### MEMORANDUM

TO: Lisa Biddle, EPA

Karen Milam, EPA

FROM: James K. O’Connell, ERG

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

DATE: June 7 , 2016

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

Characteri zation Data Compilation

– DCN SGE0 1184

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 for Effluent Limitations Guidelines and Standards for Oil and Gas Extraction (TDD) ( DCN SGE01188 ). Specifically, this memorandum focuses on information included in Chapter C in the TDD ; it c overs: data sources used, preparation and analysis of data, and compilation of summary data. Table 1 , below, provides an index of the tables and figures explained in more detail in this memorandum . Tables and figures in the TDD that are not described in this memorandum either did not require calculations or analysis by ERG, or are described in separate, supporting memoranda. The Crosswalk Memorandum between Proposed

an d Final Technical Development Document for Effluent Limitations Guidelines and Standards for Oil and Gas Extraction: Tables and Figures (DCN SGE01334) contains a crosswalk of all
ta bles and figures in the TDD. Appendix F of the TDD contains the name of the relevant supporting memorandum for each TDD table and figure , where applicable. This memorandum is organized into the following sections :

 Section 1.0 Compilation of UOG produced water volume data (TDD Table C

- 7

, Table C

- 8 , and Table C

- 9 )

 Section 2.0 Compilation of UOG produced water rates over time (TDD Figure C

2 )

.

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

.

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

.

 Section 5.0 describes additional UOG produced water characterization data analyses using national and state

- level datasets.

 Section 6.0 describes ERG’s quality assurance procedures

.

 Section 7.0 lists the references used for this memorandum and its attachments

.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 2

The 16 attachments to this memorandum contain the underlying data and calculations

us ed to support the information presented in the TDD and to create the TDD tables and figures discussed in this memorandum. These att achments are listed in Section 8.0 below.

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

, Table 1 provides the TDD chapter , memorandum section, and attachment information.

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 SGE01184 .A01

Figure C

- 3 Anions and Cations Contributing to TDS Concentrations

in Shale and Tight Oil and Gas Formations 3.3 SGE01184 .A 12

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 SGE01184 .A 12

Figure C

- 5 Barium Concentrations in UOG Produced Water from

Shale and Tight Oil and Gas Formations 3.3 SGE01184 .A 12

Table C

- 7 UOG Well Flowback Recovery by Resource and Well

Trajectory 1.0 SGE01184 .A01

Table C

- 8 Long

- Term Produced Water Generation Rates by

Resource Type and Well Trajectory 1.0 SGE01184 .A01

Table C

- 9 Produced Water Volume Generation by UOG Formation 1.0 SGE01184 .A01

Table C

- 11 Concentrations of Select Classical and Conventional

Constituents in UOG Produced Water 3.3 SGE01184 .A12

Table C

- 13 Concentrations of Select Anions and Cations

Contributing to TDS in UOG Produced Water 3.3 SGE01184 .A12

Table C

- 15 Concentrations of Select Organic Constituents in UOG

Produced Water 3.3 SGE01184 .A12

Table C

- 17 Concentrations of Select Metal Constituents in UOG

Produced Water 3.3 SGE01184 .A12

Table C

- 19 Concentrations of Select Radioactive Constituents in

UOG Produced Water 3.3 SGE01184 .A12

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

1.0 C OMPILATION OF UOG P RODUCED W ATER V OLUME D ATA

ERG compiled data to characterize typ ical 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:UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 3

 Fracturing fluid volume ( million gallons per well, Mgal/well) 1

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

 Long

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

Table C

- 9

, “ Produced Water Volume Generation by UOG 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

- 8 in the TDD , both of which are higher

- level aggregations of the data presented in Table C

- 9

. Table C

- 7

, “ UOG Well Flowback Recovery by Resource and Well Trajectory

, ” presents flowback recovery at the re source type level

, and Table C

- 8

, “ Long

- Term Produced Water Generation Rates by Resource Type and Well Trajectory

, ” presents long

- term produced water rates at the resource type level. The following subsections provide more information about the data sources and method s used to generate Table s C

- 7 , C

- 8 and C

- 9 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 analyses presented in Section 4.0

.

1.1.1 National

- level Datasets

ERG used two national

- level datasets, DI Desktop ® and FracFocus ®

. ERG conduct ed an analysis to calculate the median, as well as to illustrate the range of values contained within a given dataset 2

. 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 SGE0 1170 )

DI Deskt op ® 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. 3 The underlying data in the DI Desktop ® database comes from individual state oil and gas agencies and contains a record for all oil and gas wells ever drilled

. 4 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 2000 through 2014 . The version of the DI Desktop ® database that ERG used for this analysis was downloaded in March 2015 , representing,

1 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.

