### MEMORANDUM

TO: Lisa Biddle, U.S. EPA

FROM: Brent Ruminski, ERG

Sarah Yates, ERG

DATE: June 7 , 201 6

SUBJECT: Data Compilation Memorandum for the TDD (DCN SGE001179 )

This memorandum describes how ERG developed various tables and figures presented in EPA’s Technical Development Document for Effluent Limitations Guidelines and Standards for Oil and Gas Extraction (TDD) (DCN SGE01188 ) . Specifically, this memorandum focuses on the tables and figures listed in Table 1 of this memorandum all of which are specific to unconventional oil and gas (UOG) extraction

. TDD t ables and figures not liste d in Table 1 either did not require calculations and/or analyses by ERG or are described in separate, supporting memoranda. The Crosswalk Memorandum between Proposed and Final Technical Development Document for Effluent Limitations Guidelines and Standards for Oil and Gas Extraction: Tables and Figures (DCN SGE01334) contains a crosswalk of all ta bles and figures in the TDD. Appendix F of the TDD contains the name of t he relevant supporting memorandum for each TDD table and figure , where applicable. This memorandum is organized into the following sections :

 Section 1.0 discusses tables and figures in the TDD Chapter B, Scope and Industry Description

.

 Section 2.0 discusses tables and figures in the TDD Chapter C, Unconventional Oil and Gas Extraction Wastewater Volumes and Characteristics

.

 Section 3.0 discusses tables and figures in the TDD Chapter D, Unconventional Oil and Gas Extraction Wastewater Management and Disposal Practices

.

 Section 4.0 describes ERG’s quality assurance procedures

.

 Section 5.0 lists the references used for th e s e analys e s

.
For those figures/tables ERG generated specifically for this memorandum, the underlying data and analysis are contai ned in:

 Attachment 1

– Onshore Oil and Gas Drilling Activity

- DCN SGE001179 .A01

 Attachment 2

– EIA UOG R esource Potential

- DCN SGE001179 .A02

 Attachment 3

– TDD Data Compilation

- DCN SGE001179 .A03

For the tables/figures explained in more detail in this memorandum

, Table 1 provides the TDD chapter , memorandum section, and attachment information.Data Compilation Memorandum for the TDD

June 7 , 2016 Page 2

Table 1

. List of Tables and Figures Discussed in this Memorandum

TDD Chapter TDD Table

or Figure Number TDD Table or Figure Title Memo

. Section Memo

.

Attachment DCN

B Figure B

- 7 Length of Time to Drill a Well in Various UOG

Formations (2012 through 2014) 1.1 SGE001179 .A01

Figure B

- 13 Number of Active U.S. Onshore Rigs by Trajectory and

Product Type over Time 1.2 SGE001179 .A01

Table B

- 2 Active Onshore Oil and Gas Drilling Rigs by Well

Trajectory and Product Type (as of October 9

, 201 5 ) 1.2 SGE001179 .A01

Table B

- 3 a UOG Potential by Resource Type as of January 1, 201 3 1.3 SGE001179 .A02

Table F

- 3 b UOG Resource Potential: Shale as of January 1, 201 3 1.3 SGE001179 .A02

Table F

- 4 b UO G Resource Potential: Tight as of January 1, 201 3 1.3 SGE001179 .A02 Figure B

- 14 Projections of UOG Well Completions 1.4 SGE001179 .A03

C Table C

- 1 Sources for Base Fluid in Hydraulic Fracturing 2.0 SGE001179.A03

D Table D

- 1 UOG Produced Water Management Practices 3.1 SGE001179 .A03

Table D

- 5 Reported Reuse/Recycle Criteria 3.2.1 SGE001179 .A03

Table D

- 6 Reported Reuse/Recycle Practices as a Percentage of Total

Fracturing Volume 3.2.2 SGE001179 .A03

Figure D

- 9 Hypothetical UOG Produced Water Generation and Base

Fracturing Fluid Demand over Time 3.2.3 SGE001179 .A03

a

— This table in the TDD also includes some data from a separate ERG analysis ( Analysis of DI Desktop ® Memorandum

, DCN SGE01180 ). b

— These tables are related to the discussion about Table B

- 3 in Chapter B of the TDD

. For definitions of common terms used throughout the TDD, the supporting memoranda, and memoranda attachments, please refer to the Glossary in the introduction of the TDD.

1.0 C OMPILATION OF D ATA FOR TDD C HAPTER B

The following subsections discuss the data and methods used to d evelop the tables and figures listed in Table 1 and presented in TDD Chapter B.

1.1 TDD Chapter B, Section 2 .1 UOG Well Drilling and Construction (Figure B

- 7)

Figure B

- 7 “ Length of T ime to Drill a Well in Various UOG Formation s” shows the number of days required to drill a well in various UOG formations

. Attachment 1 ( DCN SGE001179 .A01 ) contains the underlying data in the tabs called “Drilling Days Data ” and “Drilling Da y s Figure” . For this analysis, ERG obtained data from Baker Hughes ’ U.S. Onshore Well Count (DCN SGE01234 )

. This data set is a quarterly census of the number of new onshor e oil and gas wells that were spud 1 in the U.S., and includes counts of the number of land wells, the number of land rigs, and the number of land wells per rig that were spud in each major U.S.

