### MEMORANDUM

TO: Lisa Biddle, EPA

FROM: James K. O’Connell, ERG

Brent Ruminski, ERG Jason Sese, ERG Sarah Yates, ERG

DATE: March 31

, 201 5

SUBJECT: Unconventional Oil and Gas (UOG) Produced Water Volumes and

Characteri zation Data Compilation

– DCN SGE00724

T his memorandum describes the data and methods used to compile unconventional oil and gas (UOG) produced water volume s and characterization data for the Technical Development Document (TDD) for Proposed Effluent Limitations Guidelines and Standards for Oil and Gas Extraction ( DCN SGE00704 ). Specifically, this memorandum focuses on information included in Chapter C in the TDD and covers the following:

 Data sources used

 Preparation and analysis of data

 Compilation of summary data

This memorandum is organized into the following sections :

 Section 1.0 focuses on how ERG compiled UOG produced water volume data to create Table C

- 6, Tab le C

- 7, and Table C

- 8 in the TDD

.

 Section 2.0 describes how ERG compiled UOG produced water rates over time to
create Figure C

- 2 in the TDD

.

 Section 3.0 describes the UOG produced water characterization database and its related analyses

.

 Section 4.0 describes individual analyses ERG perform ed to obtain produced water volume and characterization data

.

 Section 5.0 describes ERG’s quality control (QC) procedures

.

 Section 6.0 lists the references used for this memorandum and its attachments

.

 Section 7.0 contains the Microsoft Excel spreadsheet and Microsoft Access database attachments to this memorandum and their Document Control Numbers (DCNs). These spreadsheets and databases contain the u nderlying data andMemorandum

March 31 , 2015 Page 2

calculations used to support the information presented in the TDD and to create

the TDD tables and figures discussed in this memorandum.

Tables and figures in the TDD that are not described in this memorandum either did not require calc ulations or analys i s by ERG

, or are described in separate, supporting memoranda. Appendix F of the TDD contains a crosswalk of all tables and figures in the TDD and the name of the relevant supporting memorandum, if applicable. Table 1 provides an index of the tables and figures explained in more detail in this memorandum

.

Table 1 . List of Tables and Figures Discussed in this Memorandum

TDD Table or Figure Number TDD Table or Figure Title Memo

. Section Memo

. Attachment

Number

Figure C

- 2 Ranges of Typical Produced Water Generation Rates

Over Time After Fracturing 2.0 SGE00724.A01

Figure C

- 3 Anions and Cations Contributing to TDS Concentrations

in Shale and Tight Oil and Gas Formations 3.3 SGE00724.A01 3

Figure C

- 4 Chloride, Sodium, and Calcium Concentrations in

Flowback and Long

- Term Produced Water (LTPW) from Shale and Tight Oil and Gas Formations 3.3 SGE00724.A01 3

Figure C

- 5 Barium Concentrations in UOG Produced Water from

Shale and Tight Oil and Gas Formations 3.3 SGE00724.A01 3

Table C

- 6 UOG Well Flowback Recovery by Resource and Drill

Type 1.0 SGE00724.A01

Table C

- 7 UOG Well Long

- Term Produced W ater Generation Rates

by Resource and Drill Type 1.0 SGE00724.A01

Table C

- 8 UOG Well Produced Water Volume s by Formation 1.0 SGE00724.A01

Table C

- 11 Concentrations of Select Classical and Conventional

Constituents in UOG Produced Water 3.3 SGE00724.A01 3

Table C

- 13 Concentrations of Select Anions and Cations

Contributing to TDS in UOG Produced Water 3.3 SGE00724.A01 3

Table C

- 15 Concentrations of Select Organic Constituents in UOG

Produced Water 3.3 SGE00724.A01 3

Table C

- 17 Concentrations of Select Metal Constituents in UOG

Produced Water 3.3 SGE00724.A01 3

Table C

- 19 Concentrations of Select Radioactive Constituents in

UOG Produced Water 3.3 SGE00724.A01 3Memorandum

March 31 , 2015 Page 3

This memorandum will refer to the following terms , which are also used throughout the TDD , the supporting memoranda, and memoranda attachments :

 Unconventional oil and gas (UO G) resources 1

– crude oil and natural gas 2 produced by a well drilled 3 into a low porosity, lo w permeability formation (including, but not limited to, shale gas, sh ale oil, tight gas, tight oil).

 UOG extraction wastewater

– sources of wastewater pollutants associated with production, field exploration, drilling, well completion, or well treatment for unconventional oil and gas extraction

. 4 UOG extraction wast ewater includes produced water , drilling wastewater, and produced sand 5

.

 Produced water

– the water (brine) brought up from the hydrocarbon

- bearing strata during the extraction of oil and gas. This can include formation water, injection water, and any chemicals added downhole or during the oil/water separation process . Based on the stage of com pletion and production the well is in, produced water can be further broken down into the following components:

o Flowback

– the produced water generated by UOG wells in the initial period after hydraulic fracturing prior to production (i.e., fracturing flui d, injection water, any chemicals added downhole, and varying amounts of formation water) . After the hydraulic fracturing procedure is completed and pressure is released, the direction of fluid flow reverses, and the fluid flows up through the wellbore to the surface. The water that returns to the surface is commonly referred to as “flowback.” Flowback is typically reported as a percentage of fracturing fluid volume in literature and by industry. 6

o Long

- term produced water (LTPW)

– the produced water generated by UOG wells during the production phase

, after the initial flowback process. Long

term produced water includes increasing percentages of formation water that make up the total volume of long

- term produced water

. Long

- term produced
water co ntinues to be produced throughout the lifetime of the well and is usually reported in terms of flow rates in literature and by industry. 7

1 UOG resource types are categorized into shale and tight formations.
2 Natural gas can include “natural gas liquids,” co mponents that are liquid at ambient temperature and pressure.
3 UOG wells may be drilled using horizontal, vertical, or directional well trajectories. Literature sometimes refers to well trajectory as “drill type”.
4 Stormwater is not considered a source of UOG extraction wastewater. In general, no NPDES permit is required for discharges of stormwater from any field activities or operations associated with oil and gas production, except as specified in 40 C.F.R. 122.26(c)(1)(iii ) for discharges of a reportable quantity or that contribute to a violation of a water quality standard. States may impose additional requirements for management of drilling site stormwater.
5 Drilling wastewater and produced sand are not discussed in thi s memorandum. Additional information about drilling wastewater can be found in ERG’s Unconventional Oil and Gas (UOG) Drilling Wastewater memorandum (DCN SGE00740).
6 ERG also expressed flowback as a percent of fracturing fluid volume in its analyses. Flow rate changes rapidly during flowback

, making it difficult to summarize.
7 ERG analyzed LTPW in terms of flow rates because these rates do not vary significantly over time. In addition, LTPW is generated over the entire life of the well. Because well life varies significantly between well s , ERG did not convert LTPW flow rates to a total volume.Memorandum

March 31 , 2015 Page 4

 Drilling wastewater

– t he liquid waste stream separated from recovered drilling

fluid (mud) and drill cuttings during the drilling process

.

1.0 C OMPILATION OF UOG P RODUCED W ATER V OLUME D ATA
ERG compiled data to characterize typical volumes of water used for fracturing fluid and the rate at which wastewater is generated during UOG extraction on a per well basis. Specifically , ERG compiled the following data:

 Fracturing fluid volume ( million gallons per well, Mgal/well) 8

 Flowback r ecovery ( p ercent of fracturing fluid volume )

 Long

- term produced water rates ( gallons per day per well, gpd/well)

Table C

- 8

, “ UOG Well Produced Water Volumes by Formation

, ” contains the se data listed above by UOG formation (e.g., Marcellus) and well trajectory. ERG also generated Table s C

- 6 and C

- 7 in the TDD , both of which are higher

- level aggregations of the data presented in Table C

- 8 . Table C

- 6

, “ UOG Flowback Recovery by Resource and Drill Type

, ” presents flowback recovery at the resource type level

, and Ta ble C

- 7

, “ UOG Well Long

- Term Produced Water Generation Rates by Resource and Drill Type

, ” presents long

- term produced water rates at the res ource type level. The following subsections provide more information about the data

sources and method s used to generate Table C

- 6, Table C

- 7, and Table C

- 8 in the TDD

.

1.1 Key Data Sources

ERG used three general categories of datasets for this analysis :

 N ational

- level d atasets ( Drilling i nfo, Inc

. (DI) Desktop ® , FracFocus ® )

 S tate

- level d atasets ( e.g., state oil and gas databases)

 Available l iterature

The specific data fields that ERG used from each of these sources are explained in the individual example an alyses presented in Section 4.0

.

1.1.1 National

- level Datasets

ERG used two national

- level datasets, DI Desktop ® and FracFocus ®

. T he structure of
t hese datasets required ERG to conduct an analysis to calculate the lower range , median, and
upper range values from a given dataset 9 . The DI Desktop ® and FracFocus ® analyses are explained in Section s 4.1 and 4.2 of this memorandum , respectively

.

1.1.1.1 DI Desktop ® W e ll File Database (DCN SGE00520)

DI Desktop ® is a comprehensive well file database compiled and maintained by DI that provides a record for all oil and gas well s drilled in the United States. The underlying data in the

8 F lowback volumes can be estimated by multiplying the total fracturing fluid volume by the percent of fracturing fluid returned as flowback. However, ERG does not perform this calculation.
9 In most cases, ERG calculated the 10 th and 90 th percentiles to estimate lower and upper ranges and to eliminate outliers.Memorandum

March 31 , 2015 Page 5

DI Desktop ® database comes from individual state oil and gas agencies and contains a r ecord for all oil and gas wells ever drilled

. 10 Data for each well include : well API number

, well completion date, well depth, latitude, longitude

, and well trajectory. DI Desktop ® also includes annual oil, gas, and produced water production per well from 2 007 through 2011. The version of the DI Desktop ® database that ERG used for this analysis was downloaded in January 2012

, representing, for the most part, data from 2011. The raw data are contained in the “Active Oil and Gas Wells” table in Attachment 3 (DCN SGE00724.A03 ).

1.1.1.2 FracFocus ® D atabase (DCN SGE00 585 )

In March 2015 , EPA’s Office of Research and Development (ORD) released a database they developed from public disclosures to FracFocus ® (DCN SGE00 585 )

. FracFocus ® is an industry

- managed national registry of chemicals used in hydraulic fracturing. Operators submit disclosures to FracFocus ® for individual wells that they hydraulically fracture

. 11 Historically, submitting disclosures has been voluntary

, but some states are beginning to mandat e reporting to FracFocus ®

. Each record include s the well completion date, well type (oil or gas), total fracturing fluid volume ( in gallons) , well API number, well depth, latitude, longitude , and the concentrations of additives in the fracturing fluid

. FracFocus ® publishes reports for individual wells in portable document file (PDF) format

. EPA’s ORD converted these PDF files into a Microsoft Access database to conduct a national

- level analysis of chemical additives

. ORD’s FracFocus ® raw data base is con tained in the “ ORD FF DB ( DCN SGE00585) ” table in Attachment 5 (DCN SGE00724.A05 ).

1.1.2 State

- level Datasets

To perform select analyses to estimate typical produced water volumes and rates, ERG used databases from O hio, Colorado , N ew M exico , N orth D akota , and W yoming

. ERG included these states because they have significant UOG activity and their state oil and gas agencies publish comprehensive databases that contain monthly or annual produced water volumes per well (depending on the state), and include well API number

, formation name, well completion date, and/or well trajectory. The analyses ERG performed are described in Sections 4.3 through 4.9 ; a ttachments 6 through 12 contain the data and ERG’s calculations (DCN SGE00724.A06

- 12). A more detailed description of each data source is provided in the “Data Source” subsection s in Se ctions 4.3 through 4.9

.

1.1.3 Available Literature

ERG also used other literature that reported UOG produced water v olumes or rates
, such as detailed reports, site visit reports, and technical presentations from conferences

. These data sources appear in Table 9 at the end of this me morandum , and are also listed in the “Source” column in the “PW Data” tab in Attachment 1 (DCN SGE00724.A01 ). Many of the references that ERG used r eported produced water volumes and rates in terms of lower range , median or average , and /or upper range

. For example, one reference specifically reported that a typical horizontal Barnett well requires approximately 1,000,000 to 7,300,000 gal lons of fracturing

10 The exact year recordkeeping began varies by state, but the majority of states go back to 1900.
11 These reports represent we lls completed in UOG formations, conventional oil and gas (COG) formations , and coalbed methane formations

.Memorandum

March 31 , 2015 Page 6

fluid

, with a median of 3,700,000 gallons

, based on data for 14

, 000 wells (DCN SGE00465). ERG entered t hese values into the PW Data tab as the lower range , 12 upper range, median /average , and num ber of data points

. This data compilation procedure is further described in Section 1.2

.

1.2 General Data Compilation Procedures

ERG took the following steps to generate Tables C

- 6, C

- 7, and C

- 8 in the TDD . Each of the se step s corresponds to a specific tab in Attachment 1 (DCN SGE00724.A01 ) , as noted in the headings below

. Step 1 : Data input into PW Data tab

The PW Data tab contains the fracturing fluid volume and produced water volume data generated by the i ndividual analyses that ERG performed ( described in Sections 4.1 through 4.9 ) and reported in other available literature. ERG initiated a new record item (i.e., row) in this tab only when the exis ting data source reported the UOG formation and well trajectory

. ERG calculated t he weighted average as explained in Step 2 ( Equation 1 ) and Step 3 ( Equation 2 ). The PW Data tab contains the following data fields :

 Basin

 F ormation

 Resource type (shale, tight)

 W ell trajectory ( horizontal, directional, vertical)

 Fracturing fluid volume

◦ Lower range ( barrels /well)

◦ Median/average ( barrels /well) 13

◦ Upper range ( barrels /well)

◦ Number of d ata points

◦ Formation Level Weighted Average Fracturing Volume

◦ Resource Level Weighted Average Fracturing Volume

 Flowback recovery (% of fracturing fluid injected)

◦ Lower range (%)

◦ Median/average (%) 13

◦ Upper range (%)

◦ Number of data points

◦ Formation Level Weighted Average Flowback Recovery

◦ Resource Level Weighted Average Flowback Recovery

 Long

- term produced water

12 The upper and lower ranges represent either the 10 th and 90 th percentiles from analyses of comprehensive databases ERG analyz ed or the typical minimum and maximum values reported by industry. In order to exclude outliers, these ranges do not include absolute minimum and maximum values that are possible.
13 In some cases, ERG’s individual analyses produced median values that would be entered into this field. In other cases, values from literature were reported as an average. Therefore, a value in this field could represent a median, an average, or an uncharacterized single value.Memorandum

March 31 , 2015 Page 7

◦ Lower range ( b arrels / day/ well)

◦ Median/average ( barrels/day /well) 13

◦ Upper range ( barrels/day /well)

◦ Number of data points

◦ Formation Level Weighted Average LTPW Rate

◦ Resource Level Weight ed Average LTPW Rate

 Source Flag (A, B, C

, or D) 14

 Data Quality Justification

 Notes

 Source ( i.e., DCN number )

ERG followed the procedure s listed below for entering data into the PW Data tab :

 Where data were available for input , but the number of data points was not reported, ERG assigned the number of data points equal to 1.

 W here data were only available in the form of a range (e.g., 100 to 150 gpd/well), ERG assigned these two values to the lower and upper range fields

, resp ectively

. ERG assigned no value to the median/average field and assigned a 2 to the number of data points field.

 ERG only considered non

- null values in the analysis. Note that values reported as zero were not considered null values. Values reported as zero s were counted as zeros in all calculations.

 Where a data point w as report ed only as a minimum or maximum , ERG assigned this value to the lower or upper range field

, as appropriate

. ERG assigned no value to the median/average field and assigned the number of data points equal to 1.

 In most cases, ERG used literature that speci fic ally reported flowback in terms of percent of fracturing fluid volume

, and long

- term produced water in te r ms of flow rate (e.g., gallons per day, barrels per day, gallons per year, barrels per year). If the literature did not report the data on these base s, ERG’s a lternative approaches/assumptions are described in the “ Notes ” column in the PW Data tab in Attachment 1 (DCN SGE00724.A01 ).