2 In most cases, ERG calculated the 10 th percentile and 90 th percentile values to represent the typical range of the data.

3 The database is subject to restrictions on its use and dissemination. Based on the license agreement discussions, access to the raw data in the database is limited to ERG and EPA personnel only; although summary data developed using queries can be disseminated more widely. Wholesale “data dumps” cannot be disseminated electronically. All disseminations of such summary data, however, should cite Drillinginfo as the source of the information.

4 The exact year recordkeeping began varies by state, with the majority of records dating back to 1900.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 4

for the most part, data from 2014 but this varies by state

. State

- level information such as the oil and gas ag ency names, last production date 5 , production start date 6 , and update frequency (e.g., monthly, quarterly) is provided in Drillinginfo’s Data Coverage table ( DCN SGE01171). The raw data are contained in the “ DI Desktop Wells (SGE01170) ” table in Attachment 3 (DCN SGE01184 .A03 ).

1.1.1.2 FracFocus ® D atabase (DCN SGE0 1169 )

FracFocus ® is an industry

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

. 7 Historically, submitting disclosures has been voluntary

, but some states are beginning to mandate 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

.

In June 2015, FracFocus ® published a Microsoft Access database (FracFocus ® 2.0) containing all of the public disclosures submitted to the orga nization through June 2015. It contains over 102,000 well records. In July 2015, ERG downloaded FracFocus ® 2.0 directly from the FracFocus ® website ( https://fracfocus.org/data

- download ) . The raw data from FracFocus ® 2.0 is contained in the “FF V2 ( SGE01169 )” table in Attachment 5 (DCN SGE01184 .A05).

1.1.2 State

- level Datasets

To estimate typical produced water volumes and rates in some states

, ERG used databases from O hio, Colorado , N ew M exico , N orth D akota

, and W yoming state agencies

. 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), a nd include well API number

, formation name, well completion date, and/or well trajectory. The analyses ERG performed are described in Sections 4.3 through 4.8 ; A ttachments 6 through 1 1 contain the data and ERG’s calculations (DCN SGE01184 .A06

- 1 1 ). A more detailed description of each data source is provided in the “Da ta Source” subsection s in Sections 4.3 through 4.8

.

1.1.3 Available Literature

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

. These data sources appear in Table 10 at the end of this memorandum , and are also listed in the “Source” column in the “PW Data” tab in Attachment 1 (DCN SGE01184 .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

5 This is the date that the state last updated the data that Drillinginfo included in ERG’s version of the DI Desktop ® database downloaded on March 30, 2015.

6 First year that the state agency maintained records for oil and gas wells.

7 These reports represent we lls completed in UOG formations, conventional oil and gas (COG) formations , and coalbed methane formations

.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 5

specifically reported that a typical horizontal Barnett well requires approximately 1,000,000 to 7,300,000 gal lons of fracturing fluid

, with a med ian of 3,700,000 gallons

, based on data for 14

, 000 wells (DCN SGE00465). ERG entered these values into the PW Data tab as the lower range , 8 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

- 7 , C

- 8 , and C

- 9 in the TDD . Each of the se step s corresponds to a specific tab in Attachment 1 (DCN SGE01184 .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 4.8 ) and reported in other available literature. ERG initiated a new record item (i.e., row) in this tab only when the existing data source reported the UOG formation and well trajectory

. ERG calculate d weighted average s of fracturing fluid volume, flowback

recover y, and long

- term produced water generation rates using the Equations in Step 2 ( Equation 1 ) and Step 3 ( Equation 2 ) below

. These averages were weighted by the number of data points contained in each formation/trajectory and resource/trajectory combination (i.e., combinations with more data points were giv en more weight in calculating the averages than those with fewer data points). 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

◦ Low er range ( barrels /well)

◦ Median/average ( barrels /well) 9

◦ Upper range ( barrels /well)

◦ Number of data points

 Flowback recovery (% of fracturing fluid injected)

◦ Lower range

◦ Median/average 9

◦ Upper range

◦ Number of data points

 Long

- term produced water generation rates

◦ Lower range ( b arrels / day/ well)

8 The lower and upper ranges represent the 10 th and 90 th percentile values, respectively, of the data ERG analyzed. Percentile values were chosen to represent the range of data instead of the minimum and maximum values reported, as the minimum and maximum v alues may not be representative of the typical range.