1 The term “spud” means to initiate the drilling of a well.Data Compilation Memorandum for the TDD

June 7 , 2016 Page 3

basin /formation 2 . These counts are available from first quarte r 2012 t hrough fourth quarter 2014

, and are representative of all U.S. oilfield activities.

To calculate the average time to drill a well in each formation presented in TDD Figure B

- 7, ERG divide d the number of days in each quarter (typically 9 1 or 92 days) by the number of wells per rig for that quarter to calculate drilling efficiency, or the average number of drilling days per well per rig in a given UOG basin/ formation.

For simplicity, ERG combined the well counts for the three different Woodford shale formations ( i.e., Ardmore Woodford, Arkoma Woodford, Cana Woodford) to represent the Woodford shale formation. ERG accomplished this by summing the well count s and rig counts respectively for each quarter for the three different Woodford shale format ions . ERG then perform ed the final calculation described above using the new, combined Woodford shale totals to get the number of drilling days per rig

.

1.2 TDD Chapter B, Section 3 .1 Historical and Current Drilling Activity for Unconventional Oil and Gas (Fi gure B

- 13 and Table B

- 2)

Baker Hughes periodically publishes the two active rig count datasets 3 listed below that provide different and more detailed information on active wells than the Baker Hughes U.S. Onshore Well Count data set (DCN SGE01234 ) described in Section 1.1

. ERG downloaded the se two additional rig count datasets in October 2015 and used them as the basis for Figure B

- 13 and Table B

- 2 in the TDD

. Attachment 1 ( DCN SGE001179 .A01 ) contains the downloaded rig count dataset s and ERG’s analys e s. Information contained in these two Baker Hughes datasets are described below.

 North America Rotary Rig Count (Jan 2000 4

- Current) ( DCN SGE01235 ) : tabulates the total number of active rigs in the U.S. and Canada for each week dating back to January 1991 and indicates product type ( i.e., oil

, gas , mis 5 ) and well trajectory ( i.e., horizontal, directional, vertical). The dataset includes the following f ields :

 Well T rajectory

 Number of rigs drilling horizontal wells

 Number of rigs drilling directional wells

 Number of rigs drilling vertical wells

 Total number of active rigs

 Product Type

 N umber of rigs drilling for oil

 Number of rigs drilling for gas

 Number of rigs drilling for “miscellaneous”

 Total number of active rigs (equals the total number of active rigs in the trajectory category above)

2 Baker Hughes reported a mixture of basins (e.g., Williston, Permian) and formations (e.g., Marcellus, Utica) in all of their rig counts datasets.

3 Baker Hughes’s r ig count datasets serve as an indicator of demand for products used in drilling, completing, producing, and processing hydrocarbons in the petroleum industry.

4 Although this source title includes the phrase “Jan 2000

– Current”, it includes data back to J anuary 1991.

5 Baker lists some wells as “Mis” which stands for miscellaneous. ERG added these types of rigs to oil rig counts for all analyses assuming that they represent wells that produce a mixture of oil and gas (i.e., wet gas).Data Compilation Memorandum for the TDD

June 7 , 2016 Page 4

 North America Rotary Rig Count Pivot Table ( DCN SGE01233 ) : presents a record for each active rig in North America on a weekly basis beginning in February 2011 . The dataset includes the following for each rig :

 Country ( i.e., Canada

, U nited S tates ) ;

 County;

 Basin 6 ;

 Drill For ( i.e., gas, oil , miscellaneous ) ;

 Location (i.e., land, offshore, inland waters);

 Trajectory ( i.e

., directional, horizontal, vertical , other ) ;

 Well Type;

 Well Depth;

 Water Depth;

 Date (both publish date and the date the data represents ) ;

 Rig count (i.e., number of rigs) ; and

 State/Province

. The following two subsections describe how ERG used these B aker Hughes datasets to generate Figure B

- 13 and Table B

- 2 in the TDD.

1.2.1 Figure B

- 13 “Number of Active U.S. Onshore Rigs by Trajectory and Product

Type over Time”

Figure B

- 13 “Number of Active U.S. Onshore Rigs by Trajectory and Product Type over Time” shows the estimated total number of active drilling rigs between January 2000 and October 2015

. The figure also plots the number of drilling rigs by trajectory type ( i.e., directional, horizontal, vertical) and by well type (i.e., oil, gas). To prepare this figure, E RG graphed the relevant U.S. data as reported in the Baker Hughes North America Rotary Rig Count dataset (Jan 2000

- Current) 7 (DCN SGE 0 1235 ). Attachment 1 (DCN SGE001179 .A01 ) contains the underlying data and analysis for Figure B

- 13 in the tabs called “Drill O ver Time Data (SGE01235) ” and “Drill over Time Figure ”.

1.2.2 Table B

- 2 “ Active Onshore Oil and Gas Drilling Rigs by Well Trajectory and Product Type (as of October 9, 2015 ) ”

Table B

- 2 “ Active Onshore Oil and Gas Drilling Rigs by Well Trajectory and Product Type (as of October 9, 2015 ) ” shows the number of active drilling rigs in the U.S. by basin and/or formation 8 . The rig counts are further broken down by well trajectory (i.e., directional, horizontal, vertical) and by well type (i.e., oil, gas)

. To develop Table B

- 2, ERG used the most
recent rig counts from the Baker Hughes N orth American Rotary Rig Count Pivot Table dataset

6 Baker Hughes reporte d a mixture of basins (e.g., Williston, Permian) and formations (e.g., Marcellus, Utica) in all of their rig counts datasets.