Step 2: Generation of PW Data by Formation tab (TDD Table C

- 8)

T o create TDD Table C

- 8

, ERG aggregated the data in the PW Data tab by formation and well trajectory (e.g., horizontal Barnett wells, vertical Marcellus wells)

. Table C

- 8 presents the following three different types of produced water d ata : fracturing fluid volume

, flowback recovery (percent of fracturing fluid) , and long

- term produced water generation rate

. For each formation and well trajectory combination, and for each of these three types of produced water data

, ERG calculated the following :

14 For a discussion on the source flags, please see Section 5.0.Memorandum

March 31 , 2015 Page 8

 Minimum of the lower range

– Identified the minimum value in the lower range

reported in the PW Data tab for each formation and well trajectory combination

 Weighted average of the median/average values

– Calcula ted the wei g h t ed average of the average/median values reported in the PW Dat a tab for each formation and well trajectory combination

, using Equation 1 below.

 Maximum of the upper r ange

– Identified the maximum value in the upper range reported in the PW Data tab for each formation and well trajectory combination

 Number of data points

– Summed the total number of data p o ints reported in the PW Data tab for each formation and well tr ajectory combination.

Equation 1

Where,

Form i = E ach formation and trajectory combination N Form,i = Number of total data points for each formation and trajectory combination N i = Number of data points for line item entered i n to the PW Data tab Vol i = V olume data point ( i.e., fracturing fluid volume , flowback recovery , or long

- term produced
water rate )

The calculated values are listed i n the columns marked “ Calculated Numbers by Formation an d Well Trajectory (from the PW Data tab) ” in the PW Data by Formation tab . ERG rounded these values to two significant figures for the TDD ; these rounded numbers are listed in the c olumns marked “Sig Figs for TDD ” in the PW Data by Formation tab.

This tab also includes columns indicating the number of data points that came from sources with a specified source flag. This information is presented to demonstrate the quality of information. For more information about source flags, see Section 5.0

Step 3 : Generation of PW Data by Resource tab ( TDD Table C

- 6 and Table C

- 7)

T o create TDD Table s C

- 6 and C

- 7, ERG aggregated data in the PW Data tab by resource type and well trajectory (e.g., horizontal shale wells, vertical tight wells). Table C

- 6 presents fracturing fluid volume and flowback recovery by UOG resource type and well trajectory. Table C

- 7 shows long

- term produced water rates by UOG resource type and well trajectory

. ERG calculated the following for each of these types of volume data:

 Minimum of the lower range

– Identified the minimum value in the lower range reported in the PW Data tab for each resource type and w ell trajectory combination

.

 Weighted average of the median/average values

– Calculated the wei g h t ed average of the average/median values reported in the PW Data tab for each resource type and well trajectory combination using Equation 2 below.Memorandum

March 31 , 2015 Page 9

 Maximum of the upper range

– Identified the maximum value in the upper range

reported in the PW Data tab for each resource type and well trajectory combination

.

 Number of data p oints

– Summed the total number of data p o ints reported in the PW Data tab for each resource type and well trajectory combination.

Equation 2

Where,

Res i = Each resource type and trajectory combination N Res ,i = Number of total data points for the resource type and trajectory combination N i = Number of data points for the specific data point/range entered Vol i = V olume data point ( i.e., fracturing fl uid volume , flowback recovery , or long

- term produced

water rate)

ERG rounded the calculated values to two significant figures for the TDD ; these rounded numbers are listed below the row marked “Sig Figs for TDD Tables ” in the PW Data by Resource tab.

2.0 C OMPILATION OF UOG P RODUCED W ATER R ATES O VER T IME A FTER F RACTURING
ERG compiled produced water rates (e.g., gallons per day) over time after fracturing from available literature to generate Figure C

- 2 in the TDD

. T his graph show s that flowback
rates after fracturing are initially high and decrease rapidly over time before gradually leveling off to long

- term produced water rates.

2.1 Data Sources

ERG used numerous literature sources that reported produced water rates over time after hydraulic fracturing. E RG only included data points from source s report ing the associated well trajectory

, number of days after fractur e , and associated UOG formation. These data sources are identified by DCN number for each data point in the “Source ” column in the FB Data tab i n Attachment 1 (DCN SGE00724.A01 ). Most of these references were studies of flowback rates and characteristics over time after fracturing

. 15

2.2 Methods and Procedures

To compile typical produced water flow rates over time after fracturing, ERG took the following steps :

15 Most of these studies specifically reported flowback rates, as opposed to produced water, long

- term produced water, or a more vague description of UOG wastewater.Memorandum

March 31 , 2015 Page 10

Step 1 :

ERG entered data from literature in to the following data fields in the FB Data tab in Attachment 1 (DCN SGE00724.A01 ) :

 Basin

 F ormation

 W ell T rajectory ( horizontal, vertical)

 Reported F low R ate ( barrels per day, b pd ) 16

 Number of Da ys after Fractur ing

 Number of Data P oints

 Source Flag

 Notes

 Source ( DCN number)

Step 2:

Next, ERG categorized each data point based on how long after fracturing the reported flow rate was measured. The categories were 1

– 5 days, 6

– 14 days, and 15

– 90 days. For example, if a source reported the flow rate three days after the fracture, ERG assign ed it to the “1

- 5 days” category. The appropriate category was listed for each data point in the “Day Category_ERG” column in the FB Data tab in Attachment 1 (DCN SGE00724.A01 ).

Step 3:

The FB Data Summary tab in Attachment 1 (DCN SGE00724.A01 ) shows ERG ’s calculations of the 10 th percentile, median (i.e., 50 th percentile)

, and 90 th percentile flow
rates , and the number of data points for each UOG formation

, well trajectory , and day category (e.g., 1

- 5 days)

. ERG c onverted values from barrels per day to g allons per day by multiplying by 42 (gallons/barrel) and round ing the results to two significant figures

. This tab also shows the list of sources that ERG used to calculate flow rates for each formation and well trajectory

, and a list of the corresponding source flags.

ERG also calculated the same results for all basins and formations combined in the last row in the FB Data Summary tab in Attachment 1 and summed the total number of data points . The results for all basins and formations are shown graphically in the FB Rates Graph tab

, which is also Figure C

- 2 “Typical UOG Well Produced Water Generation Rates” in the TDD

. In the FB Rates Graph tab, ERG obtained t he “ W ell L ife (~10

– 30 years) ” da ta points from the “ W eighted A verage LTPW R ate” column in the PW Data by Resource tab in Attachment 1

.

16 References reported flowback rates in units of barrels per day. Step 3 show s how ERG converted these rates from barrels per day to gallons per day.Memorandum

March 31 , 2015 Page 11

3.0 UOG P RODUCED W ATER C HARACTERIZATION D ATA
ERG developed the UOG Wastewater Characterization database to collect information about the constituents in UOG extraction wastewater. The database compiles information about each well (e.g., location), the type of wastewater sampled (e.g., flowback), measured constituents , and the range of concentrations measured and recorded. The UOG Wastewater Characterizati on database is included in Attachment 14 (DCN SGE00724.A01 4).

W hile the database compiles information on various types of wastewater
, t his memorandum only discusses the wastewater characterization data associated with UOG produced water . Additionally, w astewater characterization data associated with drilling wastewater is discussed in the Unconventional Oil and Gas (UOG) Drilling Wastewater

m emorandum (DCN SGE00 740 ). Sources of information included in the UOG Wastewater Characterization d atabase and anal yses o f the collected data are described in detail in the following sections of this memorandum

.

3.1 Data Sources

ERG com piled characterization data from approximately 50 sources, including publicly available databases, industry reports, and numerous journal articles and technical papers. ERG also analyzed and aggregate d data from the 2014 United States Geological Survey ( USGS ) Produced Water Geochemical D atabase v. 2.0 (PROVISIONAL) (USGS database) by well , as described in Section 4.10 and shown in Attachments 15 and 16 (DCN SGE00724.A01 5

- A16). ERG also standardize d the data from ORD’s non

- confidential business information ( CBI ) 17 well operator data, as described in Section 4.11 and shown in Attachment 17 (DCN SGE00724.A01 7).

Table 9 l ists all data sources that ERG used to develop the UOG Wastewater Characterization database (specifically flagged with an “X” in the “WW Char.” column)

, including the document control numbers (DCNs), source citations, and source quality flags (A, B, C, or D) . The source quality flags are described further in the TDD and in Section 5.0 in this memorandum . In some cases, multiple sources reference the same original data source; therefore, ERG reviewed the content of each source to identify duplicat ed data. When ERG found duplicat ed data, ERG selected data from only one source.

3.2 Key Database Fields and Standardization Procedures

The UOG Wastewater Characterization database (DCN SGE00724.A01 4) was designed to incorporate information from different data sourc es and to identify key wastewater characterization information, including:

 Measured constituent

 Constituent category (e.g., metal)

 Location/region

 Basin

17 ORD removed all of the data flagged as confidential business information (CBI) under the Toxic Substances Control Act of 1976 (TSCA) before providing this subset of data to ERG.Memorandum

March 31 , 2015 Page 12

 Formation

 Resource type (shale

, tight)

 Well type (gas or oil)

 W ell trajectory ( horizontal, directional, vertical)

 Wastewater description ( e.g., flowback, long

- term produced water, UOG wastewater)

 Sample information ( e.g., number of samples, units, analytical methods)

 Concentration values ( e.g., detection limit minimum value , median value

, 18
maxim um value)

ERG extracted the information listed above from each data source, where available. Missing data elements were marked as “unknown.”

Because naming conventions, terminology, and measured units differed by data source

, ERG standardize d each data field to allow for comparison and summary of data across the entire database. The following sections provide details on how ERG standardized the overall dataset to facilitate comparison of data across all data sources

. All of the data, crosswalk s, and analyses described below are contained within the UOG Wastewater Characterization database (DCN SGE00724.A01 4).

3.2.1 Data Preparation

ERG used three main raw data tables in the UOG Wastewater Characterization database :

a g eneral “Pollutant Concentratio ns” summary table , data imported from the USGS d atabase , and national

- level produced water characterization data from EPA’s ORD. The general “Pollutant Concentrations” summary table was compiled from the various sources listed in Table 9 , but excluded the USGS and ORD data. The methods that ERG used to standardize the data from the USGS and ORD datasets are discussed in Sections 4.10 and 4.11 , respectively. These three data tables were then compiled into a single data table in the UOG Wastewater Characterization database

. When extracting data that were expressed as a range by a data source , ERG assigned the
two range values to the lower and upper range fields. Where only a single measurement was reported, that value was e ntered into the median field ; therefore, a data point in the median field

c ould be a median, an average, or some other uncharacterized single value.

ERG placed data related to the measured constituent , basin, formation, resource type, well type, well tr ajectory , and wastewater description into raw data fields , capturing the data as they we re reported by the source. Before performing any analyses o f the dataset, ERG removed all leading and trailing spaces from the raw data fields.

18 The “median” field in the UOG Wastewater Characterization database can represent medians, averages, or other uncharacterized single values.Memorandum

March 31 , 2015 Page 13

3.2.2 Constituent Standardiz ation and Constituent Category Assignments

ERG created a list of all constituents included in the various sources and created a “Pollutant Parameter Crosswalk” to standard ize constituent name s

. For example, “Co” and “Cobalt” were standardized to “Cobalt.”

In a separate “Pollutant Categories Crosswalk,” ERG assigned primary and secondary (optional) categories for each standard constituent name to allow for grouping and analysis of certain const ituents . For example, aluminum was placed in the “Metals” category. All crosswalks used in the data standardization and analyses are contained in the database.

3.2.3 Minimum, Median , 19 and Maximum Data

For each set of reported constituent concentrations from a given source , ERG compared the minimum, median

, 19 and maximum values , where available, to ensure regularity in the data. If the reported values did not reflect the correct relative sequence (minimum value < median value < maximum value), ERG reviewed the values to determine the source of error , and if appropriate, corrected the values so that the correct relative sequence was maintained

. ERG completed this corre ction in queries 101 through 121 in the UOG Wastewater Characterization database. ERG o nly considered non

- null values in the analysis

. ( Note that values reported as zero were not considered null values

. )

In some cases, data sources indicated that certain values were not measured because they did not exceed the limit of detection. Where a source reported a non

- detect value but listed the associated limit of detection, ERG used the limit of detection as the measured value

. Where a source reported a n on

- detect value but did not report the associated limit of detection, ERG did not assign a value.

3.2.4 Formation Name Standardization

ERG compiled a list of reported formation names and created a “Raw Formation Name Crosswalk” to standardize formation names. For example, data sources that reported variations of the Bakken formation (e.g.

, Bakken MT, Bakken, ND Core, etc.) were standardized and updated to Bakken. Formation names that were not reported within the reference and that ERG could no t associate with an existing formation

, or that were reported as being associated with a conventional well

, were designated as “NA

– Unknown” or “NA

– Conventional,” respectively.

3.2.5 Basin Name Standardization and Location/Region Assignment

Similar to the formation name standardization method discussed above, ERG created a separate “Raw Basin Name Crosswalk,” to standardize and update basin names.

However, in some instances, data sources did not report a specific basin, but did report the associated formation. ERG generated a “Basin

- Formation Crosswalk” of known basins and formations to infer basin names based on the formation names

. ERG devised t he crosswalk by

19 The “median” field in the UOG Wastewater Characterization database can represent medians, averages, or other unch aracterized single values.Memorandum

March 31 , 2015 Page 14

referencing EIA documents and using engineering judgment (DCN SGE00988, DCN SGE 00 153, DCN SGE00155 ) . Basin names that were not reported within the reference , that ERG could not associate with an existing basin

, or that were reported as being associated with a conventional oil and gas well were designated as NA

– Unknown or NA

– Conventio nal, as appropriate

.

ERG also created a “Basin

- Region Crosswalk,” assign ing each basin to its appropriate region (Northeast, Gulf Coast, Midcontinent, Southwest, Rocky Mountain, or West Coast), as identified by the U.S. EIA in their 2014 Assumptions to the Annual Energy Outlook (DCN SGE00988)

.

3.2.6 Well Trajectory

, Resource Type

, and Well Type Standardization

Based on the information available with in each data source, ERG assigned well trajectory

, resource type, and well type for each set of data points , using the “Drill Type Crosswalk” and “Well Type

– Resource Type Crosswalk.” ERG identified w ell trajectory as horizontal, vertical, directional, or unknown. ERG defined r esource type as conventional, NA (unknown), shale and/or tight, and ERG defined well type as NA (unknown or conventional), or oil and/or gas.

3.2.7 Wastewater Description Standardization

ERG standardized w astewater descriptions provided in each data source into the following categories : 20 fracturing fluid, base fluid, flowback, produced water; UOG
wastewater 21 ; and unknown

. These were standardized using the “WW Description Crosswalk ” in the UOG Wastewater Characterization database (DCN SGE00724.A01 4)

. ERG captured

w astewater descriptions as reported in the existing data source and did not reclass ify any wastewater descriptions . ERG only standardized names (e.g., “flowback” and “fracturing fluid flowback” were consolidated into “flowback”)

.

3.2.8 Unit

s of Measure Standardization

ERG converted reported constituent concentrations to standardized units o f measure appropriate for each constituent

. ERG established a “Unit Definition Crosswalk,” in the database to list units and conversion factors.

3.3 Data Summary Analysis for TDD

Once ERG standardized all of the data and compiled them into a single summary table in the database , E RG queried produced water data for 79 specific constituents of interest for the TDD . ERG compiled the list of constituents of interest based on the presence and relevance of the given constituent i n the UOG industry, as indicated by data provided in existing literature

.

20 These terms (fracturing fluid, base fluid, flowback, produced water, UOG wastewater, and unknown) refer to the wastewater descriptions reported in the underlying data sources and do not always correspond with the definitions of these terms as used throughout the TDD, the supporting memoranda, and memoranda attachments (defined at the beginning of this memo).
21 ERG assigned the “UOG wastewater” category to any data source that reported data associated with wastewater generated fr om the well after fracture, but that did not specify flowback or produced water.Memorandum

March 31 , 2015 Page 15

The list comprised 19 classical and conventional constituents , 31 metals, 21 organics, 2 others, and 4 radioactive constituents , as listed in Table 2 below

.

