. Sandia National Laboratories, Carlsbad, NM. 

Camphouse, R.C., D.C. Kicker, S. Kim, T.B. Kirchner, J.J. Long, B. Malama, and T.R. Zeitler. 2013. 

Summary Report for the 2014 WIPP Compliance Recertification Application Performance Assessment. 

ERMS 560252. Sandia National Laboratories, Carlsbad, NM. 
3rd Response Submittal to the EPA Enclosure 1 

34

Detwiler, R.P. 2004. Partial Response to Environmental Protection Agency (EPA) May 20, 2004 Letter 

on CRA. ERMS 537372. Sandia National Laboratories, Carlsbad, NM. 

Vaughn, P. 1996. Phase I FEPS Composite FEP Records Screening Analysis. ERMS 418211. Sandia 

National Laboratories, Carlsbad, NM. 
3rd Response Submittal to the EPA Enclosure 1 

35

EPA Comment 

2-43-1 Changes in Passive Institutional Controls (PICs). Recent Nuclear Energy Agency and 

International Atomic Energy Agency reports describe changes and developments in international 

approaches to PICs. These are referenced in INIS-US-13-WM-13145 which states “The DOE/CBFO 

WIPP PIC’s program in place today meets the regulatory criteria, but complete feasibility of 

implementation is questionable, and may not be in conformance with the international guidance being 

developed.” Please explain this feasibility concern. Please also provide the complete INIS-US-WM13145 report (the Web link only provides an Abstract) and any other recent studies or reports that may 

impact PICs planning in the future. 

Reference: 

INIS-US-13-WM-13145, “The Revised WIPP Passive International Controls Program – A Conceptual 

Plan – 13145, Dated 2013-07-01, 

Web link: http://www.osti.gov/scitech/biblio/22225507

DOE Response 

The reference INIS-US-13-WM-13145 is a Waste Management Symposia 2013 paper that outlines some 

preliminary thoughts on developing a revised WIPP PICs program. The paper is provided with this 

response and discusses the feasibility concerns in EPA comment 2-43-1. 

DOE will discuss with EPA the current status of the development of international guidelines for PICs, 

which is outside of the context of the CRA-2014 completeness review. 
3rd Response Submittal to the EPA Enclosure 1 

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EPA Comment 

2-55-1 Incorrect Reference. IGP-2014, Section IGP-2.1 makes reference to 194.55(b)(1), should this be 

194.54(b)(1) “Existing boreholes...”?

DOE Response 

This is a typographical error in Appendix IGP-2014. The text will be corrected to read “Existing 

boreholes, as required by 40 CFR § 194.54(b)(1)...”. 

This typographical error has been added to Enclosure 4, CRA-2014 Errata Tracking. 
3rd Response Submittal to the EPA Enclosure 1 

37

EPA Comment 

2-C-7 MgO Hydration Rate Data File. Please provide a copy of the Microsoft Excel file “hydration 

kinetics Q & HY2 & HH djc 5-1-07.xls” used by Nowak and Clayton (2007) to calculate the MgO 

hydration rates. 

References: 

Nowak, E.J. and D. Clayton. 2007. Analysis of MgO Hydration Laboratory Results and Calculation of 

Extent of Hydration and Resulting Water Uptake versus Time under Postulated WIPP Conditions. Sandia 

National Laboratories ERMS 546769.

DOE Response 

The requested documentation is included in Enclosure 2. 
3rd Response Submittal to the EPA Enclosure 1 

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EPA Comment 

2-C-8 Iron and Lead Corrosion Rate Data. Please provide spreadsheets containing the iron and lead 

corrosion data listed in Appendix A, Tables A-1 and A-2 from Roselle (2013). 

References: 

Roselle, G.T. 2013. Determination of Corrosion Rates from Iron/Lead Corrosion Experiments to be Used 

for Gas Generation Calculations. Sandia National Laboratories ERMS 559077.

DOE Response 

The requested documentation is included in Enclosure 2.