7 This document published by Baker Hughes includes drill rig counts for the entire North America but also provides separate counts for the United States. ERG used the data reported for the United States which is in the “ US Oil & Gas Split ” tab in DCN SGE001235.

8 Baker Hughes reported a mixture of basins (e.g., Williston, Permian) and formations (e.g., Marcellus, Utica) in all of the ir rig counts datasets.Data Compilation Memorandum for the TDD

June 7 , 2016 Page 5

downloaded on October 12, 2015 9

. Attachment 1 (DCN SGE001179 .A01 ) contains the underlying data and analysis for Table B

- 2 in the tabs called “Rigs by Basin Data (SGE01233) ” and “Rigs by Basin Table ”.

ERG used the following steps to summarize the rig counts :

1. Filtered the “Rigs by Basin D ata (SGE01233) ” tab for:

a. “U nited States ” rigs in the Country field b. “ L and” ( i.e., onshore ) rigs in the Location field

c. “ 10 / 9 / 2015 ” in the PublishDate field (as downloaded o n October 12, 2015 ). 2. In the “ Rigs by Basin Table ” tab

, ERG summed the total number of rigs, number of gas rigs, and number of oil rigs for each reported basin/ formation applying the filters in S tep 1

. For each well type (i.e., oil, gas), ERG further catego rized the number of oil or gas wells by well trajectory (i.e., directional, horizontal, vertical). Most data provided by Baker Hughes is on a basin/formation basis. Baker Hughes reported a mixture of basins (e.g., Williston, Permian) and formations (e.g., Marcellus, Utica) in all of their rig counts datasets. ERG distinguished which data reported by Baker Hughes were basins and which data were formations. ERG categorized the data by basin and formation, filling in the blanks as necessary based primarily on EIA publications that indicate UOG basins and formations. For Woodford formations, Baker Hughes published the following sub

- formation data for the Woodford shale: Cana Woodford, Arkoma Woodford, and Ardmore Woodford

. ERG combined th e number of rigs for the se into one common formation called “Woodford”.

1.3 TDD Chapter B, Section 4. 2 Unconventional Oil and Gas Resource Potential ( Table

B

- 3 , Table F

- 3 Table F

- 4 )

The following tables in the TDD summariz e the total new well potential , estimated ultimate recover y (E UR), and technically recoverable resource (TRR) for four resource types (i.e., shale gas, shale oil, tight gas, tight oil) and for each known formation (e.g., Marcellus, Barnett) :

 Table B

- 3

- “UOG Resource Potential by Type as of January 1, 201 3 ”

.

 Table F

- 3

- “UOG Resource Potential: Shale as of January 1, 201 3 ”

.

 Table F

- 4

- “UOG Resource Potent ial: Tight as of January 1, 201 3 ”

. 10

To create these tables

, ERG used the data reported in Table 9.3 of the U.S. Energy Information Administration ’s (EIA) Assump tions to the Annual Energy Outlook 201 5 (DCN SGE01190 )

. Attachment 2 ( DCN SGE001179 .A02 ) contains the underlying data and analysis

. In the assumptions to each Annual Energy Outlook (AEO) report
, EIA reports the total resource potential for each active and prospective UOG formation. EIA bases these estimates on studies completed by the United States Geological Survey (USGS) , historical oil and gas production, and expected future advances in drilling technology

. The two r esource estimate s

9 The Baker Hughes data was downloaded on 10/12/2015. These data had last been updated by Baker Hughes on 10/9/2015.

10 Tables F

- 3 and F

- 4 are located in Chapter F of the TDD but support Chapter B.Data Compilation Memorandum for the TDD

June 7 , 2016 Page 6

reported by EIA tha t ERG used in our analysis are described below. 11 The “ EIA UOG Potential Data ” tab in Attachment 2 contains the estimates as reported by EIA

.

 Technically R ecoverable R esource ( TRR )

– TRR is the total crude oil 12 and/or gas that is believed to be extractable from a formation based on current technology disregarding economics

. In EIA’s 201 5 Assumptions report (DCN SGE 01190 ) , TRR estimates are reported as of January 1, 201 3

. EIA reports natural gas TRR in units of trillion cubic feet ( T CF) and crude oil TRR in u nits of billion barrels ( B B bls). ERG converted the natural gas TRR from TCF to billion cubic feet (BCF) and the crude oil TRR from B B bls to million barrels (MMbbls) before inputting the data in the “ EIA UOG Potential Data ” tab in Attachment 2 (DCN SGE00117 9 .A02 ).

 Estimated U ltimate R ecovery ( EUR )

– Lifetime recovery of crude oil

, and/or natural gas per well based on existing production data and current/expected drilling practices in each formation (e.g., vertical or horizontal drilling). These estimates ar e averages across all wells; actual production may vary significant ly from well to well

. EIA reports natural gas EUR in units of BCF per well a nd crude oil EUR in units MMb b l s per well.