Table 2

. Constituents of Interest for the TDD , by Constituent Category

Constituent Category Constituent

Classicals and Conventionals Alkalinity

, Ammonia

, Bicarbonate, BOD

, Bromide

, Carbonate, Chloride

, COD

, Fluoride

, Hardness

, Hardness as CaCO3

, Nitrate

, Nitrite

, Oil and Grease

, pH

, Phosphate

, Specific Conductivity

, Sulfate

, TDS

, TOC

, TSS

Metals Aluminum

, Antimony

, Arsenic

, Barium

, Beryllium

, Boron

, Cadmium

, Calcium

,

Chromium

, Cobalt

, Copper

, Fluorine

, Iron

, Lead

, Lithium

, Magnesium

, Manganes e, Mercury

, Molybdenum

, Nickel

, Phosphorus

, Potassium

, Selenium

, Silver

, Sodium

,

Strontium

, Thallium

, Tin

, Titanium

, Vanadium

, Zinc

Organics 1,2,4

- Trimethylbenzene

, 1,3,5

- Trimethylbenzene

, 2

- Butoxyethanol

, Acetone

, Benzene

, BTEX

, Carbon Disulfide

, Chlorobenzene

, Chloroform

, Ethanol

, Ethylbenzene

, Isopropylbenzene

, Methanol

, Methyl Chloride

, Naphthalene

, Phenol

, Pyridine

, Tert

- butylacetate

, Tetrachloroethylene

, Toluene

, Xylenes

Other Sulfate Reducing Bacteria

, Sulfide

Radioactives Gross Alpha

, Gross Beta

, Radium 226

, Radium 228

ERG exported data for the selected constituents from the database to Excel to generate summary tables and figures for the TDD. Attachment 13 (DCN SGE00724.A01 3) includes the Excel file with the exported data and all of the analys e s that ERG conducted to generate summary tables and figures for the TDD. The Table of Contents (TOC) in Attachment 13 indicates the specific tabs with data and calculations for each TDD figure and tab le.

ERG did not use actual m inimum and maximum reported values for the summary tables ; ranges were defined using the lowest and highest median values (i.e., the minimum value corresponds to the minimum median value and the maximum value corresponds to the highest median value)

. 22 E RG further reduced the dataset by removing data that were related to conventional or unknown wells, and limited the wastewaters of interest to the following types of wastewater, as reported in the UOG Wastewater Characterization d atabase (DCN SGE00724.A01 4): flowback, UOG wastewater , and produced water.

The majority of the tables presented in Section C. 3 (UOG Extraction Wastewater Characterization) of the TDD were compiled by filtering the final dataset by specific constituent categories (e.g., classical and conventional, metals, organics) and tabulating the minimum of the median data field , median of the median data field , maximum of the median data field , number of data points, and number of detects 23 for each constituent

. ERG also sometimes organized the produced water characterization data by formation name. T he analyses used to generate drilling wastewater characterization tables are discussed in the Unconventional Oil and Gas (UOG) Drilling Wastewater memorandum (DCN SGE00 74 0 ).

22 As discussed previously, the “median” values may represent medians, averages, or other uncharacterized single values.
23 Number of data points was based on the total number o f samples taken; number of detects was based on the number of data points with valid measurements.Memorandum

March 31 , 2015 Page 16

ERG generated Figure C

- 3 in the TDD by first tabulating the median concentration for each ionic contributor to TDS ( e.g

. , chloride, calcium, potassium, barium) by formation (see the TDS Contrib Ions w Form Summary tab in Attachment 13, DCN SGE00724.A0 1 3 )

. ERG listed the primary ionic contributors as individual constituents ; minor contributors were combined into the “Other Dissolved Constituents ” catego ry

. 24

ERG generated Figure C

- 4 and Figure C

- 5 in the TDD using built

- in Excel functions (e.g., percentile, median ) to calculate the concentration quartiles for each specific data subset of interest. The underlying data used to generate Figure C

- 4 are shown in the Cl, Na, and Ca Summary Data tab

, and the underlying data used to generate Figure C

- 5 are shown in the Barium Data tab in Attachment 13 (DCN SGE00724.A01 3). ERG used these underlying data sets to illustrate the data using box and whisker plots (see the Ca, Na, and Ca Figure and Barium Figure tabs in Attachment 13, DCN SGE00724.A01 3 )

.

4.0 A DDITIONAL UOG P RODUCED W ATER V OLUME AND C HARACTERIZATION D ATA :

A NALYSES U SING N ATIONAL AND S TATE

- L EVEL D ATASETS
The following subsections describe analyses that ERG performed on individual datasets that contained UOG produced water volumes and characteristics data

. Each of these individual analyses is contained in a separate attachment. The results of these analyses were used as inputs to the compilation analyses described in Sections 1.0 through 3.0 of this memorandum. The attachments are identified in the following subsections

, along with the analyses descriptions

. The following subsections describe analyses that ERG completed using national

- level datasets to generate data inputs to the PW Data tab in Attachment 1 (DCN SGE00724.A01 ) (see Section 1.2 ).

4.1 Attachment s 2 and 3 DI Desktop ® Long

- term Produced Water Generation Rates

ERG ana lyzed Drillingi nfo’s (DI) Desktop ® Well Database to calculate typical long

- term produced water generation rates for specific UOG formations on a per well basis and by well trajectory

. ERG entered t he results of this analysis into the PW Data tab in Attachment 1 (DCN SGE00724.A01 ). Attachment 2 (DCN SGE00724.A02 ) contains the Microsoft Excel portion of the DI Desktop ® analysis. Attachment 3 contains the Microsoft Access d atabase portion of the

a nalysis ; the queries performed in this attachment are described in S ection 4.1.3

. ERG converts the raw DI

- Desktop ® data into a more useful format for calculating long

- term produced water generation rates in Microsoft Excel . This process is described in more detail in Section 4.1.2

.

4.1.1 Data Source

ERG used the list of active oil and gas wells in the DI Desktop ® database (shown in the

“ Active Oil and Gas Wells ” table in Attachment 3, DCN SGE00724.A03 ). ERG identified the list of active oil and gas wells in a separate analysis described in ERG’s Analysis of DI Desktop® memorandum (DCN SGE00 963 ). The version of the DI Desktop ® database that ERG analyzed

24 ERG used engineering judgment to determine the “primary” versus “minor” ionic contributors based on availability of data and reported measured values (see “TDS Contrib Ions w Form Summary” tab in Attachment 13, DCN SGE00724.A01 3).Memorandum

March 31 , 2015 Page 17

was last downloaded in 2012 and contains data from 2011. The DI Desktop ® database reports the following data that ERG used in this analysis: 25

 Formation 26

 Well trajectory ( horizontal, directional, vertical, unknown)

 Well completion date (DD/MM/YYYY)

 2007 produced water production (barrels) 27

 2008 produced water production (barr els)

 2009 produced water production (barrels)

 2010 produced water production (barrels)

 2011 produced water production (barrels)

4.1.2 Method

s and Procedures

To estimate typical long

- term produced water rates, ERG used the following procedures :
Step 1 : Summar ize Data by UOG Formation

Using the queries described in Section 4.1.3

, ERG compiled UOG well counts from the DI Desktop ® database by UOG formation name and by well completion year. In each
query , ERG also summed the total annual produced water volume for each well completion year

. The query descriptions are provided in Section 4.1.3

. An example matrix resulting from these queries ( for horizontal Barnett shale wells ) is shown in Figure 1 . Results for all UOG formations are contained in the Detailed Results tab in Attachment 2 ( DCN SGE00724.A02 ). ERG only pulled records with sufficient data for this analysis, which

, at a minimum include d, the following:

 Well c ompletion date: Not null

 Annual produced w ater volume : Not null 28

 Well trajectory : Not null and not “unknown”

Step 2: Calculation of Annual Long

- term Produced Water Rates by Completion Year

In the Detailed Results tab of Attachment 2 ( DCN SGE00724.A02 ), ERG calculated the daily average long

- term produced water rate (bbl/day/well) for each completion year (i.e., across the rows). ERG used Equation 3 to calculate this avera ge , which sums the annual long

- term produced water volumes starting with the year after completion year (i.e., WCY+1) 29 through 2011

, and divides by the number of wells, 365 days, and number of

25 Some of these data fields may be missing in the DI Desktop® database. ERG excluded records that were missing one or more of these data fields from this analysis.
26 For this anal ysis, ERG specifically used the “ Common Formation Name ” field created by ERG in a separate analysis of the DI Desktop® dataset (DCN SGE 009 63).
27 The DI Desktop ® database includes annual produced water volumes but does not specify whether it is flowback or long

- term produced water.
28 Some states did not report water production to DI Desktop® . ERG did not include wells for states that have no water production data (e.g., OK, AR)

. 29 This excludes flowback volumes for wells that were fractured during the well c ompletion year.Memorandum

March 31 , 2015 Page 18

production years

. 30 Figure 1 shows the resulting calculations for the Barnett Shale example. As previously explained, t he DI Desktop ® database contains annual produced water volumes

, but does not specif y whether it is flowback and/ or long

- term produced
water. Excluding the produced water volumes during the well completion year in Equation 3 ensures that the calculated long

- term produced water rates do not include flowback volumes , as shown by the black cells in Figure 1

. ERG chose the number of completion years to include for a given formation based on drilling activity and engineering judgment . For example, the number of Bakken wells drilled per year was minimal until the 2000's

, but Cotton Valley well drilling began ramping up in the late 1990's.

Equation 3

Where: LTPW

– l ong t erm p roduced w ater WCY

– well completion year

Figure 1 . Example Calculation of Daily Average Long

- Term Produced Water Rate (Horizontal Barnett Shale Wells)

Step 3: Summary of Results

The Summary of Results tab of Attachment 2 (DCN SGE00724.A02 ) contains the final results of this analysis which includes a row for each UOG formation and well trajectory combination. For each combination

, ERG calculated the 10 th percentile, 50 th percentile

, and 90 th percentile of the “daily average long

- term produce d water rate (bbl/day/well)”

30 ERG assumed that all wells generated long

- term produced water for 365 days per year after the well completion
year.Memorandum

March 31 , 2015 Page 19

column in the Detailed Results tab. 31 ERG calculated the 10 th percentile and 90 th percentile ( as opposed to minimum and maximum ) to remove outlying data points. The total number of data points (i.e., number of wells ) is also cal culated for each UOG formation and well trajectory. ERG entered these results into the PW Data tab of Attachment 1 (DCN SGE00724.A01 ).

4.1.3 Attachment 3

– Query Description s

Table 3 describes the queries performed in Attachment 3 (DCN SGE00724.A03 )

. Table 3

. Query Descriptions for DI Desktop® Database (Attachment 3, DCN SGE00724.A03 )

Attachment 3 Quer y Query Description Applicable Tabs in Attachment 2

00

- Available Formations with Data S u ms the produced water volume for UOG formations by state

. ERG used this list to determine which UOG formations could be analyzed in this analysis and to determine which states should be e xcluded from this analysis because they did not report water production data to DI Desktop®. No applicable tab

01 a This query creates a new table called “Results” and sums

annual produced water volumes for each year 2007

- 2010 for the horizontal Bakken shale wells by:

 Completion year

 Number of wells completed during that year Detailed Results tab

01 b through 01 x T hese queries sum annual produced water volumes for each

year 2007

- 2010 for each UOG formation and by :

 Completion year

 Number of wells completed during that year

 Drill typ e (horizontal + directional or vertical)

. The results of these queries are appended to the Results table created by query “01a”. Detailed Results tab

Note: DI Desktop was formerly known as HPDI, Inc.

4.2 Attachment s 4 and 5 FracFocus ® Fracturing Fluid Volumes

ERG analyzed the FracFocus ® database published by EPA’s Office of Research and Development (ORD) in March 2015 (DCN SGE00 585 ) to calculate typical fracturing fluid volumes for specific UOG formations on a per well basis and by well trajectory . The results of this analysis were entered in to the PW Data tab in Attachment 1 (DCN SGE00724.A01 ). Attachment 4 (DCN SGE00724.A04 ) contains the Micros oft Excel portion of the analysis

. Attachment 5 (DCN SGE00724.A05 ) contains the Microsoft Access database portion of the analysis , including the queries that link ORD’s FracFocus ® data to other oil and gas databases, which are described in more detail in S ection 4.2.3

.

31 DI Desktop® reports well trajectory as “drill type.” Therefore, all raw databases and query results in Attachment 3 des cribe well trajectories using the term “drill type”.Memorandum

March 31 , 2015 Page 20

4.2.1 Data Sources

ORD’s FracFocus ® database ( DCN SGE 00 585 ) (see Section 1.1.1.1 ) contains underlying fracturing fluid volume data and well API number

. I t does not contain UOG formation name s or well trajector ies, both of which are necessary for this analysis. Therefore, ERG used DI Desktop ’s ® Well database (DCN SGE00 5 20 ) and various state databases to provide these additional data fields in this analysis. 32 As shown in

Figure 2 , the common data field in FracFocus ® , D I Desktop ® , and various state databases is the well API number. Only well API numbers that were contained in both the FracFocus ® database (DCN SGE00585) and the other databases were included in the results of this analysis. For example , FracFocus ® contains records for wells that were completed after the most recent date contained in the version of DI Desktop ® that ERG used. These FracFocus ® records were excluded from the analysis

. For most states, ERG linked the FracFocus ® records to DI Desktop ® t o obtain UOG formation and well trajectory information

. However

, s ome state agencies publish databases of UOG wells that contain the same type of data as the DI Desktop ® database ( e.g., well API number, formation, well trajectory )

, but are more up

- to

- date than the version of the DI Desktop ®
database that ERG used in this analysis. For these states, ERG used the published state agency databases instead of the DI Desktop ® database to maximize the number of usable results. For example, DI Desktop® contained no Utica shale wells because Utica well drilling ramped up in 2012 , after the last update to the version of the DI Desktop ® data that ERG is using , in late 2011

. However, the Ohio Department of Natural Resources publishes a running list of horizontal Utica

s hale wells, 140 of which matched up with FracFocus ® records. ERG used databases published by the following state agencies in this analysis:

 Ohio Department of Natural Resources (OH DNR) (DCN SGE00561)

 Oklahoma Geological Survey (OGS) (DCN SGE00694)

 Kansas Geological Survey (KGS) (DCN SGE00720)

 North Dakota Industrial Commission (NDIC) (DCN SGE00557)

 Louisiana Department of Natural Resources (LA DNR) (D C N SGE01024)

 Arkansas Oil and Gas Commission (AOGC) (DCN SGE01021)

32 ERG used the list of active oil and gas wells in the DI Desktop® database as identified by ERG in a separate analysis of the DI Desktop® dataset (DCN SGE 009 63). The version of the DI Desktop® database analyzed was last updated in 2012 and referred to data from 2011.Memorandum

March 31 , 2015 Page 21

Figure 2 . Overview of Sources Used for FracFocus ® Fracturing Fluid Volume Analysis

4.2.2 Method

s and Procedures

To estimate typical fracturing fluid volumes, ERG used the following procedure s :
Step 1 : Cross Reference FracFocus ® against DI Desktop ®

Using the queries des cribed in Section 4.2.3

, ERG linked the FracFocus ® database ( DCN SGE00724.A05 ) with the DI Desktop ® database using well API number. ERG excluded

w ells with “unknown” or blank well trajectories in the DI Desktop ® database from the results. The resulting table contains the data fields listed below and can be found in the Query Results from SGE00724.A05 tab in Attachment 4 (DCN SGE00724.A04 ). The Query Results from SGE00724.A05 tab is the output from the Microsoft Access database.

 API Number

 Formation

 Well trajectory ( i.e., horizontal, directional, vertical)

 Fracturing fluid volume (gallons) Step 2: Cross Reference FracFocus ® Database against State Age ncy D atabases

ERG identified six state agency databases with more up

- to

- date data than the version of the DI Desktop ® database that ERG used for this analysis

. Using queries in the FracFocus ® database ( DCN SGE00724.A05 ), ERG cross

- linked the FracFocus ® dat abaseMemorandum

March 31 , 2015 Page 22

with these state agency databases using well API number. The results of this cross reference override the results of the cross reference in Step 1 because, as explained in Section 4.2.1 , ERG determined that these state agency databases have more up

- to

- date data than the DI Desktop ® database. The Data Sources by State tab in Attachment 4 (DCN SGE00724.A04 ) indicates the state s for which ERG used a state agency data base instead of

, or in combination with

, the DI Desktop ® data base

. Table 4 contains more detail about the data contained in ea ch state agency database.