9 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 fi eld could represent a median, an average, or an uncharacterized single value.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 6

◦ Median/average ( barrels/day /well) 9

◦ Upper range ( barrels/day /well)

◦ Number of data points

 Source Flag (A, B, C

, or D) 10

 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

, respectively . 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 zeros 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 produc ed 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 Da ta tab in Attachment 1 (DCN SGE01184 .A01 ). Step 2: Generation of PW Data by Formation tab (TDD Table C

- 9 )

T o create TDD Table C

- 9

, ERG aggregated the data in the PW Data tab in Attachment 1 (DCN SGE01184 .A01) by formation and well trajectory (e.g., horizontal Barnett wells, vertical Marcellus wells)

. Table C

- 9 presents the following three different types of produced water data : fracturing fluid volume

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

- term produced water gener ation rate

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

, ERG calculated the following :

 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 (based on the number of data points) reported in the PW Dat a tab for each formation and well t rajectory combination

, using Equation 1 below.

 Maximum of the upper range

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

.

10 For a discussion on the source flags, please see Section 6.0

.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 7

 Number of data points

– Summed the total number of data p o ints reported in the PW Data tab for each formation and well trajectory combination. Equation 1

Weig h ted Average For m , i = ∑ Vol i × N i N Form i Form i 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 in the columns marked “ Data from the PW Data tab ” in the PW Data by Formation tab . ERG rounded these value s to two significant 11 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 both the quantity of data available, as well as the relative quality of the underlying information. For more info rmation about source flags, see Section 6.0

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

- 7 and Table C

- 8 )

T o create TDD Table s C

- 7 and C

- 8 , ERG aggregated data in the PW Data tab in Attachment 1 (DCN SGE01184 .A01) by resource type and well trajectory (e.g., horizontal shale wells, vertical tight wells). Table C

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

- 8 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
rep orted in the PW Data tab for each resource type and well trajectory combination

.

 Weighted average of the median/average values

– Calculated the wei g h t ed average (based on the number of data points) of the average/median values reported in the PW Data tab for each resource type and well trajectory combination using Equation 2 below.

 Maximum of the upper range

– I dentified the maximum value in the upper range reported in the PW Data tab for each resource type 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 resource type and well t rajectory combination.

11 Since the number o f significant figures contained in the source material varies and in some cases is unknown, it would be impractical to maintain significant figures throughout all calculations.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 8

Equation 2

Weig h ted Average Res
, i = ∑ Vol i × N i N Res i Res i 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 fluid 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. ERG only included data points from source s report ing the associated well trajectory

, number of days a fter 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 in Attachment 1 (DCN SGE01184 .A01 ). Most of these references were studies of flowback rates and chara cteristics over time after fracturing

. 12

2.2 Methods and Procedures

To compile typical produced water flow rates over time after fracturing, ERG took the following steps :
Step 1 :

ERG entered data from literature in to the following data fields in the FB Data tab in Attachment 1 (DCN SGE01184 .A01 ) :

 Basin

 F ormation

 W ell T rajectory ( horizontal, vertical)

 Reported F low R ate ( barrels per day, b pd ) 13

12 Most of these studies specifically reported flowback rates, as opposed to pro duced water, long

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

13 References reported flowback rates in units of barrels per day. Step 3 shows how ERG converted these rates from barrels per day to gallons per day.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 9

 Number of Days 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 SGE01184 .A01 ).

Step 3:

The FB Data Summary tab in Attachment 1 (DCN SGE01184 .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

.

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 Characterization d atabase is included in Attachment 13 (DCN SGE01184

. A13 ).

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, wastewater characterization data associated with drilling wastewater is discussed in the Unconventional Oil and Gas (UOG) Drilling Wastewater

m emorandum (DCN SGE01181 ). Sources of information included in the UOG Wastewater Characterization d atabase and an alyses o f the collected data are described in detail in the following sections of this memorandum

.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 10

3.1 Data Sources

ERG com piled characterization data from approximately 50 sources, including publicly available databases, industry reports, and numerous jour nal articles and technical papers. ERG also analyzed and aggregate d data from the 201 5 United States Geological Survey ( USGS ) Produced Water Geochemical D atabase v. 2. 1 (PROVISIONAL) (USGS database) by well , as described in Section 5.1 and shown in Attachments 14 and 15 (DCN SGE01184

. A14

- A1 5 ). ERG standardize d the data from ORD’s non

- confidential business information ( CBI ) 14 well operator data , as described in Section 5.2 and shown in Attachment 16 (DCN SGE01184

. A16 ). ERG also analyzed and aggregated data from the Wyoming Oil and Gas Conservation Commis sion (WY OGCC) by well, as described in Section 5.3 and shown in Attachment 17 (DCN SGE01184 .A17).