ERG used EIA’s TRR and EUR estimates to calculate new well potential by formation (e.g., Marcellus) and by resource type (e.g., shale gas, tight oil)

. ERG calculated the new well potential based on EIA’s TRR estimates which assume current oil and gas extraction technology (e.g. hydraulic fracturing, horizontal drilling). Th ese estimates do not factor in future changes to TRR estimates, advances in drilling technology, or economic conditions that ultimately determine how many wells industry drills.

Specifically, E RG used the following procedures for this analysis:

1. In the “ EIA UOG Potential Data ” tab in Attachment 2 (DCN SGE001179 .A02 ), ERG calculated new well potential for each formation or sub

- formation (e.g., Central Fayetteville, West Fayetteville) reported by EIA using Equation 1

. 13 The natural gas and crude oil TRR and EUR can be used interchangeably to find the same new well potential for each formation. A f

ew unconventional oil formations have zero natural gas TRR. For these, ERG used the crude oil TRR and EUR to calculate new well potential

. Otherwise, ERG used the natural gas TRR and EUR to calculate new well potential. Equation 1

New Well Potential formation ( w e lls ) = TRR formation ( BCF )

EUR formation ( BCF

well )

11 EIA also publishes the following statistics for each UOG formation: total land area (square miles), percent of land area that may be developed (%), and maximum well spacing (wells/square mile). Multiplying these values for a given formation provides an es timate of new well potential.

12 EIA’s TRR for crude oil includes the TRR for lease condensates. EIA provides TRR estimates for natural gas plant liquids (NGPLs) separately but they were not the focus of ERG’s analysis. EIA defines NGPLs production as the extraction of gas plant liquid constituents such as ethane

, propane , normal butane, isobutane

, and natural gasoline , sometimes referred to as extraction loss

. 13 ERG calculated the total new well potential using the same method EIA presented in EIA’s Assumptions to the Annual Energy Outlook 2015 (DCN SGE01190).Data Compilation Memorandum for the TDD

June 7 , 2016 Page 7

2. In the “ EIA UOG Potential Data ” tab in Attachment 2 (DCN SGE001179 .A02 ), ERG used engineering judgment to assign each formation and sub

- formation (reported by EIA)

a common formation name. For example, EIA reported resource potential separately for “Fayettevil le

- Central” and “Fayetteville

- West. ” ERG consolidated these formation names into “Fayetteville.” 3. In the “ EIA UOG Potential Data ” tab in Attachment 2 (DCN SGE001179 .A02 ), ERG classified each formation and sub

- formation into one of four resource types: shale gas, shale oil, tight gas, or tight oil. For most formations, ERG used the resource types assigned to formations by EIA in their shale formation map (DCN SGE01191), t heir tight formation map (DCN SGE00155), and their Assumptions to the Annual Energy Outlook 2013 (DCN SGE00486)

. 14 However, a ll unconventional oil formations were combined by EIA in this report i nto the group called “tight oil ” which includes both shale and tight formations. Therefore, ERG assigned each unconventional oil play to either the shale oil or tight oil category as shown in EIA’s shale and tight maps (DCN SGE01191 and DCN SGE00155). 15
4. In the “Potential Data by Formation” tab i n Attachment 2 (DCN SGE001179 .A02 ), ERG used Equation 2 and Equation 3 below t o recalculate total new well potential and TRR for each consolidated formation in order to eliminate sub

- formations from the list

. ERG calculated the average EUR for each consolidated formation using Equation 4 and the results from Equation 2 and Equation 3 . The results of this step generate Table F

- 3 and F

4 in the TDD

. Equation 2

TRR formation ( BCF ) = ∑ TRR sub

− formations ( BCF )

Equation 3

New Well Potential formation ( wells ) = ∑ New Well Potential sub

− formatio n s ( wells )

Equation 4

Average EUR formation ( BCF
well )

= TRR formation ( BCF )

New Well Potential formation ( wells )

5. In the “Potential Data by Resource Type ” tab i n Attachment 2 (DCN SGE001179 .A02 ), ERG used Equation 5 and Equation 6 below to recalculate total TRR and total new well potential for each of the four resource types that were assigned by ERG in Step 3

, above

. Next, ERG calculated the weighted average EUR for e ach resource type using Equation 7 and the results from Equation 5 and Equation 6

. The results of this step generate Table B

3 in the TDD

. Equation 5

TRR resource type ( BCF ) = ∑ TRR formations ( BCF )

14 EIA’s 2015 assumptions report (DCN SGE0 1190) did not organize the list of UOG formations by resource type but the 2013 version of the report (DCN SGE00486) did.

15 A few formations did not appear in EIA’s 2013 assumptions report or in the EIA shale and tight maps. ERG used assessment reports com

pleted by the USGS to assign the appropriate resource type to these formations.Data Compilation Memorandum for the TDD

June 7 , 2016 Page 8

Equation 6

New Well Potential resource type ( wells ) = ∑ New Well Potential formations ( wells )

Equation 7

Wei g h ted Average EUR resource type ( BCF
well )

= TRR resource type ( BCF )

New Well Potential resource type ( wells )

Table B

- 3 also shows estimates of active UOG wells during 2013

– 201 5

. ERG obtained these estimates using data from Drilling i nfo’s (DI) Desktop ® well database described in a separate memorandum

, Analysis of DI Desktop ® Memorandum (DCN SGE0 118 0 )

.