Step 3: Summary of Results

The Query Results from SGE00724.A05 tab i n Attachment 4 ( DCN SGE00724.A04 ) contains the resulting reco rds from the database portion of this analysis. These are the FracFocus ® database records with fracturing fluid volumes that ERG was able to link to U OG formation and well trajectory data from another database

. On a UOG formation and well trajectory basis, ERG calculated the 10 th percentile, 50 th percentile (i.e., median), and 90 th perc entile statistics of fracturing fluid volumes (gallons)

. ERG calculated the 10 th percentile and 90 th percentile ( as opposed to the minimum and maximum ) to remove outlying data points. The results for these calculations are shown in the Summary of Results t ab in Attachment 4 (DCN SGE00724.A04 ). ERG converted the volumes from gallons to barrels by dividing by 42 gallons per barrel. The total number of data points (i.e., number of wells ) 33 is also shown in this tab. ERG entered these results into the PW Data tab of Attachment 1 (DCN SGE00724.A01 ).

4.2.3 Attachment 5

– Query Descriptions

Table 4 describes the queries E RG used to analyze the FracFocus ® database in Attachment 5 (DCN SGE00724.A05 ). The results of the analysis are documented in Attachment 4 (DCN SGE00724.A04 ).

The following are the tables found in Attachment 5:

 ORD FF DB ( DCN SGE00585)

– This is the raw FracFocus database published by ORD (DCN SGE00585).

 ORD FF DB

- Manipulated

– This is a version of the FracFocus database published by ORD that ERG created by processing the queries listed in Table 4

.

 ORD FF DB

- Final

– This is the final version of the FracFocus database that ERG generated by processing the queries listed in Table 4

. This table is cop ied into the Query Results from SGE00724.A05 tab in Attachment 4.

 C onsolidated Formation Crosswalk

– Crosswalk of known basin and formation combinations in the DI Desktop® d atabase from ERG’s analysis of that database (DCN SGE00963).

33 In this analysis, the number of data points equals the number of wells.Memorandum

March 31 , 2015 Page 23

 HPDI_EXPORT_ 011012

– The raw DI Desktop® database (DCN SGE00520). DI Desktop was formerly known as HPDI, Inc.

 KS Horizontal Wells ( DCN SGE00720)

– List of wells published by the Kansas Geological Survey (KGS) that contains formation and well trajectory information by API number.

 ND Wells ( DCN SGE00557)

– List of wells published by NDIC that contains formation and well trajectory information by API number.

 OGS Woodford Permits ( DCN SGE00694)

– Thi s is a list of permitted Woodford shale wells published by OGS.

 Fayetteville Wells ( DCN SGE01021)

– This is a list of permitted Fayetteville shale wells published by AOGC.

 Haynesville Wells ( DCN SGE01024)

– This is a list of permitted Haynesville shale wells published by LA DNR.

 Utica Well Permits ( DCN SGE00561)

– This is a list of permitted Utica wells published by OHDNR

.

Table 4

. FracFocus ® Fracturing Fluid Volumes Query Descriptions

Query Query Description

000 This query makes a new table called " ORD FF DB

- Manipulated " and populates it with all records in EPA ORD’s FracFocus ® (DCN SGE00585 ) database flagged as "OK" in the field called "VolumeFFflag". When creating this new table, this query also creates a bla nk field nam ed API_ERG that is populated in subsequent queries.

100 This que ry update s the API_ERG field in the " ORD FF DB

- Manipulated " table to match the API field reported in FracFocus ® database ( DCN SGE00585)

. The API_ERG field is manipulated by queries 101 through 110 to a format that matches DI Desktop ® ( DCN SGE00520). For example, all API numbers in
FracFrocus are in the format: "##

- ###

- #####"

, but DI Desktop ® reports Arkansas API numbers with "

- 00

- 00" at th e end. States that are not included in queries 101 through 11 0 report API number in the
same format as FracFocus ®

. 101 Adds "

- 00

- 00 " to end of the API_ERG field for AR wells in the " ORD FF DB

- Manipulated " table

. 102 Adds "

- 00" to end of the API_ERG field for AL wells in the " ORD FF DB

- Manipulated " table

. 10 3 Adds "

- 00" to end of the API_ERG field for CO wells in the " ORD FF DB

- Manipulated " table

. 10 4 Adds "

- 00" to end of the API_ERG field for LA wells in the " ORD FF DB

- Manipulated " table

. 10 5 Adds "

- 00" to end of the API_ERG field for MS wells in the " ORD FF DB

- Manipulated " table

. 106 Adds "

- 00

- 00 " to end of the API_ERG field for MT wells in the " ORD FF DB

- Manipulated " table

. 107 Adds "

- 00" to end of the API_ERG field for UT wells in the " ORD FF DB

- Manipulated " table

. 108 Adds "

- 00" to end of the API_ERG field for TX wells in the " ORD FF DB

- Manipulated " table

. 109 Adds "

- 00" to end of the API_ERG field for WV wells in the " OR D FF DB

- Manipulated " table

. 110 Adds "

- 00" to end of the API_ERG field for NM wells in the " ORD FF DB

- Manipulated " table

.

200 This query makes a new table called " ORD FF DB

- Final " and cross

- referenc es all API numbers in FracFocus ® ( DCN SGE00585) against the raw DI Desktop ® data base . The resulting table includes allMemorandum

March 31 , 2015 Page 24

Table 4

. FracFocus ® Fracturing Fluid Volumes Query Descriptions

Query Query Description

of the FracFocus® database fields in addition to the following fields from the DI Desktop® database if a matching API number was found: Basin_DI

, Formation_DI , and Drill_Type_DI

. Wells without matches are still included in the new table but these fields are left blank. Empty fields are also created for Formation_ERG and Resource Type_ERG, which are populated in subsequent queries.

201 This query cross references the Basin_DI and Formati on_DI fields in the " ORD FF DB

- Final " table against the “Consolidated Formation Crosswalk” table a . For those records with matching basin and formations, this query updates the “Formation_ERG” field in the " ORD FF DB

- Final " with the common formation nam e in the “Consolidated Formation Crosswalk” table.

202 This query cross references the API numbers in the " ORD FF DB

- Final " table against a list of horizontal Utica shale wells published by OH DNR ( DCN SGE00561). If the API numbers in
FracFocus ® (DCN SGE00585) match API numbers in OH DNR (DCN SGE00561), this query updates the Formation_ERG, Drill Type_DI, and Recourse T ype _ERG fields in the “ ORD FF DB

- Final ” table to "Utica", "H" (based on OH DNR's file name, which is a list of horizontal wells ), and "shale" respectively.

203 This query cross references the API numbers in the " ORD FF DB

- Final " against a list of permitted Oklahoma shale wells published by OGS (DCN SGE00694). If the API numbers in FracFocus® (DCN SGE00585) match API numbers in OGS's shale list (DCN SGE00694), this query updates the Formation name, Drill Type, and Resource Type fields in the “ ORD FF DB

- Final ” table to "Woodford", "H", and "shale" respectively. This query only pulls wells from OGS's shale well list where the reported formation name includes "Woodford" and the lateral length is greater than zero.

204 This query cross references the API numbers in the " ORD FF DB

- Final " against a list of permitted horizontal Kansas wells published by the KGS (DCN SGE00720). If the API numbers in FracFocus ® (DCN SGE00585) match API numbers in KGS's list (DCN SGE00720), this query updates the Formation_ERG , Drill Type _DI , and Resource Type _ERG fields in the " ORD FF DB

- Final " table to "Mississippi Lime", "H" (based on KGS's file name, which is a list of horizontal wells), and "shale" respectively. This query only pulls wells from KGS's horizontal well list where the repo rted formation name includes "Mississippi".

205 This query cross references the API numbers in the " ORD FF DB

- Final " against a list of oil and gas wells in North Dakota published by NDIC (DCN SGE00557). If the API numbers in FracFocus ® (DCN SGE00585) match API numbers in NDIC's list (DCN SGE00557) t his query updates the Formation_ERG and Resource Type _ERG fields in the " ORD FF DB

- Final " table to "Bakken" and "shale" respectively. This query only pulls wells from NDIC's well list where the reported formation name includes "Bakken". This query also updates the Drill Type _ERG field in the “ ORD FF DB

- Final ” table to the reported value in th e w ellbore field (i.e., d rill type) in NDIC's list.

206 This query cross references the API numbers in the " ORD FF DB

- Final " against a list of oil and gas wells in Arkansas published by AOGC (DCN SGE01021) (see the “Fayetteville Wells” table ) . This query updates the Formation name and Resource Type fields in the " ORD FF DB

- Final " table to "Fayetteville" and "shale" respectively if the API numbers in FracFocus ® (DCN SGE00585) match API numbers in DCN SGE01021 and if the existing formation field in “ ORD FF DB

- Final ” was blank

.

207 This query cross references the API numbers in the " ORD FF DB

- Final " against a list of oil and gas wells in Louisiana published by LA DNR (DCN SGE0102 4 ) (see the “ Haynesville Wells ” table ) . This query updates the Format ion name and Resource Type fields in the " ORD FF DB

- Final " table to

" Haynesville " and "shale" respectively if the API numbers in FracFocus ® (DCN SGE00585) match API numbers in DCN SGE0102 4 and if the existing formation field in “ORD FF DB

- Final ” was blank

. 20 8 This query updates all null values in the “Drill Type_DI” field of the “ ORD FF DB

- Final ” table to

“ U ” (i.e., unknown).

20 9 This query updates all null values in the “ Formation_ERG ” field of the “ ORD FF DB

- Final ” table to

“ Unknown ”

.

2 10 This query updates all null values in the “ Resource Type_ERG ” field of the “ ORD FF DB

- Final ” table to “ Unknown ”

. These wells could be UOG wells where ERG could not identify a common formation name, COG wells, or CMB wells.Memorandum

March 31 , 2015 Page 25

Table 4

. FracFocus ® Fracturing Fluid Volumes Query Descriptions

Query Query Description

2 1 1 This query summarizes the final results. It includes counts of wells by Formation_ERG

, Drill Type_DI

, and Resource Type_ERG

.
a

— ERG created this crosswalk in a separate analysis where ERG assigned consolidated formation names to combinations of basins and formations reported in DI Desktop ® . More information about this analysis can be found in ERG’s Analysis of DI Desktop ® memorandum (DCN SGE00963).
The following subsections describe analyses that ERG completed using state or formation level data sets to g enerate data inputs to the PW Data tab in Attachment 1 (DCN SGE00724.A01 ) (see Section 1.2 ).

4.3 Attachment 6

– Bakken Flowback Recovery

ERG analyzed flowback recovery for UOG wells completed in the Bakken formation in North Dakota using data published by the NDIC (DCN SGE00557) and the results from ERG’s analysis of ORD’s FracFocus ® d ata (DCN SGE00724.A04 , DCN SGE00724.A05 ). ERG entered the results of this analysis as inputs to the PW Data tab in Attachment 1 (DCN SGE00724.A01 ). Attachment 6 (DCN SGE00724.A06 ) contains the underlying Microsoft Excel file for this analysis

.

4.3.1 Data Source

ERG obtained a subscription to NDIC’s Basic Subscription Services (DCN SGE 00557). Relevant data for this analysis that were provided in the NDIC dataset include the following :

 Well API number

 NDIC assigned “well file #” (used to search for wells in the NDIC database , see Section 4.3.2 )

 Monthly production of oil (barrels), gas ( million cubic feet, MCF), and produced water (barrels)

 Number of production days in each month 34

To obtain fracturing fluid volumes for this analysis, ERG used the results from the FracFocus ® Fracturing Fluid Volume analysis described in Section 4.1.3 (DCN SGE00724.A04

, DCN SGE00724.A05 ). Relevant data provided in the FracFoc us results included the following :

 Well API number

 Formation

 State

 W ell trajectory ( horizontal, vertical, or directional )

 Fracture Date (DD/MM/YYYY)

 Fracturing fluid volume (gallons)

34 The number of production days reported by NDIC is the number of days that the given well was producing any combination of oil, gas, and/or water in the given month.Memorandum

March 31 , 2015 Page 26

The well API number is the field ERG used to link the FracFocus ® database and NDIC’s database.

4.3.2 Method

s and Procedures

To estimate typical flowback recovery , ERG used the following procedures :
Step 1 : Identify Bakken Wells from FracFocus ® Analysis

ERG filtered the results from the FracFocus ® Fracturing Fluid Volume anal ysis for horizontal Bakken shale wells located in North Dakota (DCN SGE00724.A04

- .A5). ERG excluded vertical and directional wells from this analysis that were identified in FracFocus because there were a limited number of records

. Step 2: Identify Bakken Flowback Volumes in NDIC’s Production Data

ERG searched the NDIC production database for Bakken wells listed in the database from ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE00724.A04

- A5). For each well, ERG located the production data i n the NDIC database for the given month in which the well was completed according to the FracFocus ® database. ERG recorded the produced water volume and production days 35 in the “Estimated Flowback Volume (barrels) ” and “ Production Days ” fields

, respectively

, in the Analysis tab in Attachment 6 (DCN SGE00724.A06 ).

Literature reports that the flowback process lasts anywhere between 14 and 60 days (DCN SGE00951). During this analysis, ERG encountered some wells that produced
water for fewer days t han the general flowback process length reported in literature (e.g., 3 days) in the month the well was completed

. For all wells where the number of production days was less than 14 in the completion month , ERG recorded the volume for these days in additio n to the volumes for the entire next month of production. 36 For example, a well completed at the end of July 2011 only produced 1,000 barrels of produced water during 3 days of production by the end of the month. In August 2011, this well produced 5,000 bar rels of produced water during 31 days of production. ERG recorded 6,000 and 34 into the “Estimated Flowback Volume (barrels)” and “Production Days” fields respectively in the Analysis tab of Attachment 6 (DCN SGE00724.A06 ).

Step 3: Calculate Flowback Reco very
ERG calculated the flowback recovery as a percentage of total fracturing fluid volume using Equation 4 below. The flowback volume was obtained in Step 2 from the NDIC database. The total fracturing fluid volume was obtained from ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE007 24.A04

- A5).

35 The number of production days reported by NDIC is the number of days that the given well was producing any combination of oil, gas, and/or water in the given month.
36 ERG made this assumption in order to make the available data in literature useful for estimating flowback recovery for different UOG formations. The actual flowback recovery for individual wells may have been lower or higher than the recovery ERG estimated.Memorandum

March 31 , 2015 Page 27

Equation 4

Note: ERG converted flowback volume units using 42 gallons per barrel.

Step 4 : Summary of Resul ts

ERG calculated 10 th percentile, 50 th percentile, and 90 th percentile statistics for the flowback recovery for horizontal Bakken wells. ERG calculated the 10 th percentile and 90 th percentile as opposed to the minimum and maximum to remove outlying data points. The resulting statistics and total number of wells are shown in the Results tab of Attachment 6 (DCN SGE00724.A06 ). ERG entered these results into the PW Data tab of Attachment 1 (DCN SGE00724.A01 ). E RG also calculated the median numb er of production days associated with the flowback recovery statistics to verify it agrees with typical flowback process lengths reported in literature (i.e., between 14 and 60 days ) (DCN SGE00951)

. T he calculated flowback recovery statistics in this analy sis represent a median of 3 0 days of production, which falls within the general ranges of flowback process length reported in literature , and thus verifies the methods and procedures for this analysis

.

4.4 Attachment 7

– New Mexico Flowback Recovery

ERG analyz ed UOG flowback recovery for UOG wells completed in the Avalon and Bone Spring, Wolfcamp, and Dakota formations in New Mexico using data published by the New Mexico Energy, Minerals, and Natural Resources Department (NMEMNRD) (DCN SGE00644) along with resu lts from ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE00724.A04

- A5). ERG entered the results of this analysis as inputs to the PW Data tab in Attachment 1 (DCN SGE00724.A01 ). Attachment 7 (DCN SGE00724.A07 ) contains the underlying Microsoft Excel file.

4.4.1 Data Source

ERG obtained data from NMEMNRD Oil Conservation Division (DCN SGE00644). The online well search application allows users to obtain the following information for a specified well using the well API number:

 Monthly productio n of oil (barrels), gas (MCF), and produced water (barrels); and

 Number of production days in each month.