Table 10 lists 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 number s (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 6.0 in this memorandu m . 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 Sta ndardization Procedures

The UOG Wastewater Characterization database in Attachment 13 (DCN SGE01184

. A13 ) was designed to incorporate information from different data sources and to identify key wastewater characterization information, including:

 Measure d constituent

 Constituent category (e.g., metal)

 Location/region

 Basin

 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

, 15 maximum value)

14 ORD removed all o f 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.

15 The “median” field in the UOG Wastewater Characterization database can represent medians, ave rages, or other uncharacterized single values.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 11

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, crosswalks, and analyses described below are contained within the UOG Wastewater Characterization database (DCN SGE01184

. A13 ).

3.2.1 Data Preparation

ERG used four main raw data tables in the UOG Wastewater Characterization database : a g eneral “Pollutant Concentrations” summary table , data imported from the USGS d atabase

, national

- level produced water characterization data from EPA’s ORD , and data provided by WY OGCC

. The general “Pollutant Concentrations” summary table was compiled from the various sources listed in Table 10 , 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 5.1 and 5.2

, 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 a s 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 entered 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 trajectory , and wastewater description into raw data fields , capturing the data as they we re re ported by the source. Before performing any analyses o f the dataset, ERG removed all leading and trailing spaces from the raw data fields.

3.2.2 Constituent Standardization and Constituent Category Assignments

ERG created a list of all constituents included i n 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 constituents . For example, aluminum was placed in the “Metals” category. All crosswalks used in the data standardization and analys es are contained in the database.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 12

3.2.3 Minimum, Median , 16 and Maximum Data

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

, 16 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 correction in queries 101 through 121 of UOG Wastewater Characterization database in Attachment 13 (DCN SGE01184 .A13)

. ERG o nly con sidered 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 non

- 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 not associate with an existing formation

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

, were desi gnated 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 referencing EIA documents and using engineering judgment (DCN SGE01190 , DCN SGE0 1191 ) . 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

– Conventional, as appropriate

.

ERG also created a “Basin

- Region Crosswalk,” assign ing each basin to its appropriate region (Northeast, Gulf Coast, Midco ntinent, Southwest, Rocky Mountain, or West Coast), as identified by the U.S. EIA in t heir 201 5 Assumptions to the Annual Energy Outlook (DCN SGE01190 )

.

16 The “median” field in the UOG Wastewater Characterization database can represent medians, averages, or other uncharacterized single values.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 13

3.2.6 Well Trajectory

, Resource Type

, and Well Type Standardization

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

, resource type, and well type for each set of data points , using the “ Well Trajectory 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 stand ardized w astewater descriptions provided in each data source into the following categories : 17 fracturing fluid, base fluid, flowback, produced water; UOG
wastewater 18 ; and unknown

. These were standardized using the “WW Description Crosswalk ” in the UOG Waste water Characterization database (DCN SGE01184

. A13 )

. ERG captured

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

.

3.2.8 Unit

s of Measure Standardization

ERG converted reported constituent concentrations to standardized units of 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 int erest 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

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

.

17 These terms (fracturing fluid, base fluid, flowback, produced wat er, 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 memorandum).

18 ERG assigned the “UOG wastewater” category to any data source that reported data associated with wastewater generated from the well after fracture, but that did not specify flowback or produced water.

19 Secti on 304(a)(4) of the that Clean Water Act (CWA) designates the following as "conventional" pollutants: biochemical oxygen demand (BOD 5 ), total suspended solids (TSS), fecal coliform, pH, and any additional pollutants EPA defines as conventional. The Agency designated "oil and grease" as an additional conventional pollutant on July 30, 1979 (see 44 FR 44501). The CWA does not define “classical” pollutant. Rather, pollutants that are not designated as either conventional or toxic are considered nonconventional pollutants. An example would be TDS. In the discussion of pollutants in UOG wastewaters in this memorandum, ERG has organized the discussion according to the categories in Table 2 , which includes the category “Classical and conventional”. In this context, “Classical and conventional” refers to a range of parameters that are determined via classical wet chemistry analytical methods, including some CWA 304(a)(4) convent ional pollutants as well as other parameters such as nutrients, alkalinity, hardness, COD, etc.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 14

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

, Tetr achloroethylene

, 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 1 2 (DCN SGE01184 .A 12 ) 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 Content s (TOC) in Attachment 1 2 indicates the specific tabs with data and calculations for each TDD figure and table.