1.4 TDD Chapter B, Section 3 .3 Current and Projections of Future UOG Well Completions (Figure B

- 14)

Figure B

- 14 “Projections of UOG Well Completions” shows the projected number of UOG wells completed annually and cumulatively using information from the October 2012 IHS Report, America’s New Energy Future: The Unconventional Oil and Gas Revolution and the US Economy (DCN SGE 00 864 )

. Attachment 3 ( DCN SGE001179 .A03 ) contains the underlying data and analysis in the tabs called “ IHS Well Projections” and “ IHS Well Projections Figure ”

.

IHS estimated annual well completion s for 2012, 2015, 2020, 2025, 2030, and 2035. IHS estimates are provided for unconventional oil wells and unconventional gas wells. 16 For gas wells, IHS estimates are further broken down by resource type (i.e., shale

, tight )

. ERG extrapolated the number of w ell completions between the years reported by IHS. For example, IHS reported 7,179 unconventional oil well completions in 2012 and 8,472 completions in 2015, or an increase of 1,293 unconventional oil wells over this three

- year period. Therefore, ERG

assum e d that 431 unconventional oil wells are completed each year from 2012 to 2015.

Using the number of wells completed each year (either reported by IHS or extrapolated from IHS data) ; ERG calculated the cumulative well completions by summing the number of completed wells for that year and all preceding years starting in 2012

.

2.0 C OMPILATION OF D ATA FOR TDD C HAPTER C , S ECTION 1.1 B ASE F LUID

C OMPOSITION (T ABLE C

- 1)

TDD Table C

- 1 “Sources for Base Fluid in Hydraulic Fracturing” shows the composition of base flui d used for hydraulic fracturing across major basins and various UOG formations. Attachment 3 ( DCN SGE001179 .A03 ) contains the underlying data references and analysis in the tab called “Base Fluid Data ”

. For some basins/formations, ERG identified data from multiple references and/or projected 17 data in addition to historic year data . Therefore, each formation may have multiple rows in this tab where each row represents the various references and types of d ata (i.e., historic or projected)

. In addition, literature reported various types of sources that are

16 IHS uses the same definition of UOG as defined in this memorandum.

17 ERG identified one report that projected base fluid composition for “low water use”, “most likely”, and “ high water use” scenarios for 2020 and 2060. ERG used the “most likely” scenario for 2020 (DCN SGE00639).Data Compilation Memorandum for the TDD

June 7 , 2016 Page 9

used for base fluid. ERG categorized the reported data from the source into one of three categories in the “Base Fluid Data ” tab:

 Fresh water

– Naturally occurring water on the Earth 's surface . Examples include ponds

, lakes

, rivers and streams , and certain underground aquifers . Fresh water is generally characterized by having low concentrations of dissolved salts and other total dissolved solids (TDS)

.

 Brac kish water

– W ater that has more salinity than fresh water , but not as much as
seawater

. Example sources include certain underground aquifers

, effluent from publicly owned treatment plants (POTWs)

, and wastewater from other industri es

.

 Reuse/recycle water

– This is any UOG extraction wastewater (i.e., flowback, long

term produced water, drilling wastewater).

To populate Table C

- 1 in the TDD, ERG compiled percentages from the “Base Fluid Data ” tab in the “Base Fluid Summary” tab on a basins/formations basis

. For basins/formations where ERG identified projected data in addition to historic data

, ERG created a separate set of columns for each basin/formation combination in the tab

. Table C

- 1 presents t hese projected data parenthetically.

3.0 C OMPILATION OF D ATA FOR TDD C HAPTER D

The following subsections discuss the data and methods used to d evelop tables and figures listed in Table 1 and presented in TDD Chapter D

.

3.1 TDD Chapter D, Intro duction (Table D

- 1)

Table D

- 1 “UOG Produced Water Management Practices” presents information about how UOG operators manage produced wate r across basins containing major UOG formations. ERG reviewed existing literature sources for information about wastewater management practices . Some sources only contain ed qualitative produced water management information, while others also report ed the p ercentage of produced water disposed of via each management practice. Because quantitative data were not available across all formations, ERG categorized management practices in each formation as follows :

 X

– A small (<10 percent) or unknown portion of UO G produced water was managed with this management practice;

 XX

– A moderate portion (>10 and <50 percent) of UOG produced water was managed with this management practice; or

 XXX

– A majority (>50 percent) of UOG produced water was managed with this
manag ement practice.

The “ UOG PW Management ” tab in Attachment 3 ( DCN SGE001179 .A03 ) contains the underlying data references used to create Table D

- 1 . The attachment includes additional information that is not included in the TDD about how ERG designated the “X” categories

. The “Additional Comments” column provides further explanation about the type of information reported in the underlying reference that ERG used to assign the “X” category.Data Compilation Memorandum for the TDD

June 7 , 2016 Page 10

3.2 TDD Chapter D, Section 3 .2 Reuse/Recycle Drivers (Table D

- 5 , Table D

- 6 , and Figure D

- 9 )

The following subsections describe how ERG used existing literature to generate T able D

- 6 , Table D

- 6 and Figure D

- 9 in the TDD

.