To obtain fracturing fluid volumes for this analysis, ERG used the results from the FracFocus ® Fracturing Fluid Volume analysis described in Section 4.1.3 (DCN SGE00724.A04

- A5). Relevant data in these results included the following :

 Well API number

 Formation

 State

 W ell trajector y ( horizontal, vertical, or direc tional)Memorandum

March 31 , 2015 Page 28

 Fracture Date (DD/MM/YYYY)

 Fracturing fluid volume (gallons)

The well API number is the common field ERG used to link the FracFocus ® database and NMEMNRD’s database.

4.4.2 Method

s and Procedures

To estimate typical flowback recovery , ERG used the follo wing procedures :
Step 1 : Identify New Mexico Wells from FracFocus ® Analysis

ERG filtered the results from the FracFocus ® Fracturing Fluid Volume analysis for wells located in New Mexico (DCN SGE00724.A04

- A5). This only included directional wells for the Av alon and Bone Spring, Wolfcamp, and Dakota formations

. There were no vertical and horizontal wells in this analysis because there were only directional UOG wells in New Mexico that were contained in the results of ERG’s FracFocus ® Fracturing Fluid Volume s analysis (DCN SGE00724.A04

- A5).

Step 2: Identify NMEMNRD Flowback Water Volumes

For each well identified in Step 1, ERG searched produced water volumes in the NMEMNRD database for the month in which the well was completed according to the FracFocus ® datab ase. ERG recorded the produced water volume and production days into the “ Flowback Volume (barrels) ” and “Flowback Days ” fields respectively in the Analysis tab of Attachment 7 (DCN SGE00724.A07 ).

Literature reports that the flowback process lasts anywhere between 14 and 60 days (DCN SGE00951). During this analysis, ERG encountered some wells that produced for fewer days than the general flowback process length reported in literature (e.g., 3 days) in the month the well was completed. For all wells where the number of production days was less than 14 in the completion month , ERG recorded the volume for these days in addition to the volumes for the entire next month of production. 37 For example, a well completed at the end of July 2011 only produ ced 1,000 barrels during 3 days of production by the end of the month. In August 2011, this well produced 5,000 barrels of produced water during 31 days of production. ERG recorded 6,000 and 34 into the “Estimated Flowback Volume (barrels)” and “Production Days” fields respectively in the Analysis tab of Attachment 7 (DCN SGE00724.A07 ).

Step 3 : Calculate Flowback Recovery

ERG calculated the flowback recovery as a percentage of total fracturing fluid volume using Equation 4 . The flowback volume was obtained in Step 2 from the NMEMNRD

37 ERG made this assumption in order to make the available data in literature useful for estimating flowback recovery for different UOG formations. The actual flowback recovery for individual wells may have been lower or higher than the recovery ERG estimated.Memorandum

March 31 , 2015 Page 29

database. The total fracturing fluid volume was obtained from ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE00724. A04

- A5).

Step 4 : Summary of Results

ERG calculated 10 th percentile, 50 th percentile, and 90 th percentile statistics of the flowback recovery for New Mexico wells. ERG calculated the 10 th percentile and 90 th percentile as opposed to the minimum and maximum to remove outlying data points. The results are shown in the Results tab of Attachment 7 (DCN SGE00724.A07 ). The total number of wells is also shown in this tab. ERG entered these results into the PW Data tab of Attachment 1 (DCN SGE00724.A01 ). ERG also ca lculated the median number of production days associated with the flowback recovery statistics to verify it agrees with typical flowback process lengths reported in literature (i.e., between 14 and 60 days) (DCN SGE00951). T he calculated flowback recovery statistics in this analysis represent a median of 30 to 31 days of production

, depending on the formation, which falls within the general ranges of flowback process length reported in literature , and thus verifies the methods a nd procedures for this analysis

.

4.5 Attachment 8

– Utica Flowback Recovery and Long

- term Produced Water Rates

ERG analyzed flowback recovery and long

- term produced water generation rates for UOG wells completed in the Utica formation in Ohio using data publis hed by the OH DNR along with ORD’s FracFocus ® database (DCN SGE00 585 ). 38 ERG used this analysis to esti mate long

- term produced water generation rates because there were limited Utica wells in the DI Desktop ® database, which is the database ERG used to estim ate long

- term produced water for most other UOG formations. ERG entered the results of this analysis as inputs to the PW Data tab in Attachment 1 (DCN SGE00724.A01 ). Attachment 8 (DCN SGE00724.A08 ) contains the underlying Microsoft Excel file for this analysis

.

4.5.1 Data Source

ERG obtained data from the OH DNR Quarterly Production Archive (DCN SGE00559 and DCN SGE00560) for shale production. ERG downloaded Microsoft Excel files from OH DNR’s website that contain oil, gas, and produced water produc tion on a quarterly or annual basis. 39 ERG downloaded the following files:

38 Section 4.5.1 explains why ERG used the raw ORD FracFocus database instead of ERG’s analysis of ORD’s FracFocus database.
39 P roduction data for 2013 and 2014 (i.e., previous and current years ) is provided in quarterly files ; production data for 2011 and 2012 (i.e., his toric data) is provided for the entire year.Memorandum

March 31 , 2015 Page 30

 2011 Utica Shale Production

– DCN SGE00559 ( 2011 Prod (SGE00559) tab in Attachment 8, DCN SGE00724.A08 ).

 2012 Utica Shale Production

– DCN SGE0056 0 ( 2012 Prod (SGE00560) tab in Attac hment 8, DCN SGE00724.A08 ).

 2013 Quarterly Horizontal Shale Production: 1st Quarter

– DCN SGE0069 4 ( 2013 Prod 1Q (SGE00694) tab in Attachment 8, DCN SGE00724.A08 ).

 2013 Quarterly Horizontal Shale Production: 2nd Quarter

– DCN SGE00695 ( 2013 Prod 2Q (SGE006 95) tab in Attachment 8, DCN SGE00724.A08 )

.

 2013 Quarterly Horizontal Shale Production: 3rd Quarter

– DCN SGE00727 ( 2013 Prod 3Q (SGE00727) tab in Attachment 8, DCN SGE00724.A08 )

.

 2013 Quarterly Horizontal Shale Production: 4th Quarter

– DCN SGE00737 ( 2013 4Q Prod (SGE00737) tab in Attachment 8, DCN SGE00724.A08 )

.

Each file reports the following data :

 Well API number

 Quarterly or annual oil (barrels), gas (t housand cubic feet of gas ), and produced water production (barrels) 40

 Number of production days in ea ch quarter or year.

To obtain fracturing fluid volumes for this analysis, ERG used ORD’s FracFocus ®
database described in Section 1.1 (DCN SGE00 585 ). Relevant da ta from these results included the following :

 Well API number

 State

 Fracture Date (DD/MM/YYYY)

 Fracturing fluid volume (gallons)

The well API number is the common field ERG used to link the FracFocus ® database to OH DNR’s production data. Note that the production files published by OH DNR indicate that all Utica wells listed are horizontally drilled.

4.5.2 Method

s and Procedures

To estimate typical flowback recovery and long

- term produced water rates, ERG used the following procedures :

40 In these reports, OH DNR refers to produced water as "brine" which includes both flowback and long

- term produced water.Memorandum

March 31 , 2015 Page 31

Step 1: I dentify Ohio Wells from FracFocus ® Analysis

ERG filtered ORD’s FracFocus ® d atabase (DCN SGE00 585 ) for all well records in Ohio.

Step 2: Identify OH DNR Flowback Volumes

For each well identified in Step 1, ERG searched produced water volumes in the OH DNR data for the first month of production . ERG recorded the produced water volume and production days into the “Flowback Volume (barrels)” and “Flowback Days” fields respectively in the Analysis tab of Attachment 8 (DCN SGE00724.A08 ).

Table 5 explains in more detail how ERG identified flowback volumes; this method varied by the completion year and/or by the quarter the well first produced oil or gas, or generated produced water. Literature reports that the flowback process lasts between 14 and 60 days (DCN SGE00951). F or the purpose of this analysis

, ERG assumed a maximum of 60 days of production to identify wells in the flowback phase

. If the re were more than 60 p roduction days during the first reporting period, ERG did not calculate flowback recovery for the well. 41 Further, some wells may have produced for less than 2 weeks in the first production period

, so the flowback recovery (calculated in next step) may be a n underestimate.

Table 5

. Calculation Methods Used for Each “First Production Period”

First Production Period for Well Calculation of Flowback Recovery (% of Fracturing Fluid Volume

2011 If the number of 2011 production days is less than 60 days, E RG divided the 2011

brine production by the fracturing fluid volume. a

2012 If the number of 2012 production days is less than 60 days, E RG divided the 2012

brine production by the fracturing fluid volume. a

2013

– 1 st Quarter If the number of 1 st quarter 2013 production days is less than 60 days, E RG divided

the 1 st quarter 2013 brine production by the fracturing fluid volume. a

2013

– 2 nd Quarter If the number of 2 nd quarter 2013 production days is less than 60 days, E RG divided

the 2 nd quarter 2013 brine production by the fracturing fluid volume. a

2013

– 3 rd Quarter If the number of 3 rd quarter 2013 production days is less than 60 days, E RG divided

the 3 rd quarter 2013 brine production by the fracturing fluid volume. a

2013

– 4 th Quarter If the number of 4 th quarter 2013 production days is less than 60 days, E RG divided

the 4 th quarter 2013 brine production by the fracturing fluid volume. a

a

— If the production days was greater than 60 days during the first reporting period, ERG did not calculate flowback recovery for the well.
Step 3 : Calculate Flowback Recovery

ERG calculated the flowback recovery as a percentage of total fracturing fluid volume using Equation 4 . The flowback volume was obtained in Step 2 from the OH DNR data. The total fracturing fluid volume was obtained from ORD’s FracFocus ® database (DCN SGE00585) for all well records in Ohio.

41 ERG used a slightly different approach from other analyses in Section 4.0 because the data published by OHDNR is organized on a quarterly basis, not monthly.Memorandum

March 31 , 2015 Page 32

Step 4 : Identify OH DNR Long

- Term Produced Water Volumes and Calculate Long

- Term Produced Water Rates

ERG calculate d long

- term produced water rates using Equation 5 ; all inpu ts were from OH DNR’s production data. Table 6 explains in more detail how ERG identified and calculated long

- term produced water volumes

, which varied by the year an d/or quarter the well first produced oil, gas, or produced water

. In addition, ERG did not calculate long

- term produced water rates for wells that had intermittent production.

Equation 5

Where: LTPW

– l ong t erm p roduced w ater

Table 6 . Calculation Methods Used for Each “First Production Period”

First Production Period for Well Calculation of Long

- term Produced Water (barrels per day per well )

2011 E RG assumed that wells that first produced in 2011 were in the production phase in 2012 and

2013 and only generated long

- term produced water in 2012 and 2013. ERG divided the total 2012 and 2013 brine production by the total 2012 and 2013 production days. a

2012 E RG assumed that wells that first produced in 2012 were in the production phase by the 2 nd

quarter of 2013 and only generated long

- term produced water in the 2 nd

, 3rd and 4th quarter of 2013. ERG divided the total 2 nd

, 3rd and 4th quarter 2013 brine production by the total 2 nd , 3 rd and 4 th 2013 production days.

2013

– 1 st Quarter E RG assumed that wells that first produced in 1 st quarter 2013 were in the production phase

during 3 rd and 4 th quarter 2013 . ERG divided the total 3 rd and 4 th quarter 2013 brine production by the total 3 rd and 4 th quarter 2013 production days.

2013

– 2 nd Quarter E RG assumed that wells that first produced in 2 nd quarter 2013 were in the production phase

during 4 th quarter 2013 . ERG divided the total 4 th quarter 2013 brine production by the total 4 th quarter 2013 pr oduction days.

2013

– 3 rd Quarter ERG did not calculate long

- term produced water rates for wells that first produced in 3 rd quarter

2013 because we did not have the produced water volume data for the time period in which these wells were producing (i.e., 2014

– 1 st Quarter)

. 2013

– 4 th Quarter ERG did not calculate long

- term produced water rates for wells that first produced in 4 th quarter

2013 because we did not have the produced water volume data for the time period in which these wells were producing ( i.e., 2014

– 2 nd Quarter).

a

—unlike the procedures for 2012, ERG used the 2012 annual volumes here because quarterly data are not available for 2012.
Step 5: Summary of Results

ERG calculated the 10 th percentile, 50 th percentile, and 90 th percentile statistics of the flowback recovery and long

- term produced water. ERG calculated the 10 th percentile and 90 th percentile

, as opposed to the minimum and maximum

, to remove outlying data points. The results are shown in the Results tab of Attachm ent 8 (DCN SGE00724.A08 ). ERG entered these results into the PW Data tab of Attachment 1 under the horizontalMemorandum

March 31 , 2015 Page 33

Utica well category 42 (DCN SGE00724.A01 ). ERG also calculated the median number of production days associated with the flowback recovery statistics to verify it agrees with typical flowback process lengths reported in literature (i.e., between 14 and 60 days) (DCN SGE00951). T he calculated flowback recovery statistics in this analysis represent a median of 16 days of production, which falls within th e general ranges of flowback process length reported in literature.

4.6 Attachment 9

– Niobrara Long

- term Produced Water Rates

ERG analyzed long

- term produced water rates generated by UOG wells completed in the Niobrara formation in Colorado using data publish ed by the Colorado Oil and Gas Conservation Commission (COGCC) (DCN SGE00518). ERG used this analysis to estimate long

- term produced water generation rates because there were limited Niobrara wells in the DI Desktop ® database, which is the database ERG use d to estimate long

- term produced water for most other UOG formations. ERG entered the results of this analysis as inputs to the PW Data tab in Attachment 1 (DCN SGE00724.A01 ). Attachment 9 (DCN SGE00724.A09 ) contains the underlying Microsoft Excel file.

4.6.1 Data Source

ERG obtained the following data from COGCC Production Data Inquiry (DCN SGE00518). The website allows users to query annual oil, gas, and produced water production data in several different ways.

 Well API number

 Production year

 Annual producti on of oil (barrels), gas (MCF), and produced water (barrels)

4.6.2 Methods and Procedures

To estimate long

- term produced water rates, ERG used the following procedures:

Step 1: Identify Niobrara Wells from COGC C

ERG queried COGC C ’s production database “by well” with the following criteria:

 Production from 2000 to 2014

 G eolog ical field number 16950 (i.e., Niobrara horizontal)

ERG assumed all production data in the results were from wells drilled horizontally d ue to the naming convention of the geological field b y COGCC (i.e., Niobrara horizontal).

42 OH DNR named some of the published production files “Utica” production and others “horizo ntal shale” production. ERG assumed that all of the wells are horizontal wells completed in the Utica formation for the purpose of this analysis.Memorandum

March 31 , 2015 Page 34

Step 2: Assign Well Completion Years

ERG copied the raw data from the search in S tep 1 into the Raw Dat a tab in Attachment 9 (DCN DGE00724.A9) and performed the following analyses :

 Sorted well records by ascending API n umber and then by year.

 Flagged all wells as “inactive” in the “ Production Year_ERG ” column if the well produced zero gas, oil, and /or water during that year

.

 Assigned each well a completion year equal to the smallest value in the

“ Production Year_ERG ” col umn. 43 ERG did not include y ears that were flagged as inactive as a completion year.

Step 3 : Calculate Niobrara Produced Water Volumes

In th e Analysis and Results tab in Attachment 9 (DCN SGE00724.A09 ), ERG summed produced water volumes for each completion year. ERG also counted the number of wells represented in each completion year.

Step 4: Calculate Niobrara Long

- term Produced Water Rate

In th e Analysis and Results tab in Attachment 9 (DCN SGE00724.A09 ), ERG calculated long

- term produ ced water rates for each completion year using Equation 6 below, where the annual LTPW volume excludes the produced water generated during the well completion year (WC Y) and the number of years does not include the well completion year (in order to exclude flowback volumes). Further, ERG assumed that all wells generated long

- term produced water for 365 days per year after the well completion year

. Equation 6

Where: LTPW

– l ong t erm p roduced w ater WCY

– well completion year

Step 5 : Summary of Results

ERG calculated the 10 th percentile , 50 th percentile , and 90 th percentile statistics for long

term produced water rates in the Analysis and Results tab of Attachment 9 (DCN SGE00724.A09 ). ERG calculated the 10 th percentile and 90 th percentile ( as opposed to the minimum and maximum ) to remove outlying data points. ERG also compiled t he total

43 The COGCC requires all operators to report monthly oil, gas, and water production beginning in 1999. Therefo re, assuming that the first year a well reported production is equivalent to the well completion year is appropriate for this analysis.Memorandum

March 31 , 2015 Page 35

number of wells (i.e., data points) in this tab. ERG entered these results into the PW Data tab of Attachment 1 (DCN SGE00724.A01 ).