ERG did not use actual m inimum and maximum reported values for the summary tables ; lower and upper ranges were defined using the 10 th and 90 th percentiles of the median values (i.e., the lower range corresponds to the 10 th percentile of the median value and the upper range corresponds to the 90 th percentile of the median value)

. 20 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 database (DCN SGE01184

. A13 ): flowback, UOG wastewater , and produced
water. To create TDD Tab le C

- 11, Table C

- 13, Table C

- 15, Table C

- 17, and Table C

- 19 presented in Section C. 3 (UOG Extraction Wastewater Characterization) , ERG filtered the final dataset by specific constituent categories (e.g., classical and conventional 19

, metals, organics) and tabulated the 10 th percentile of the median data field

, 50 th percentile (median) of the median data field

, 90 th percentile of the median data field , number of data points, and number of detects 21 for each constituent

. ERG also sometimes organized the produced water characterization data by formation name. T he analyses used to generate the drilling wastewater characterization tables (i.e., TDD Table C

- 10, Table C

- 12, Table C

- 14, Table C

- 16, and Table C

- 18) are discussed in the Unconventional Oil and Gas (UOG) Drilling Wastewater memorandum (DCN SGE01181 ).

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

20 As discussed previously, the “median” values may represent medians, averages, or other uncharacterized single values.

21 Number of data points was based on the total number of samples taken; number of detects was based on the number of data points with valid measurements.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 15

TDS Contrib Ions w Form Summary tab in Attachment 12 , DCN SGE01184 .A 12 )

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

. 22

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 u sed 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 1 2 (DCN SGE01184 .A12 ). ERG used these underlying data sets to illustrate the dat a using box and whisker plots (see the Ca, Na, and Ca Figure and Barium Figure tabs in Attachment 12 , DCN SGE01184 .A 12 )

.

4.0 A DDITIONAL UOG P RODUCED W ATER V OLUME 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.

Subsections 4.1 and 4.2 describe analyses that ERG completed using national

- level datasets to generate data inputs to the PW Data tab in Attachment 1 (DCN SGE01184 .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 File Database (hereafter referred to as DI Desktop ® ) (DCN SGE01170) to calculate typical long

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

. ERG converted the raw DI

- Desktop ® data (DCN SGE01170) 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 . Attachment 2 (DCN SGE01184 .A02) contains the Microsoft Excel portion of the DI Desktop ® analysis. Attachment 3 contains the Microsoft Access database portion of the DI Desktop ® analysis; the queries performed in this attachment are described in Section 4.1.3

. ERG entered t he results of this analysis into the PW Data tab in Attachment 1 (DCN SGE01184 .A01 ).

4.1.1 Data Source

ERG developed a list of active oil and gas wells from DI Desktop ® in a separate analysis described in ERG’s Analysis of DI Desktop® memorandum 23 (DCN SGE01180 ). ERG used th is

22 ERG used engineering judgment to determine the “primary” versus “minor” ionic contributors based on availability of data and reported measu red values (see “TDS Contrib Ions w Form Summary” tab in Attachment 12, DCN SGE01184 .A12).

23 The version of the DI Desktop ® database that ERG analyzed was last downloaded in 2015 and contains data mostly from 2014 but it varies by state. State

- level information such as the oil and gas agency names, last production date, production start date, and update frequency (e.g., monthly, quarterly) is provided in Drillinginfo’s Data Coverag e table ( DCN SGE01171).UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 16

list of active oil and gas wells (shown in the “Active Oil and Gas Wells” table in Attachment 3, DCN SGE01184 .A03 ) to calculate long

- term p roduced water generation rates

. DI Desktop ® reports the following data that ERG used in this analysis: 24

 Formation 25

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

 Well completion date (DD/MM/YYYY)

 2000 to 2014 produced water production (sepa rate column for each year in barrels

, bbl ) 26

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 DI Desktop ® by UOG formation name, well completion year, and well trajectory. For each one of these groupings, ERG counted the number of wells completed that year and summed the total annual produced water volume for those wells for each year from 2000 through 2014

. An example for horizontal Barnett shale wells is shown in Figure 1

. ERG only included wells that were completed between 2000 and 2013. 27 Additionally, ERG only included records with sufficient data for this analysis, which include d the following:

 Well c ompletion date: Not null

 Annual long

- term produced w ater volume : Not null 28

 Well trajectory : Not null and not “unknown”

Results for all UOG formations are contained in the Detailed Results tab in Attachment 2 (DCN SGE01184 .A02).

Step 2: Calculation of Annual Long

- term Produced Wate r Rates by Completion Year

In the Detailed Results tab of Attachment 2 ( DCN SGE01184 .A02 ), ERG calculated the daily average long

- term produced water rate (bbl/day/well) for each completion year (i.e.,

24 Some of these data fields may be missing in DI Desktop®. ERG excluded records that were missing one or more of these data fields from this analysis.

25 For this analysis, ERG used the “ Common Formation Name ” field generated by ERG in a separate analysis of DI Desktop® described in ERG’s Analysis of DI Desktop® memorandum (DCN SGE01180).