3.2.1 Reuse Criteria

Table D

- 6 “Reported Reuse/Recycle Criteria” shows ranges of observed or recommended constituen t concentration s for use in fracturing base fluid (i.e., mixture of wastewater and other source water) . It also shows the associated potential issue that the fluid or well may experience with concentrations in excess of that concentration

. Attachment 3 ( DCN SGE001179 .A03 ) contains the underlying data and analysis in the tabs called “Reuse Criteria Data” and “Reuse Criteria Summary”

.

E RG compiled the reported criteria (in units of mg/L, c/mL, or S

. U

. ) for each constituent from existing literature . From the se compiled values, ERG calculated the minimum and maximum reported criteria (i.e., concentrations) for each constituent

. In addition to the concentration criteria, ERG presented the associated potential issue that the fluid or well may experience, as repo rted in Acharya et al., 2011 ( DCN SGE 00070 ) , in Table D

- 5 in the TDD

.

3.2.2 Reuse Drivers at the Well Level

Table D

- 6 “ Reported Reuse/Recycle Practices as a Percentage of Total Fracturing Volume” presents the volume of reused/recycled wastewater as a percent of the total base fluid volume used to fracture a specific well , or the blending ratio, for several different formations. Ta ble D

- 6 reports the actual blending ratio and /or the estimated maximum potential blending ratio reported in literature (e.g., technical presentation from an industry conference). To generate this table, ERG only used literature where UOG operators or indus try experts were the author. The estimated maximum potential blending ratio was described in literature as the typical flowback volume per well compared to the typical fracturing volume per well

. Attachment 3 ( DCN SGE001179 .A03 ) contains the underlying dat a and analysis in the “Reuse Blending Ratios Data” and “Reuse Blending Ratios Summary” tabs

. In the “Reuse Blending Ratios Data” tab, ERG tabulated actual reuse percentages and estimated maximum

reuse potential on a basin and formation basis based on value s reported in ex isting literature. ERG calculated the minimum and maximum values within each category (i.e., actual blending ratio and estimated potential blending ratio) by basin and formation and presented the resulting
range in the “Reuse Blending Ratio Summary” tab and Table D

- 6 in the TDD

.

3.2.3 Reuse Drivers at the Formation Level

Figure D

- 9 “Hypothetical UOG Produced Water Generation and Base Fracturing Fluid Demand o ver Time” illustrates a hypothetical scenario for UOG produced water generation. This figure indicates that

, as a formation matures, the volume of base fluid needed to fracture subsequent wells may be less than the volume of produced water generated by producing wells in the area. This figure was regenerated from a wastewa ter disposal figure presented in Shell Canada Limited ’s October 29, 2012 presentation, “ Identifying the Recycling and Treatment Criteria that M

ust be Met to Avoid Scaling and Enable Successful Re

- Use ” (DCNData Compilation Memorandum for the TDD

June 7 , 2016 Page 11

SGE 0030 5.A 0 3)

. The scenario is for one operator in a particular formation based on a hypothetical drilling program. ERG regenerated this figure by interpreting values of “wastewater generation” and “demand for fracturing” from the figure in the Shell presentation

. Attachment 3 ( DCN SGE001179 .A03 ) contains the estimated volumes derived from the Shell presentation, which were used as the underlying data for Figure D

- 9 in the TDD

, in the “Hypothetical Scenario Data” and “Hypothetical Scenario Figure ” tabs

.

4.0 Q UALITY C ONTROL P ROCEDURES

All of the analyses presented in this memorandum adhered to the Environmental Engineering Support for Clean Water Regulations Programmatic Quality Assurance Project Plan (PQAPP) (DCN SGE00957) and the Unconventional Oil and Gas (UOG) Supplemental Quality A ssurance Project Plan (SQAPP) (DCN SGE00 958 ), including collecting, evaluating, and analyzing existing data and information

. Specifically, ERG used the procedures described in Section 4 of the PQAPP to gather and manage existing data in support of the UOG rulemaking. ERG staff entered reference information for relevant sources into the UOG Literature Review database. The ERG index keeper reviewed all reference information, assigned each reference a Document Control Number (DCN ), imported the reference infor mation into the UOG Project File Index database, and saved referenced files in the Electronic Project File folder.

ERG also used the procedures described in Section 3 of the SQAPP when collecting existing data for use in the UOG rulemaking. ERG used a comb ination of sources, including reports, papers, and online databases from state regulatory agencies such as departments of environmental protection and oil and gas commissions. As shown in Table 2 in this memorandum, ERG assigned a source flag (A, B, C or D ) to all references used in these analyses. ERG defines each source flag as follows:

 Source Flag A

- J ournal articles and documents prepared by or for a government agency (e.g., site visit reports, industry meeting notes);

 Source Flag B

- Documents prepared by a verified source 18 that include citation information (e.g., operator reports, vendor documents, conference presentations, university publications);

 Source Flag C

- Documents prepared by a verified source that do not include citation information (e.g., operator reports, vendor documents, conference presentations); and

 Source Flag D

- Documents prepa red by a source that could not be verified and that do not include citation information

. EPA and ERG followed the procedures described in Section 7.0 of the PQAPP to generate, evaluate, and analyze data using a spreadsheet. ERG conducted the following QA

c hecks during the analyses:

 ERG created the three Microsoft Excel spreadsheets provided in Attachment s 1 through 3 to track useful data and to document analyses. ERG performed a 100

18 ERG considered sources as “verified” if we were able to find information about the author outside of the reference document. ERG primarily verified information by looking for company/organization websites that confirmed the author’s affiliation with the UOG industryData Compilation Memorandum for the TDD

June 7 , 2016 Page 12

percent check of all data entry, manipulations and calculations, and docume nted

these in an internal version of the spreadsheet.