4.7 Attachment 10

– Wyoming Flowback Recovery

ERG analyzed UOG flowback recovery for UOG wells completed in the Niobrara, Mesaverde, and Lance formations in Wyoming using data published by the Wyoming Oil and Gas Conservation Commission (WOGCC) (DCN SGE00643) along with results from ERG’s analysis of FracFocus ® Data (DCN SGE00724.A04

- A5). ERG entered the results of this analysis in to the PW Data tab in Attachment 1 (DCN SGE00724.A01 ). Attachment 10 (DCN SGE00724.A01 0) contains the underlying Microsoft Excel file.

4.7.1 Data Source

ERG obtained data from the WOGCC Download Production tool (DCN SGE00643). This tool allows users to download the following information for a group of API numbers in Microsoft Excel format:

 Monthly production of oil (barrels), gas (MCF), and produced water (barrels)

 Number of produ ction days in each month

To obtain fracturing fluid volumes for this analysis, ERG used the results from the FracFocus ® Fracturing Fluid Volume analysis described in Section 4.1.3 (DCN SGE00724.A04

- A5). Relevant data in these results included the following :

 Well API number

 Formation

 State

 Well trajectory ( horizontal, vertical, or directional)

 Fracture Date (DD/MM/YYYY)

 Fracturing fluid volume (gallons)

The well API number is the common field ERG used to link the FracFocus ® database and WOGCC’s database.

4.7.2 Methods and Procedures

To estimate typical flowback recovery , ERG used the following procedures :
Step 1: Identify UOG Wells in the FracFocus ® Database

ERG filtered the results from the FracFocus ® Fracturing Fluid Volume analysis for all UOG wells located in Wyoming (DCN SGE00724.A04

- A5). ERG searched the WOGCC database for this list of well API numbers using the “ Download Production ” feature o n the WOGCC website. ERG downloaded t he results in Microsoft Excel format and copied them into the Analysis tab of Attachment 10 (DCN SGE00724.A01 0).Memorandum

March 31 , 2015 Page 36

Step 2: Identify Flowback Water Volumes in WOGCC’s Production Data

For each well identified in Step 1 , ERG located th e production data in the WOGCC database for the month that well was completed according to the FracFocus ® database. ERG identified the produced water volume and production days during flowback in the Raw Data tab and recorded them in the “ Flowback Volume ( barrels) ” and “Flowback Days ” fields respectively in the Analysis tab of Attachment 10 (DCN SGE00724.A01 0).

Literature reports that the flowback process lasts anywhere between 14 and 60 days (DCN SGE00951). During this analysis, ERG encountered some wells that produced for fewer days than the general flowback process length reported in literature (e.g., 3 days) in the month the well was completed. For all wells where the number of production days was less than 14 in the completion month , ERG recorded the v olume for these days in addition to the volume for the entire next month of production. 44 For example, a well completed at the end of July 2011 only produced 1,000 barrels during 3 days of production by the end of the month. In August 2011, this well produc ed 5,000 barrels of produced water during 31 days of production. ERG recorded 6,000 and 34 into the “Estimated Flowback Volume (barrels)” and “Production Days” fields respectively in the Analysis tab of Attachment 10 (DCN SGE00724.A01 0 ).

Step 3 : Calculate Flowback Recovery

ERG calculated the flowback recovery as a percentage of total fracturing fluid volume using Equation 4

. The flowback volume was obtained in Step 2 a bove from the WOGCC database. The total fracturing fluid volume was obtained from ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE00724.A04

- A5).

Step 2: Summary of Results

ERG calculated 10 th percentile, 50 th percentile (i.e., median), and 90 th percentile statistics of the flowback recovery by Wyoming wells. ERG calculated the 10 th percentile and 90 th percentile as opposed to the minimum and maximum to remove outlying data points. The results are shown in the Results tab of Attachment 10 (DCN SGE00724.A01 0). The total number of wells is also shown in this tab. ERG entered these results into the PW Data tab of Attachment 1 (DCN SGE00724.A01 ). ERG also calculated the median number of production days associated with the flowback recovery statistic s to verify it agrees with typical flowback process lengths reported in literature (i.e., between 14 and 60 days) (DCN SGE00951). T he calculated flowback recovery statistics in this analysis represent a median of 26 to 31 days of production depending on the formation, which falls within the general ranges of flowback process length reported in literature and thus verifies the methods and procedures for this analysis

.

44 ERG made this assumption in order to make the available data in literature useful for estimating flowback recovery for different UOG formations. The actual flowback recovery for individual wells may have been lower or higher than the recovery ERG estimated.Memorandum

March 31 , 2015 Page 37

4.8 Attachment 11

– Wattenberg Flowback Recovery and Long

- term Pr oduced Water

Rates

ERG analyzed produced water volumes and rates for UOG wells completed in the Wattenberg field (i.e., primarily Codell

- Niobrara formation) using data generated by Bing Bai in 2013 (DCN SGE00501). The u nderlying data and results are shown in the Analysis tab of Attachment 11 (DCN SGE00724.A01 1). ERG entered the results of this analysis into the PW Data tab of Attachment 1 (DCN SGE00724.A01 ).

4.8.1 Data Source

ERG used data from an article published in the Journal of Petroleum Science and Engineer ing by Colorado State University researcher Bing Bai in 2013 (DCN SGE00501) to estimate flowback recovery and long

- term produced water rates for the Codell

- Niobrara tight gas formation in the Denver Basin (DCN SGE00501). This article summarizes production data trends for wells completed in the J Sandstone, Codell Sandstone, Niobrara, Hygiene Sandstone, and Terry Sandstone formations

. Based on engineering judgment and EIA’s tight gas map (DCN SGE00155), ERG assumed these to be the "Codell

- Niobrara" formation

. More specifically, the article provides equations that estimate produced water rates as a function of time after completion based on production data from 1 ,677 vertica l wells and 32 horizontal wells.

4.8.2 Methods and Procedures

ERG performed the following steps to estimate flowback recovery and long

- term produced water rates using the equations provided in Bai ( 2013 ) (DCN SGE00501)

. Step 1: Flowback Rates for Horizontal Wells

ERG calculated f

lowback rates over the first 60 days of production for a typical horizontal well using Equation 7 (shown as Equation 2 in DCN SGE00501)

. As reported by Bai, 2013, Equation 7 estimates produced water flow rate as a function of days after completion and is only valid for the first 60 days of production (DCN SGE00501 ).

Equation 7

Where:
q = flow rate

, barrels per day
t = time since completion , days
Step 2: LTPW Rates for Horizontal Wells

ERG calculated long

- term produced water rates over 13 years of production for a typical horizontal well using Equation 8 below (shown as Equation 3 in DCN SGE00501)

. As reported by B ai, Equation 8 calculates produced water flow rate as a function of days after completion and is only valid aft er the first 60 days of production

, up to 13 years of production (DCN SGE00501 )

.Memorandum

March 31 , 2015 Page 38

Equation 8

Where:
q = flow rate

, barrels per day
t = time since completion , days
Step 3 : LTPW Rates for Vertical Wells

ERG calculated long

- term produced water rates over 13 years of production for a typical vertical well using Equation 9 below (shown as Equation 1 in DCN SGE00501). As reported by Bai, Equation 9 calculates produced water flow rate for vertical wells as a function of days after completion and is only valid after the first 60 days of production

, up to 13 years of production (DCN SGE00501)

. Equation 9

Where:
q = flow rate

, barrels per day
t = time since completion , days
Step 4: Summary of Results

ERG calculated 10 th percentile, 50 th percentile, and 90 th percentile statistics of the long

term produced water rates separately for ho rizontal and vertical wells. ERG calculated the 10 th percentile and 90 th percentile ( as opposed to the minimum and maximum ) to

remove outlying data points. For horizontal wells only

, 45 ERG also calculated the flowback rates over the first 30 days of production to estimate total flowback volume

. 46 ERG presents the results in the Results tab in Attachment 11 (DCN SGE00724.A01 1). ERG also presents t he total number of wells in this tab. ERG entered these results into the PW Data tab of Attachment 1 (DCN SG E00724.A01 ).

4.9 Attachment 12

– Niobrara Flowback Recovery

ERG estimated flowback recovery for UOG wells completed in the Niobrara formation in Colorado using data published by the Colorado Oil and Gas Conservation Commission (COGCC) (DCN SGE00518) along with results from ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE00724.A04

- A5). ERG entered the results of this analysis as inputs to the PW Data tab in Attachment 1 (DCN SGE00724.A01 ). Attachment 12 (DCN SGE00724.12) contains the underlying Mic rosoft Excel file.

45 Bai (2013) only provided an equation for flowback for horizontal wells.
46 Literature reports that the flowback pro cess lasts anywhere between 14 and 60 days

. (DCN SGE00951).Memorandum

March 31 , 2015 Page 39

4.9.1 Data Sources

ERG obtained data from COGCC (DCN SGE00518). The online well search application allows users to obtain the following information for a specified well using the well API number:

 Monthly production of oil (barrels), gas (MCF), and produced water (barrels)

 Number of production days in each month

To obtain fracturing fluid volumes for this analysis, ERG used the results from the FracFocus ® Fracturing Fluid Volume analysis described in Section 4.1.3 (DCN SGE00724.A04

- A5). Relevant data in these results included the following :

 Well API number

 Formation

 State

 Well trajectory ( horizontal, vertical, or directional)

 Fracture Date (DD/MM/YYYY)

 Fracturing fluid volume (gallons)

The well API number is the common field ERG used to link the FracFocus ® database and COGCC’s database.

4.9.2 Methods and Procedures

Step 1: Identify Colorado Wells from FracFocus ® Analysis

ERG filtered the results from the FracFocus ® Fracturing Fluid Volume analysis for all UOG wells located in Colorado (DCN SGE00724.A04

- A5).

Step 2: Identify UOG Flowback Volumes in COGCC’s Production Data

ERG searched COGCC’s production database for individual UOG wells listed in the filtered results (from Step 1) in ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE00724.A04

- A5). For each well, ERG located the production data in the COGCC database for the month that well was completed

, according to the FracFocus ®
data base. ERG recorded the produced water volume and production days into the “Estimated Flowback Volume (barrels) ” and “ Production Days ” fields

, respectively

, in the Analysis tab of Attachment 12 (DCN SGE00724.A01 2).

Literature reports that the flowback proc ess lasts anywhere between 14 and 60 days (DCN SGE00951). During this analysis, ERG encountered some wells that produced for fewer days than the general flowback process length reported in literature (e.g., 3 days) in the month the well was completed. For all wells that had fewer than 14 production days in the completion month , ERG recorded the volume for these days in addition to theMemorandum

March 31 , 2015 Page 40

volumes for the entire next month of production. 47 For example, a well completed at the end of July 2011 only produced 1, 000 barrels during 3 days of production by the end of the month. In August 2011, this well produced 5,000 barrels of produced water during 31 days of production. ERG recorded 6,000 and 34 into the “Estimated Flowback Volume (barrels)” and “Production Days” fields respectively in the Analysis tab of Attachment 12 (DCN SGE00724.A01 2 ).

Step 3 : Calculate Flowback Recovery

ERG calculated the flowback recovery as a percentage of total fracturing fluid volume using Equation 4 . The flowback volume was obtained in Step 2 above from the COGCC database. The total fracturing fluid volume was obtained from ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE00724.A04

- A5).

Step 4: Summary of Results

ERG calculated 10 th percentile, 50 th percentile, and 90 th percentile statistics of the flowback recovery by formation and well trajectory

. ERG calculated the 10 th percentile and 90 th percentile ( as opposed to the minimum and maximum ) to remove outlying data points. The results are shown in the Results tab of Attachment 12 (DCN SGE00724.A01 2). The total number of wells is also shown in this tab. ERG entered these results into the PW Data tab of Attachment 1 (DCN SGE00724.A01 ). ERG also calculated the median number of production days associated with the flowback recovery statistics to ve rify it agrees with typical flowback process lengths reported in literature (i.e., between 14 and 60 days) (DCN SGE00951). The calculated flowbac k recovery statistics in this analysis represent a median of 2 9 to 30 days of production depending on the well trajectory , which falls within the ranges of flowback process length reported in literature , and thus verifies the method s used for this analysis

.

N ATIONAL L

EVEL UOG P

RODUCED W

ATER C HARACTERIZATION A NALYSES
The following subsections describe analyses that ERG completed using national

- level datasets to generate data inputs to the UOG Wastewater Characterization Database in Attachment 14 (DCN SGE00724.A01 4 ) (see Section 3.0 )

.

4.10 USGS Data Used for UOG Produced Water Constituent Characterization

The following subsections describe the analysis that ERG comp leted using a national

level produced water characterization dataset published by USGS. The analyses and underlying data appear in Attachments 15 and 16 (DCN SGE00724.A01 5

- .A16).

4.10.1 Data Source

The USGS Produced Water Geochemical Database v. 2.0 (PROVISIONAL) (USGS database) contains geochemical and other information for produced waters from both

47 ERG made this assumption in order to make the available data in literature useful for estimating flowback recovery for different UOG formations. The actual flowback recovery for individual wells may have been lower or higher than the recovery ERG estimated.Memorandum

March 31 , 2015 Page 41

conventional and unconventional well types (DCN SGE00956) . The database is a compilation of 25 individual databases, publications, or reports . ERG used the USGS datab ase to obtain produced water constituent data to include in the UOG Wastewater Characterization Database in Attachment 14 (DCN SGE00724.A01 4).

ERG obtained data from the USGS d atabase from the USGS website on August 8, 2014 and aggregated the data for incl usion in the “ Raw Data 3

- USGS Data ” table in the “ UOG Wastewater Characterization ” database in Attachment 14 ( DCN SGE00724.A01 4 ). The “USGS National Produced Waters Geochemical Database v. 2

. 0 (PROVISIONAL)

– Documentation” file (DCN SGE00956) provides additional background about this database and defines all of the fields within the tables in the database.

4.10.2 Method

s and Procedures

ERG performed the following steps to analyze the USGS data :
Step 1: Extract Relevant Data

ERG imported the USGS data into the “USGS Raw Data” table in ERG’s USGS Produced Waters database in Attachment 16 (DCN SGE00724.A01 6)

, extracted entries where the well type was shale and/ or tight

, then deleted entries from references that were already included in the UOG Wastewater Characte rization database , based on the citation s listed for each entry in the USGS database

.
Step 2: Compile Unique List of Wells and Assign Well IDs

ERG compiled a list of unique wells, based on the following USGS database fields: original database/reference, basin, formation, well name , and well type

. ERG assigned

e ach unique well in the extracted dataset from Step 1 a “ Well ID ” that was used to aggregate constituent data by well.

Step 3 : Calculate Medians

Because Microsoft Access does not support median calculations, ERG exported the “USGS Temp” table in Attachment 16 ( DCN SGE00724.A01 6) into the USGS Data tab in Attachment 15 ( DCN SGE00724.A01 5 ) . Within Attachment 15 , ERG first removed any negative values 48 in the USGS Data_Neg Values Removed tab . ERG then used Excel functions to calculate the median values for each unique Well ID and Parameter in a crosstab format on the Median Summary tab in Attachment 15

. Finally, ERG manually removed any Parameters that did not have values for any of the wells in the Median Summary_Del Blank Col tab.

48 ERG identified some negative values in the data that referred to numeric codes (e.g., “

- 3=NA, not analyzed, unknown”). ERG also identified non

- coded negative values in the data that referred to actual data values. ERG was unable to find an explanation of these values. These non

- coded negative values only accounted for 0.2 percent of the full dataset; ERG excluded these non

- coded negative values from the analysis because they were difficult to interpret and their exclusion should not have an impact on the results.Memorandum

March 31 , 2015 Page 42

Step 4: “Un

- Crosstab” Data

ERG exported the results of the Median Summary_Del Blank Col tab from Attachment 15 ( DCN SGE00724.A01 5) into the “USGS Median Summary Data (from Excel)” table in Attachment 16 ( DCN SGE00724.A01 6)

. Because the Excel results were in a crosstab

type format where the parameter names were store d in the column headings, ERG created union queries 49 to pull the re sults of each column into a single table with three columns containing Well ID, Parameter, and Median Value. ERG also performed a similar type of “un

- crosstab” 50 process on the “USGS_Temp” table in Attachment 16 (DCN SGE00724.A01 6) to make the data more usa ble in Step 5

. Step 5: Compile Min, Max, and Median Data

From the “un

- crosstabbed” full data set, ERG queried the true (non

- media n ) min imum and maximum values for each unique Well ID and Parameter and added them to a final table. ERG added the median val ues based on the data in the “un

- crosstabbed” median table. Lastly, the final table was formatted for export into the UOG Wastewater Characterization database.