26 DI Desktop ® includes annual produced water volumes but does not specify whether it is flowback or long

- term produced water.

27 ERG used the 2000 ye ar as a cutoff based on engineering judgement and when hydraulic fracturing became more common. ERG used the 2013 year as a cutoff because DI Desktop® included produced water volume through 2014. However, wells that were completed in 2014 may have produced flowback in 2014 which should not be included in long

- term produced water calculations.

28 Some states did not report water production to DI Desktop® . ERG did not include wells for states that have no water production data (i.e., KS, KY, MO, OH, OK, OR, PA, TN, UT). Information included or not included at the
state

- level is provided in Drillinginfo’s Data Coverage table ( DCN SGE01171). For AR, ERG only excluded Fayetteville wells because none of the Fayetteville wells had water data, but other wells in AR did.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 17

across the rows). ERG used Equation 3 to calculate this average

, which sums the annual long

- term produced water volumes starting with the year after the completion year (i.e., WCY+1) through 2014

, and divides by the number of wells, 365 days, and the number of production years (i.e., 2014

– WCY)

. 29 Figure 1 shows the resulting calculations for th e Barnett Shale example. As previously explained, DI Desktop ® 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

. Equation 3

LTPW per day per well = ∑ Annual LTPW 2014 WCY + 1 # of Wells × ( 2014

− WCY ) × 365

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 SGE01184 .A02 ) contains the final results of this analysis which include a row for each UOG formation and well trajectory combination 30

. For each combination

, ERG calculated the 10 th percentile, 50 th percentile (i.e., median) , and 90 th percentile of the “daily average long

- term produced water rate (bbl/day/well)” column in the Detailed Results tab. ERG calculated the 10 th percentile and 90 th percentile values to represent the typical range of the data. ERG also calculated
t he total number of wells for eac h UOG formation and well trajectory. ERG entered these results into the PW Data tab of Attachment 1 (DCN SGE01184 .A01 ).

29 ERG assumed that all wells generated long

- term produced water for 365 days per year after the well completion
year. 30 The associated basin and resource type of the UOG formation is also included in the results.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 18

4.1.3 Attachment 3

– Query Description s

Table 3 describes the queries in Attachment 3 (DCN SGE01184 .A03 )

. Table 3

. Query Descriptions for ERG’s Long

- Term Produce Water Analysis of DI

Desktop ® Database (Attachment 3, DCN SGE01184 .A03 )

Attachment 3 Quer y # Query Description Applicable Tabs in Attachment 2

100 This qu ery creates a new table called [Results] . To make this table, the

query groups well records in the [Active Oil and Gas Wells] table by :

 UOG formation name;

 W ell completion year;

 Resource type (shale or tight); and

 W ell trajectory (horizontal, directional or vertical). For each of these combination groupings of UOG formation, completion
year, resource type, and well trajectory

, the query :

 Counts the number of wells that fit into th at grouping ; and

 Sums the annual produced water volumes for each year from 2000 to 2014 for all the wells that fit in to that grouping. ERG excluded the following records from the “Results” table:

 Wells complete d in 2014 ;

 W ells completed before the year 2000 ;

 Wells that don’t belong to any UOG formation ; and

 Wells with an unknown well trajectory. ERG also excluded states that did not report water production data to DI Desktop ®

. Information included or not included at the state

- level is provided in Drillin ginfo’s Data Coverage table ( DCN SGE01171). Detailed Results tab

4.2 Attachment s 4 and 5 FracFocus ® Fracturing Fluid Volumes

ERG analyzed a database published by FracFocus ® in June 2015 (DCN SGE01169 ) 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 SGE01184 .A01 ). Attachment 4 (DCN SGE01184 .A04 ) contains the Micros oft Excel portion of the analysis

. Attachment 5 (DCN SGE01184 .A05 ) contains the Microsoft Access database portion of the analysis , including the queries that link the FracFocus ® data to other oil and gas databases, which are described in more detail in Sec tion 4.2.3

.

4.2.1 Data Sources

The FracFocus ® database ( DCN SGE01169 ) (see Section 1.1.1.1 ) contains fracturing fluid volume data for individual well s identified by API number

. I t does not contain UOG formation name s or well trajector ies, both of which are necessary for this analys is. Therefore, ERG used DI Desktop ® (DCN SGE01170 ) and various databases published by state oil and gas agencies to identify these additional data fields for this analysis. 31 As shown in Figure 2 , the

31 ERG used the list of active oil an d gas wells in DI Desktop ® as identified by ERG in a separate analysis of DI Desktop ® described in ERG’s Analysis of DI Desktop ® memorandum (DCN SGE01180). The version of the DI Desktop ® database analyzed was last updated in 2015 and referred to data from 2014 but it varies by state. State

level information such as the oil and gas agency names, last production date, production start date, and update frequency (e.g., monthly, quarterly) is provided in Drillinginfo’s Data Coverage table ( DCN SGE01171).UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 19

common data field in the FracFocus ® database , DI Desktop ® , and the state oil and gas databases is the well API number. ERG o nly included well API numbers that were contained in both the FracFocus ® database (DCN SGE01169 ) and the other databases in the results of this analysis. For example

, the FracFocus ® database contains records for wells that were completed after the
most recent date contained in DI Desktop ® ; t hese FracFocus ® records were excluded from the analysis

.