 ERG had a senior staff member familiar with ELGs and the UOG rulemaking review the results from the three Microsoft Excel spreadsheets provided in Attachments 1 through 3.

5.0 R EFERENCES

Table 2 provides DCNs, citations , and source flags for references used in the s e analyses

. The references in Table 2 are sorted by DCN.

Table 2 . References

DCN Source Citation Source Flag a
SGE00007.A10 Mantell, Matthew, Chesapeake Energy Corp. 2011. Produced Water Reuse and

Recycling Challenges and Opportunities Across Major Shale Plays B

SGE00070 Acharya, Harish; Matis, Hope; Kommepalli, Hareesh; Moore, Brian; Wang, Hua.

2011. Cost Effective Recovery of Low

- TDS Frac Flowback Water for Re

- use. A

SGE00090 NYSDEC. 2011. Suppl. Generic Env. Imp. Statement on Oil, Gas, & Soln. Mining

Reg. Prgm. Prelim. Rev. Draft. A

SGE00091 Rimassa, Shawn; Howard, Paul; Blow, Kristel; Schlumberger. 2009. Optimizing

Fracturing Fluids from Flowback Water. Society of Petroleum Engineers. A

SGE00092 ALL Consulting. 2004. Coal Bed Methane Primer. US DOE. A

SGE00093 Veil, John et. al. 2004. A White Paper Describing Produced Water from Production of

Crude Oil, Natural Gas, and Coal Bed Methane. By Argonne Nati Lab A

SGE00094 Journal of Environmental Law and Litigation, Volume 17(2) B
SGE00095 URS. 2011. Water

- Related Issues Associated with Gas Production in the Marcellus

Shale. (March 25). B

SGE00096 Sumi, Lisa. 2008. Shale Gas: Focus on the Marcellus Shale. Oil and Gas

Accountability Project / Earthworks. B

SGE00155 U.S. Energy Info rmation Administration. 2010. Tight Sands Gas Plays, Lower 48

States. Prepared by EIA Office of Oil and Gas. (June). A

SGE00254 MI DEQ. 2006. MI Oil and Gas Regulations: Natural Resources and Environmental

Protection Act

— No. 451 of the Public Acts of 1994. (April) A

SGE00275 U.S. EPA. 2012. Site Visit Report: Citrus Energy Corporation Marcellus Shale Gas

Operations. (January 22). A

SGE00276 U.S. EPA. 2012. Meeting with XTO Energy, Inc. about Unconventional Oil and Gas

Sanitized. A

SGE00284 Hayes, Thomas et al. 2012. Barnett and Appalachian Shale Water Management and

Reuse Technologies. RPSEA A

SGE00298.A23 Robie Cathey. 2012. Ecosphere. Ecosphere Tech. B

SGE00305.A03 Cheung, Timothy. 2012. Identifying the Recycling and Treatment Criteria That Must

be Met to Avoid Scaling and Enable Successful Reuse. Shell. C

SGE00311.A12 Mark Mazoch. 2012. Fayetteville Shale. Southwestern Energy. B

SGE00339 Susquehanna River Basin Commission (SRBC). 2011. Susquehanna River Basin

Commission: Water Withdrawals & Consumptive Use for Natural Gas Industry. AData Compilation Memorandum for the TDD

June 7 , 2016 Page 13

Table 2 . References

DCN Source Citation Source Flag a
SGE00341 John A. Veil. 2011. Water Management Practices Used by Fayetteville Shale Gas

Producers. Argonne Nat'l Lab and US Dept of Energy Natl Energy Tec Lab A

SGE00379 Hill, David A. 2012. The Future Is NOW for Water Recycling in the Niobrara.

Wyoming Energy News. C

SGE00422 James Werline. 2011. Water Requirements and Sustainable Sources in the Barnett

Shale. Devon Energy. B

SGE00480 Richard Luedecke. 2012. Energy Water Conservation & Recycling 33rd Annual

Governor's Water Conference. Devon Energy. C

SGE00486 U.S. Energy Information Administration. 2013. Assumptions to the Annual Energy

Outlook 2013. A

SGE00507 Boschee, Pam. 2012. Handling Produced Water from Hydraulic Fracturing. Oil &

Gas Facilities. B

SGE00507 Boschee, Pam. 2012. Handling Produced Water from Hydraulic Fracturing. Oil &

Gas Facilities. B

SGE00521 ERG. 2012. Camp, Meghan; Ruminski, Brent. Notes for Shale Gas Industry Meeting

Held on 29 February 2012. (April 20). A

SGE00532 Hansen, E; Mulvaney, D; Betcher, M. 2013. Water Resource Reporting and Water