4.10.3 Attachment

s 15 and 16

– Query Descriptions

Table 7 describes the queries and their results used to perform the analyses in Attachment s 1 5 and 16 (DCN SGE00724.A01 5 and A16 ).

Table 7

. USGS Produced Water Database: Query Descriptions

Query(s) Query Description Relevant Memorandum Attachment 000 Initialize d [USGS_Temp] table

.

1 6 001 A ppended the entries from the entire set of [USGS Raw Data] into [USGS_Temp],

where the well type was “shale gas” or “tight”

. 002 Removed entries from [USGS_Temp] (Hayes and NYSDEC), which were already

included in the TDD database

. 100 Initialize d [List of Wells] table

. 101 Extracted all unique combinations of IDDB, REFERENCE, BASIN, FORMATION,

DFORM, WELL, and WELLTYPE and appen ded to [List of Wells]. WellID was auto numbered to create a list of all unique wells. 102 Linked [USGS_Temp] table to [List of Wells] table by IDDB, REFERENCE, BASIN,

FORMATION, DFORM, WELL, and WELLTYPE , and updated [USGS_Temp].[WellID] to be equal to [List of Wells].[WellID]. This query assigned WellID values in the [USGS_Temp] table. 200 Exported [USGS_Temp] to Excel (USGS_Median Data.xlsx, USGS Data tab)

. 1 5 51

49 Union queries combine the results of several similar select queries.
50 The “un

- crosstab” process refers to the process of translating data from columns into rows.
51 Attachment 15 (D CN SGE00724.A01 5) is an Excel attachment in which ERG completes the median calculations that cannot be performed in the Access database in Attachment 16 (DCN SGE00724.A01 6). Attachment 16 lists Query 200 as a placeholder entry for the step in which ERG exp orts the data to Excel to perform these median calculations.Memorandum

March 31 , 2015 Page 43

Table 7

. USGS Produced Water Database: Query Descriptions

Query(s) Query Description Relevant Memorandum Attachment “USGS_Data_Neg Values Removed” tab: Referenced “USGS Data” tab and only pulled non

- negative values. “Median Summary” tab: Created a table with WellID row headers and Parameter column headers. Array equations calculate the median value for each combination of WellID and Parameter. “Median Summary_Del Blank Col” tab: Manually removed Parameter columns with no data, for easier handling in the Access file. Imported “Median Summary_Del Blank Col” tab into Access as [USGS Median Data (from Excel)]

. 300 Initialize d [Median Summary] table

.

1 6 301a

, 302a Created a union query to pull [WellID] and median value for each Parameter. The text

for the union query was created by making a list of Parameters in Excel, and then creating an equation template to crea te each line of text. A single union query was too large for Access to handle; therefore it was split into two separate queries. This query converts the data from a crosstab type query (WellID row headers and Parameter column headers) into a table with ind ividual line entries for each Well ID, Parameter, and Median Value. 301b

, 302b A ppend ed the results of 301a and 302a into [Median Summary] table

. 400 Initialize d [All Parameter Data] table

. 401a

, 402a

, 403a

, 404a Similar to 301a and 302b above, except it uses all data from [USGS_Temp]

.

401b

, 402b A ppend ed the results of 401a through 404a into [All Parameter Data] table

. 500 Initialize d [USGS Data for Export] table

501a Summarize d Min, Max, and Number of Data Points for all values in [All Parameter

Data] table

. 501b Append ed well information and results of 501a into [USGS Data for Export] table.

502 Update d query to update [USGS Data for Export] with median data from [Median

Summary]

. 503 Delete d min and max in [USGS Data for Export] if there is only one data point

. 504 Standardize d the format for easy import in to a separate TDD database: Add ed

reference to USGS, 2014; set all WW Descriptions to “Produced”, etc.

4.11 ORD Data Used for UOG Wastewater Constituent Characterization

The following subsections describe the analysis that ERG completed using a national

level produced water characterization dataset from EPA that was compiled from the public docket for EPA ORD ’s Study of the Potential Impacts of Hydraulic Fracturing on Drin king Water Resources: Progress Report (Docket ID: EPA

- HQ

- ORD

- 2010

- 0674 ) . The analyses and underlying data are contained in Attachment 1 7 (DCN SGE00724.A01 7 ) and the QC procedures are described in Section 5.0

.Memorandum

March 31 , 2015 Page 44

4.11.1 Data Source

As part of ORD’s Study of Hydraulic Fracturing for Oil and Gas and its Potential Impact on Drinking Water Resources , ORD obtained data from nine UOG well operators, randomly selected to obtain a stratified statistical representation of the industry. A portion of the data that ORD received from operators included concentrations of constituents found in their produced
water

. Th ese data are available through the public docket for EPA’s Study of the P otential Impacts of Hydraulic Fracturing on Drinking Water Resources: Progress Report (Docket ID: EPA

- HQ

- ORD

- 2010

- 0674 )

. 52 EPA compiled t h ese concentration data into a spreadsheet and provided it to ERG. ERG performed QC checks on the concentration data ; a d escription of these QC checks is included in Section 5.0

. ERG imported the concentration data from EPA’s spreadsheet into the “ Raw Data 2

- O RD_All_Data_Manipulat ed ” table in the “ UOG Wastewater Characterization ” database in Attachment 14 (DCN SGE00724.A01 4).

ERG received a non

- CBI 53 subset of the national concentration data from EPA and analyzed the produced water data for inclusion in the W astewater C haracterization database, which is shown in Attachment 14 (DCN SGE00724.A01 4)

.

4.11.2 Method

s and Procedures

ERG ’s analysis of the ORD data is shown in Attachment 17 (DCN SGE00724.A01 7). ERG performed the following steps t o compile the constituent concentration data from ORD ’s data set :
Step 1: Standardize API Numbers

Using ORD’s data set (“ Raw Data_NonCBI Operator Data from ORD ” table in Attachment 17, DCN SGE00724.A01 7)

, ERG first standardized the API numbers for TX, ND, NM, AR, and LA to the format used by other states

. Queries 00 through 05 in Attachment 17 show this standardization.

Step 2: Make Table with ORD and DI Desktop ® Data

The API number standardization (Step 1) allowed ERG to link the ORD dataset to the DI Desktop ® dataset to pull additional data fields into the analysis (i.e., state, basin, formation, resource type, well trajectory, spud date, completion date). Query 10 in Attachment 17 shows this step in the analysis

. M ore information about the DI Desktop ®
databas e can be found in ERG’s Analysis of DI Desktop ® memorandum (DCN SGE00963)

. Step 3 : Update Data

ERG manually updated the “Resource Type_ERG” field to “tight” for the Spraberry formation, based on existing literature (DCN SGE00486) (see Query 11 in Attachmen t 17, DCN SGE00724.A01 7) . ERG also deleted any data where the associated formation

52 These data are referred to as source ORD, 2014 in the relevant attachments.
53 EPA removed all of the data flagged as confidential business information (CBI) under the Toxic Substances Control A ct of 1976 (TSCA) before providing this subset of data to ERG.Memorandum

March 31 , 2015 Page 45

name was blank (see Query 12 in Attachment 17, DCN SGE00724.A01 7) . ERG used Microsoft Access functions to calculate the number of days since fracturing, based on the date re ported in the ORD dataset and the completion date reported in the DI Desktop ®
dataset (see Query 13 in Attachment 17, DCN SGE00724.A01 7) . Finally, ERG updated the wastewater type to “UOG wastewater” for all data because the ORD dataset did not identify was tewater as flowback or long

- term produced water (see Query 14 in Attachment 17, DCN SGE00724.A01 7)

. Step 4 : Generate Final Table

ERG imp orted the final table (“All_Data_Final” table in Attachment 17, DCN SGE00724.A01 7) into the W astewater C haracterization database in Attachment 14 ( DCN SGE00724.A01 4) and standardized the data using the methods described in Section 3.2 of this memorandum.

4.11.3 Attachment 17

– Query Descriptions

Table 8 describes the queries used for the an alyses performed in Attachment 17 (DCN SGE00724.A01 7).

Table 8

. Analysis of ORD Non

- CBI Operator Data: Query Descriptions

Query(s) Query Description

00 Copied [API No] to [API_ERG] 01, 02, 03, 04, 05 Updated the [API_ERG] numbers for TX, ND, NM, AR, and LA to standardize the format of

the API number across all of the states represented in the data. 10 Linked the ORD dataset to the DI Desktop ® dataset to pull additional data fields into the

analysis (i.e., state, basin, formation, resource type, well trajectory, spud date, completion date). 11 Updated [ Formation ] and [ Resource Type ] for Spraberry.

12 Removed records with null or blank dates.

13 Calculated [Days Since Fracturing] by finding the differential between the sample date and well

completion date. 14 Set [Wastewater Type] to “UOG Wastewater”

5.0 Q UALITY C ONTROL (QC) P ROCEDURES
All of the analyses presented 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 Assurance Project Plan (SQAPP) (DCN SGE00 958 ), including collecti ng, evaluating, and analyzing existing data and information about p roduced w ater v olumes and constituent c haracteri stics

. Specifically, ERG used the procedures described in Section 4 of the PQAPP to gather and manage existing data in support of the UOG pro posed 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 NumberMemorandum

March 31 , 2015 Page 46

(DCN ), imported the reference information 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 proposed rulemaking. ERG used a combination 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 9

, 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., EPA site visit reports, industry meeting notes)

.

 Source Flag B

- Documents prepared by a verified 54 source that include citation information (e.g., operator reports, vendor document s, 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)

.

 Source Flag D

- Documents prepared by a source that could no t be verified and that do not include citation information.

ERG followed the procedures described in the PQAPP to generate, evaluate, and analyze data using spreadsheet s (Section 7.0) and databases (Section 8.0)

. ERG conducted the following QA checks during the analyses:

 ERG performed a 20 percent check of all data manually entered

.

 ERG performed a 100 percent check of all analyses and calculations, and documented these checks in internal version s of the spreadsheet s and databases

.

 For all analys e s per formed in state

- specific Access databases, one team member created queries and another team member reviewed the design and logic of the queries. ERG documented these checks in the internal versions of spreadsheet s and databases

.

 ERG had a senior staff memb er familiar with ELGs and the UOG proposed rulemaking review the results from each analysis.

ERG performed the following, specific QC checks on the data collected as part of ORD’s Study of Hydraulic Fracturing for Oil and Gas and its Potential Impact on Drinking Water Resources (discussed in Section 4.11 ):

54 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/organizati on websites that confirmed the author’s affiliation with the UOG industry.Memorandum

March 31 , 2015 Page 47

 ERG performed a 20 percent check of the data entry from the raw UOG well operator data to the compiled spread sheet. If ERG identified a discrepancy between the two files, ERG checked all of the relevant data from the file (i.e., not just a 20 percent check), where it was reasonable to do so (i.e., the number of data points in the file was less than 50).

 Where ER G identified a discrepancy between the data, ERG corrected the data in the “ Raw Data 2

- ORD_All_Data_Manipulated ” table in the “UOG Wastewater Characterization” database in Attachment 14 (DCN SGE00724.A01 4).

 ERG found data discrepancies in less than two percent of the files that were checked.

6.0 R EFERENCES

Table 9 lists the sources ERG used along with their DCN and source flag (see Section 5.0 for a description of source flags ). The type of information extracted from each source is noted with an X in the “WW Volume s ” (wastewater volumes) and /or “WW Char .” (wastewater characterization) columns.

Table 9

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

SGE00002 Volz, Conrad, Ferrar, Kyle, and Michanowicz, D. 2011.

Contaminant Characterization of Effluent from PA Brine Treatment Josephine Facility. A X

SGE00004.A06 Coleman, Nancy. Chesapeake Energy. Produced Formation

Water Sample Results from Shale Plays. B X

SGE00006.A03 Havics, Andrew. 2011. pH2, LLC/QEPA. Fracing &

Associated Media Composition in Colorado. A X

SGE00006.A04 McElreath, Debra. 2011. Chesapeake Energy Corp.

Comparison of Hydraulic Fracture Fluid Composition with Produced Formation Water Quality Following Fracturing: Implications for Fate and Transport. C X

SGE00007.A10 Mantell, Matthew. Chesapeake Energy Corp. Produced

Water Reuse and Recycling Challenges and Opportunities Across Major Shale Plays. C X

SGE00007.A13 Hayes, Tom. Gas Technology Institute. 2011.

Characterization of Marcellus Shale and Barnett Shale Flowback Waters and Technology Development for Water Reuse. A X

SGE00007.A14 Tipton, Steven. 2011. Newfield Exploration. Mid

- Continent

Water Management for Stimulation Operations. B

SGE00007.A18 Alleman, David. 2011. ALL Consulting. Treatment of Shale

Gas Produced Water for Discharge. D X

SGE00011 Veil, John. Argonne National Laboratory: E. 2010. Water

Management Technologies Used by Marcellus Shale Gas Producers. A X

SGE00064 Williams, John. 2011. Marcellus Shale Gas Development

and Water Resource Issues. USGS. A XMemorandum

March 31 , 2015 Page 48

Table 9

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

SGE00070 Acharya, Harish R. 2011. Cost Effective Recovery of Low

TDS Frac Flowback Water for Reuse. GE Global Research. A X X

SGE00091 Rimassa, Shawn, Paul Howard, Kristel Blow,

Schlumberger. 2009. Optimizing Fracturing Fluids from Flowback Water. Society of Petroleum Engineers. A X

SGE00110 Bruff, Mathew 20 11 . An Integrated Water Treatment

Technology Solution for Sustainable Water Resource Management in the Marcellus Shale. Alteta Inc. Argonne National Laboratory. BLX, Inc. CWM Environmental, Inc. A X

SGE00153 Energy Information Administration. 2011. Shale Gas Play,

Lower 48 States. Prepared by EIA Office of Oil and Gas. (May). A X

SGE00155 Energy Information Administration. 201 0 . Tight Gas Plays,

Lower 48 States. Prepared by EIA Office of Oil and Gas. ( June ). A X

SGE00241 Rowan, E.L., et al. Radium content of oil

- and gas

- field

produced waters in the northern Appalachian Basin (USA)

— Summary and discussion of data. U.S. Geological Survey Scientific Investigations Report 2011

– 5135, 31 p A X

SGE00275 US EPA. 2012. Site Visit Report Citrus Energy Corporation

Marcellus Shale Gas Operations. A X

SGE00276 US EPA. 2012. Meeting with XTO Energy, Inc. about

Unconventional Oil and Gas Sanitized. A X

SGE00280 US EPA. 201 3 . Site Visit Report Anadarko Petroleum

Corporation Marcellus Shale Gas Operations. (J anuary 9 ). A X

SGE00283 ERG. 2012. Camp, Meghan; Ruminski, Brent. Notes on

Conference Call with BLX, Inc on 15 May 2012. (June 11). A X

SGE00284 Hayes, Tom. 2012. Barnett and Appalachian Shale Water

Management and Reuse Technologies A X

SGE00286 Hammer, 2012. In Fracking's Wake: New Rules are Needed

to Protect Our Health and Environment from Contaminated Wastewater. (May). A X

SGE00298.A05 Ashwin Dhanasekar. 2012. Assessing Specific Shale Plays

-

Niobrara. Colorado State University. B X

SGE00305.A05 Dave Yoxtheimer. 2012. Flowback Treatment and Reuse

Strategies for Tight Oil Formations. Penn State Marcellus Center for Outreach and Research. B X

SGE00311.A07 Michael Dunkel. 2012. The Economics of Water

Management. Pioneer Natural Resources. B X

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

Energy. B X X

SGE00313 Gradient. 2009. Evaluation of Potential Impacts of Hydraulic

Fracturing Flowback Fluid Additives on Microbial Processes in Publicly

- Owned Treatment Works (POTWs). Prepared for Halliburton Energy Services, Inc

. C X

SGE00332 Kent, Perry. New Albany Shale Gas Research Project. Gas

Technology Institute. B XMemorandum

March 31 , 2015 Page 49

Table 9

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

SGE00333 Horn, Aaron D. 2009. Breakthrough Mobile Water

Treatment Converts 75% of Fracturing Flowback Fluid to Fresh Water and Lowers CO2 Emissions. Society of Petroleum Engineering. B X X

SGE00339 Susquehanna River Basin Commission (SRBC). 2011.