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

. However

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

, but are more up

- to

- date than the version of DI Desktop ® that ERG used in this analysis. For these states, ERG used the published state agency databases instead of DI Desktop ® to maximize the number of usa ble results. For example, ERG identified less than one hundred UOG wells drilled into the Utica shale formation (in Ohio) in DI Desktop ® , resulting in limited results that matched up with FracFocus ® records . However, the Ohio Department of Natural Resources (OH DNR) publishes a running list of Utica shale wells (updated weekly)

, over a thousand wells of which matched up with a FracFocus ® record s

. Therefore, ERG linked the FracFocus ® data to the OH DNR data, as opposed to DI Desktop ® , to obtain the UOG formation and well trajectory information for the Utica shale wells. ERG used databases published by the following state agencies in this analysis:

 Ohio Department of Natural Resources (OH DNR) (DCN SGE0 1172 )

 K ansas Geological Survey (KGS) (DCN SGE0 1175)

 North Dakota Industrial Commission (NDIC) (DCN SGE0 1189 )

Figure 2 . Overview of Sources Used for FracFocus ® Fracturing Fluid Volume AnalysisUOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 20

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 described in Section 4.2.3

, ERG linked well records in the FracFocus ® database to well records in DI Desktop ® using well API number (DCN SGE01184 .A05)

. The resulting table, FF DB

– Manipulated, contains the data fields listed below for each well API number:

 From the FracFocus ® database (DCN SGE001169):

o Well Name

o Well location (state, county, latitude, longitude)

o Operator name

o Fracturing fluid volume (gallons) 32

o Fracture date (start and end dates)

 From DI Desktop ® (DCN SGE01170 ):

o Resource type

o Formation

o Well tr ajectory ( i.e., ho rizontal, directional, vertical)

If ERG did not find a match in DI Desktop ® , the resource type, formation, and well trajectory fields were left blank in the final table, but ERG still included the well API number and relevant data from th e FracFocus ® database

. Step 2: Cross Reference FracFocus ® Database against State Agency D atabases

ERG identified state agency databases with more up

- to

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

. Using the queries described in Section 4.2.3

, ERG linked the FracFocus ® database with these state agency databases using well API number ( similar to Step 1 above )

. The results (i.e., resource type, formation, and well trajectory) 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 DI Desktop ®

. ERG used a state agency data base instead of DI Desktop ® for North Dakota, Ohio, and Kansas. Table 4 contains more detail about the data contained in each state agency database.

The FF DB

- Manipulated tab in Attachment 4 (DCN SGE01184 .A04) contains the resulting records from Steps 1 and 2.

Step 3: Summary of Results

The Summary of Results tab in Attachment 4 (DCN SGE01184 .A04) provides summary statistics of the data in the FF DB

– Manipulated tab. ERG calculated the 10 th percentile,

32 The fracturing fluid volume is noted in Attachment 4 (DCN SGE01184.A04) as “TotalBaseWaterVolume”.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 21

50 th percentile (i.e., median), and 90 th percentile 33 statistics of fracturing fluid volumes (gallons) reported in the FF DB

- Manipulated tab. ERG converted the volumes from gallons to barrels by dividing by 42 gallons per barrel. These statistics were calculated for each UOG formation and well trajectory b asis 34

. The Summary of Results tab also sums the total number of data points (i.e., number of wells) 35

. ERG entered these results into the PW Data tab of Attachment 1 (DCN SGE01184 .A01 ).

4.2.3 Attachment 5

– Query Descriptions

Table 4 describes the queries ERG used to analyze the FracFocus ® database in Attachment 5 (DCN SGE01184 .A05 ). The results of the analysis are documented in Attachment 4 (DCN SGE01184 .A04 ).

The following is a list of tables found in Attachment 5 (DCN SGE01184 .A05) with a brief descriptio n of the data contained in each :

 DI Desktop Wells (SGE01170)

– The raw DI Desktop® database (DCN SGE001170).