Footprint from Marcellus Shale Development in WV and PA. (October 30). B

SGE00556 Nicot , Jean

- Philippe, et al. 2011. Current and Projected Water Use in the Texas

Mining and Oil and Gas Industry. A

SGE00575 Petroleum Equipment Suppliers Association (PESA). 2012. Outlook for Domestic

Unconventional Resources. Presentation at PESA Annual Meet ing. B

SGE00616 U.S. EPA. 2013. Summary of the Technical Workshop on Wastewater Treatment and

Related Modeling. (April 18) A

SGE00625 U.S. EPA. 2015. Site Visit Report: Southwestern Energy Fayetteville Shale Gas

Operations. Sanitized. A

SGE00637.A05 Vidic, Radisav. 2013. Reuse of Produced Water For Hydraulic Fracturing. B

SGE00639 Nicot et al. 2012. Oil & Gas Water Use in Texas: Update to the 2011 Mining Water

Use Report. Univ of TX at Austin. (September) A

SGE00691 U.S. EPA. 2013. Summary of the Technical Workshop on Water Acquisition

Modeling: Assessing Impacts Through Modeling and Other Means. (September). A

SGE00705 ERG. 2014. Ruminski, Brent. Notes on Call with Hydrozonix, LLC on 7 February

2014. (March 7.) A

SGE00721 U.S. EPA. 2015. Analysis of Hydraulic Fracturing Fluid Data from the FracFocus

Chemical Disclosure Registry 1.0. (March). A

SGE00728 IHS. 2012. America’s New Energy Future: The Unconventional Oil and Gas

Revolution and the US Economy. Volume 1: National Economic Contributions. B

SGE00738 Livingston, Doug. 2013. Water Recycling: The Cure for Drillers' Drinking Problem?

Shale Magazine. B

SGE00864 IHS. 2012. America’s New Energy Future: The Unconventional Oil and Gas

Revolution and the US Economy. October 2012. B

SGE00957 ERG. 2013. Environmental Engineering Support for Clean Water Regulations

Programmatic Quality Assurance Project Plan (PQAPP). AData Compilation Memorandum for the TDD

June 7 , 2016 Page 14

Table 2 . References

DCN Source Citation Source Flag a
SGE00958 ERG. 2014. Unconventional Oil and Gas (UOG) Supplemental Quality Assurance

Project Plan (SQAPP). A

SGE00966 CCST. 2014. Advanced Well Stimulation Technologies in California: An

Independent Review of Scientific and Technical Information. A

SGE00991 USGS. 2008. Assessment of Undiscovered Oil and Gas Resources of the Permian

Basin Province of West Texas and Southeast New Mexico. A

SGE00992 United States Geological Survey. Unknown. Woodbine Formation. Accessed on

10/21/2014. A

SGE00993 United States Geological Survey. Unknown. Buda Formation. Accessed on

10/21/2014. A

SGE01178 ERG. 2016. Analysis of Centralized Waste Treatment Facilities (CWTs) Accepting

UOG Extraction Wastewater. A

SGE01180 ERG. 2016. Analysis of DI Desktop® Database. A

SGE01182 ERG. 2016. Analysis of Pennsylvania Department of Environmental Protection’s Oil

and Gas Waste Reports. A

SGE01188 U.S. EPA. 2016. Technical Development Document for Proposed Effluent

Limitations Guidelines and Standards for Oil and Gas Extraction. A

SGE01190 U.S. Energy Information Administration. 2015. Assumptions to the Annual Energy

Outlook 2015. A

SGE01191 U.S. Energy Information Administration. 2015. Lower 48 States Shale Plays.

Prepared by EIA Office of Oil and Gas. (April). A

SGE01233 Baker Hughes. 2015. North America Rotary Rig Count Pivot Table (Feb 2011

–

Current). (October 9). Downloaded on 10/12/2015. B

SGE01234 Baker Hughes. 2015. U.S. Onshore Well Count. (January 9). Downloaded on

10/12/2015. B

SGE01235 Baker Hughes. 2015. North America Rotary Rig Count (Jan 2000

– Current). (October

9). Downloaded on 10/12/2015. B

SGE01334 ERG. 2016. Memorandum Providing a Crosswalk between Tables and Figures in the

Proposed and Final Technical Development Document for Effluent Limitat ions Guidelines and Standards for Oil and Gas Extraction

. A

a

– Source Flag A

- J ournal articles and documents prepared by or for a government agency (e.g., site visit reports, industry meeting notes); Source Flag B

- Documents prepared by a verified source that include citation information (e.g., operator reports, vendor documents, conference presentations, university publications); Source Flag C

- Documents prepared by a verified source that do not include citatio n information (e.g., operator reports, vendor documents, conference presentations); and Source Flag D

- Documents prepared by a source that could not be verified and that do not include citation information.A TTACHMENT 1 : O NSHORE O IL AND G AS D RILLING A CTIVITY E XCEL F ILE ( DCN SGE001179 .A01 )A TTACHMENT 2 : EIA UOG P OTENTIAL E XCEL F ILE ( DCN SGE001179 .A02 )A TTACHMENT 3: TDD D ATA C OMPILATION E XCEL F ILE ( DCN SGE001179 .A03 )