Susquehanna River Basin Commission: Water Withdrawals & Consumptive Use for Natural Gas Industry. A X

SGE00343 Welsh, James. Hydraulic Fracturing Regulatory Processes in

Louisiana. Louisiana Department of Natural Resources. A X

SGE00344 Haluszczak, Lara O.. 2012. Geochemical evaluation of

flowback brine from Marcellus gas wells in Pennsylvania, USA. Department of Geosciences, Pennsylvania State University. A X

SGE00345 Lewis, Aurana. 2012. Wastewater Generation and Disposal

from Natural Gas Wells in Pennsylvania. Nicholas School Of The Environment. Duke University. B X

SGE00350 Stepan, Daniel, et al.. 2010. Bakken Water Opportunities

Assessment

- Phase 1. Energy & Environmental Research Center, University of North Dakota. Prepared for National Energy Technology Laboratory. A X X

SGE00358 Ecolotron Water Recovery Systems. 2011. Treatment of

Flow Back and Produced Water from the Hydraulic Fracturing of Oil

– Shale. A X

SGE00359 Kimball, Robert. 2012. Key Considerations for Frac

Flowback / Produced Water Reuse and Treatment. CDM Smith. C X

SGE00414 Hayes, Thomas, et al. 2012. Characterization of Flowback

Waters from the Marcellus and the Barnett Shale Regions Report No. 08122

- 05.09. Research Partnership to Secure Energy for America (RPSEA). A X X

SGE00442.A02 Colwell, Cecil. 2013. Development of Cost Effective

Systems for Handling Produced Water. Source Energy. C X

SGE00442.A06 Murray, Kyle E.. 2013. Examining Water Production

Volumes and Produced Water Quality in the Mississippi Lime to Develop Appropriate Management Strategies. Mississippi Lime Production and Produced Water. B X X

SGE00465 Nicot, Jean

- Philippe and Scanlon, Bridget. 2012. Water Use

for Shale

- Gas Production in Texas, U.S.. University of Texas at Austin. A X

SGE00480 Luedecke, Richard. 2012. Energy Water Conservation &

Recycling 33rd Annual Governor's Water Conference. Devon Energy. C X

SGE00486 Energy Information Administration. 2013. Assumptions to

the Annual Energy Outlook 2013. A X

SGE00501 Bai, Bing. 2013. Modeling of Frac flowback and produced

water volume from Wattenberg oil and gas field. Journal of Petroleum Science and Engineering. Department of Civil and Environmental Engineering, Colorado State University. A X

SGE00507 Boschee, Pam. 2012. Handling Produced Water from

Hydraulic Fracturing. Oil & Gas Facilities. B XMemorandum

March 31 , 2015 Page 50

Table 9

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

SGE00511 Casey, Greg. 2013. The evolution of Class II Salt Water

Disposal (SWD) Wells as Part of the Shale Revolution. Technical Presentation presented at Ground Water Protection Council's Annual UIC Conference. (January). B X

SGE00518 Colorado Oil and Gas Conservation Commission (COGCC).

COGIS

- Production Data Inquiry. A X

SGE00520 Drillinginfo. 2011. DI Desktop ® December 2011 Download.

Drillinginfo, Inc. B X

SGE00532 Hansen, et al. 2013. Water Resource Reporting and Water

Footprint from Marcellus Shale Development in West Virginia and Pennsylvania. San Jose State University. (October 30). B X X

SGE00555 New York State Department of Environmental Control

(NYSDEC). 2009. New Discharge Notification: SPDES Permit NY 002 5984 to Watertown, NY POTW. (December). A X

SGE00556 Nicot, Jean

- Philippe. 2011. Current and Projected Water Use

in the Texas Mining and Oil and Gas Industry. Texas Water Development Board. Bureau of Economic Geology. (January). A X

SGE00557 North Dakota Industrial Commission (NDIC). 2014. Basic

Subscription Services

- Well Index. Department of Mineral Resources, Oil and Gas Division. Last Accessed on 1/27/2014. A X

SGE00558 Office of Geological Survey (OGS). 2011. Hydraulic

Fracturing of Natural Gas Wells in Michigan. (May 31). A X

SGE00559 Ohio Department of Natural Resources (OH DNR). 2012.

2011 Utica Shale Production. A X

SGE00560 Ohio Department of Natural Resources (OH DNR). 2013.

2012 Utica Shale Production. A X

SGE00561 Ohio Department of Natural Resources ( OH DNR ) . 2013.

Utica/Point Pleasant Shale Cumulative Permitting Activity through 12/07/2013. Downloaded on 12/12/2013. Last updated on 12/6/2013. A X

SGE00585 U.S. Environmental Protection Agency (U.S. EPA). 2014.

FracFocus ® Database . Office of Research and Development (ORD). A X

SGE00592 U.S. Department of Energy (U.S. DOE). 2013. Oil & Natural

Gas Program Newsletter (E&P Focus): Water Issues Dominate Oil and Gas Production. Fall. A X

SGE00607 U.S. Environmental Protection Agency (U.S. EPA). 2012.

Conference Call with Quicksilver Resources, Inc. About Shale Gas Operations Sanitized. (October 11). A X

SGE00616 U.S. Environmental Protection Agency (U.S. EPA). 2013.

Summary of the Technical Workshop on Wastewater Treatment and Related Modeling. April 18. A X

SGE00625 U.S. EPA. 201 5 . Site Visit Report: Southwestern Energy

(SWN) Fayetteville Shale Gas Operations Sanitized A XMemorandum

March 31 , 2015 Page 51

Table 9

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

SGE00629 Warner, Nathaniel, Cidney Christie, Robert Jackson, Avner

Vengosh. 2013. Impacts of Shale Gas Wastewater Disposal on Water Quality in Western Pennsylvania. Environmental Science and Technology. September 10. A X

SGE00632 Williams, John. Unknown. The Marcellus Shale Gas Play:

Geology, Development, and Water Resource Impact Mitigation. USGS: New York Water Science Center. A X

SGE00635 U.S. Environmental Protection Agency (U.S. EPA). 2012.

Site Visit Report Chesapeake Energy Corporation Marcellus Shale Gas Operations Sanitized. A X

SGE00639 Nicot et al. 2012

. Oil & Gas Water Use in Texas: Update to

the 2011 Mining Water Use Report. (September). Bureau of Economic Geology. A X

SGE00640 Mingazetdinov, Ildus. 2012. Predictions Of Produced Water

Quality And Quantity For Spatially

- Distributed Wells In Niobrara Formation. Department of Civil and Environmental Engineering. Colorado State University. B X

SGE00641 Nicot, Jean

- Philippe. 2013. Geographical, Geological, and

Hydrogeological Attributes of Formations in the Footprint of the Eagle Ford Shale. Bureau of Economic Geology. (February). A X

SGE00642 Goodwin, Stephan, et al. 2012. Life Cycle Analysis of Water

Use and Intensity of Oil and Gas Recovery in Wattenberg field, Colo. Oil & Gas Journal. (May 7). B X

SGE00643 Wyoming Oil and Gas Conservation Commission. 2013.

Download Production. A X

SGE00644 New Mexico Energy, Minerals and Natural Resources

Department (NMEMND). 2014. OCD Permitting: Well Search. A X

SGE00691 U.S. Environmental Protection Agency (U.S. EPA). 2013.

Summary of the Technical Workshop on Water Acquisition Modeling: Assessing Impacts Through Modeling and Other Means. September. A X

SGE00693 ERG. 201 5

. Data Compilation Memorandum for the

Technical Development Document (TDD) for Proposed Effluent Limitations Guidelines and Standards for Oil and Gas Extraction

. Office of Water Engineering and Analysis Division. A X

SGE00694 Oklahoma Geological Survey. 2014. Gas Shale Database.

Accessed January 29, 2014. A X

SGE00695 U.S. Environmental Protection Agency (U.S. EPA). 2012.

Conference Call with ConocoPhilips About Shale Gas Operations. A X

SGE00704 U.S. Environmental Protection Agency ( U.S. EPA ) . 2015.

Technical Development Document for Proposed Effluent Limitations Guidelines and Standards for Oil and Gas Extraction. A X X

SGE00710 Slutz, James, et al. 2012. Key Shale Gas Water Management

Strategies: An Economic Assessment Tool SPE 157532. Society of Petroleum Engineers. (September 11). B XMemorandum

March 31 , 2015 Page 52

Table 9

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

SGE00719 Agrawal, Archna. 2009. A Technical and Economical Study

of Completion Techniques in Five Emerging U.S. Shale Plays. Office of Graduate Studies of Texas A&M University. (December) B X

SGE00720 Kansas Geological Survey. 2014. Horizontal or Slant Wells

in Kansas. Last updated 2/8/2014. Accessed on 3/17/2014. A X

SGE00727 Ohio Department of Natural Resources (OH DNR). 2014.

2013 Quarterly Horizontal Shale Production: 3rd Quarter. A X

SGE00731 Silva, James. 2013. Pretreatment Targets for Salt Recovery

from Marcellus Shale Gas Produced Water. GE Global Research Center. IWC

- 13

- 38. (November 17). A X

SGE00734 Boschee, Pam. 2014. Produced and Flowback Water

Recycling and Reuse: Economics, Limitations, and Technology. Oil and Gas Facilities Magazine. (February). A X

SGE00737 Ohio Department of Natural Resources (OH DNR). 2014.

2013 Quarterly Horizontal Shale Production: 4th Quarter. A X

SGE00739.A03 ERG. 201 5 . Analysis of Pennsylvania Department of

Environmental Protection’s (PA DEP) Oil and Gas Waste Reports

– Attachment 3

– Data Calculations

. A X

SGE00740 ERG. 201 5

. Unconventional Oil and Gas (UOG) Drilling

Wastewater Memorandum. A X

SGE00773 Helmer, Stephen. 2014. RE: Public Records Request

- Frack

Waste

- Solids and Fluids

- Norm. (January 14). Tenorm A X

SGE00774 Ziemkiewicz, Paul. 2013. Water Quality Literature Review

and Field Monitoring of Active Shale Gas Wells. Phase I: Assessing Environmental Impacts of Horizontal Gas Well Drilling Operations. West Virginia Department of Environmental Protection. (Feb. 15). A X

SGE00777 Johnson, Tommy and Harry, David. 2014. Uinta Water

Management. Water Management for Shale Plays Conference. (May 28). C X

SGE00779.A25 RETTEW. 2014. Water Treatment

- Oil and Gas

Environment Compliance Conference Appalachian Basin

- Washington, PA May 13

– 14 C X

SGE00788 NYSDEC. 2009. Supplemental Generic Environmental

Impact Statement (SGEIS) on the Oil, Gas, and Solution Mining Regulatory Program. C X

SGE00948 Chapman. 2012. Geochemical and Strontium Isotope

Characterization of Produced Waters from Marcellus Shale Natural Gas Extraction. A X

SGE00949 Division of Solid and Hazardous Materials. 1999. An

Investigation of Naturally Occurring Radioactive Materials (NORM) in Oil and Gas Wells in New York State. DEC Publication . (April). A X

SGE00950 EERC Northern Great Plains Water Consortium (NGPWC).

2009. Bakken Water Opportunities Assessment. North Dakota Petroleum Council Annual Meeting. C XMemorandum

March 31 , 2015 Page 53

Table 9

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

SGE00951 NY S DEC. 201 1 . Supplemental Generic Environmental

Impact Statement (SGEIS) on the Oil, Gas, and Solution Mining Regulatory Program: Information Requests. Prepared by: ALL Consulting. A X

SGE00953 Gastem, Aaron Sulkey. Unknown. Otsego County, Utica

Water Analysis. USA A X

SGE00954 Palacios, Virginia. 201 2 . Baseline Groundwater Quality

Testing Needs in the Eagle Ford Shale Region April 2012 A X

SGE00955 USGS. 2013. USGS Produced Water Database Accessed on

November 25, 2013. A X

SGE00956 Blondes, Madalyn S., Kathleen D. Gans, James J. Thordson,

Mark E Reidy, Burt Thomas, Mark A Engle, Yousif K Kharaka, Elizabeth L Rowan. 2014. U.S. Geological Survey (USGS) National Produced Waters Geochemical Database v2.0 (PROVISIONAL) A X

SGE00957 ERG. 2013. Environmental Engineering Support for Clean

Water Regulations Programmatic Quality Assurance Project Plan (PQAPP)

. A X X

SGE00958 ERG. 2014. Unconventional Oil and Gas (UOG)

Supplemental Quality Assurance Project Plan (SQAPP)

. A X X

SGE00963 ERG. 201 5 . Analysis of DI Desktop ® M emorandum

. A X

SGE00988 Energy Information Administration. 2014. Assumptions to

the Annual Energy Outlook 2014. A X

SGE01021 Arkansas Oil and Gas Commission (AOGC). 2014. B

- 43

Field

- Well Completions. Downloaded 1/5/2014. A X

SGE01022 Energy Information Administration (EIA) . 2011.

Distribution and Production of Oil and Gas Wells by State. (January 7). A X

SGE0102 4 Louisiana Department of Natural Resources. 2014.

Haynesville Shale Wells. Last updated 1/5/2014. Downloaded 1/7/2014. A X

SGE01028 Pennsylvania Department of Environmental Protection.

2015. Technologically Enhanced Naturally Occurring Radioactive Materials (TENORM) Study Report. A X

a

— Source Flag A

— J ournal articles and documents prepared by or for a government agency (e.g., EPA 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, 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). Source Flag D

— Documents prepared by a source that could not be ve rified and that do not include citation information.

7.0 A TTACHMENTSA TTACHMENT 1: UOG PW D ATA C OMPILATION (DCN SGE00724.A01 )A TTACHMENT 2: DI D ESKTOP L ONG

- TERM P RODUCED W ATER G ENERATION R ATES (DCN SGE00724.A02 )A TTACHMENT 3: DI D ESKTOP L ONG

- TERM P RODUCED W ATER G ENERATION R ATES (DCN SGE00724.A03 )A TTACHMENT 4: F RAC F OCUS F RACTURING F LUID V OLUMES (DCN SGE00724.A04 )A TTACHMENT 5: F RAC F OCUS F RACTURING F LUID V OLUMES (DCN SGE00724.A05 )A TTACHMENT 6: B AKKEN F LOWBACK R ECOVERY (DCN SGE00724.A06 )A TTACHMENT 7: N EW M EXICO F LOWBACK R ECOVERY (DCN SGE00724.A07 )A TTACHMENT 8: U TICA F LOWBACK R ECOVERY AND L ONG

- TERM P RODUCED W ATER R ATES (DCN SGE00724.A08 )A TTACHMENT 9: N IOBRARA L ONG

- TERM P RODUCED W ATER R ATES (DCN SGE00724.A09 )A TTACHMENT 10: W YOMING F LOWBACK R ECOVERY (DCN SGE00724.A01 0)A TTACHMENT 11: W ATTENBERG F LOWBACK R ECOVERY AND L ONG

- TERM P RODUCED W ATER R ATES (DCN SGE00724.A01 1)A TTACHMENT 12: N IOBRARA F LOWBACK R ECOVE RY (DCN SGE00724.A01 2)A TTACHMENT 13: UOG W ASTEWATER C HARACTERIZATION A NALYSIS (DCN SGE00724.A01 3 )A TTACHMENT 14 : UOG W ASTEWATER C HARACTERIZATION D ATABASE (DCN SGE00724.A01 4 )A TTACHMENT 15 : USGS P RODUCED W ATER D ATABASE (DCN SGE00724.A01 5 )A TTACHMENT 16: USGS P RODUCED W ATER D ATABASE (DCN SGE00724.A01 6)A TTACHMENT 17: ORD N ON

- CBI O PERATOR D ATA (DCN SGE00724.A01 7)