 FF DB

- Manipulated

– This is a version of the FracFocus ® datab ase that ERG created by processing the queries listed in Table 4 . This table is copied into the FF DB

- Manipulated tab in Attachment 4.

 FF V2 ( SGE011 69 )

– This is version 2 of the raw FracFocus ® database published by FracFocus ® in June 2015 (DCN SGE01169 ).

 Formation C onsolidation Crosswalk

– C rosswalk of known basin and formation combinations in DI Desktop ® developed during ERG’s analysis of DI Desktop ® (DCN SGE0 1170 ).

 KS Horizontal Wells (SGE0 1175 )

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

 ND Wells ( SGE01189 )

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

 OH Horizontal Utica Wells (SGE0 1172 )

– L ist of permitted Utica wells published by OH DNR

.

33 ERG calculated the 10 th percentile and 90 th percentile values to represent the typical range of the data.

34 ERG added the basin for each formation in the Summa ry of Results tab.

35 In this analysis, the number of data points equals the number of wells.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 22

Table 4

. FracFocus ® Fracturing Fluid Volumes Query Descriptions

Attac hment 5 Query # Query Description

1 00 This query makes a new table called [ FF DB

– Manipulated ] and populates it with all records

from the FracFocus ® database (DCN SGE01169) that meet the following criteria:

 The field “ TotalBaseWaterVolume ” is greater than 0.

 The field “ State ” is not "beaver" and not "beckham" and not "harper" and not "hemphill" and not “ red river" and not “ roosevelt" and not "rusk" and not “ state" and not "ward"

. ERG identified data quality issues with these entries in th e FracFocus® database . These exclusions corresponded to a small number of total records.

200 This query cross references the API numbers in the [ FF DB

– Manipulated ] table against the [ DI

Desktop Wells (SGE01170) ] table . When an API match is found, this query populates the Well Trajectory field in the [ FF DB

– Manipulated ] table with the well trajector y reported in DI Desktop ®

. Wells without a match are still included in the [ FF DB

– Manipulated ] table, but the

“ Well Trajectory ” field is left blank

.

201 This query performs the following two cross references simultaneously:

 The [ FF DB

– Manipulated ] table is cross referenced against the [ DI Desktop Wells (SGE01170) ] table via API number; and

 T he [ DI Desktop Wells (SGE01170) ] table is cross referenced against the [ Consolidated Formation Crosswalk ] table a via “ Basin, ” “ Reservoir, ” and “ Formation ” fields. If a match is found

, this query updates the “ Consolidated Formation ” and “ Resource Type ” fields in the [ FF DB

– Manipulated ] table with the “ Consolidat ed Formation ” and “ Resource Type ” fields reported in the [ Formation Consolidation Crosswalk ] table

. Wells without a match are still included in the [ FF DB

– Manipulated ] table

, but the “R esource T ype ” and “F ormation ” fields are left blank.

300 This query cross references the API numbers in the [ FF DB

– Manipulated ] table against a list of

horizontal Utica shale wells published by OH DNR ( DCN SGE01172 ). If the API numbers in FracFocus ® (DCN SGE0 1169 ) match API numbers in OH DNR (DCN SGE01172 ), th is query updates the “ Formation, ” “ Well Trajectory

, ” and “ Re s our c e T ype ” fields in the [ FF DB

– Manipulated ] table to "Utica", "H" (based on OH DNR's file name, which is a list o f horizontal wells), and "shale

, ” respectively.

301 This query cross references the API numbers in the [ FF DB

– Manipulated ] table against a list of

permitted horizontal Kansas wells published by the KGS (DCN SGE0 1175 ). If the API numbers in FracFocus ® (DCN SGE0 1169 ) match API numbers in KGS's list (DCN SGE 0 1175 ), this query updates the “ Consolidated Formation

, ” “ Well Trajectory

, ” and “ Resource Type ” fields in the [ FF DB

– Manipulated ] table to "Mississippi Lime", "H" (based on KGS's file name, which is a list of horizontal wells), and " tight

, " respectively. This query only pulls wells from KGS's horizontal well list where the reported format ion name includes "Mississippi.”

302 This query cross references the API numbers in the [ FF DB

– Manipulated ] against a list of oil

and gas wells in North Dakota published by NDIC (DCN SGE01189 ). If the API numbers in FracFocus ® (DCN SGE0 1169 ) match API numbers in NDIC's list (DCN SGE01189 ) t his query updates the “ Consolidated Formation ” and “ Resource Type ” fields in the [ FF DB

– Manipulated ] 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 Well Trajectory field in the [ FF DB

– Manipulated ] table to the reported value in the w ellbore field (i.e., Well Trajectory ) in NDIC's list.

400 This query updates all null values in the “ Well Trajectory ” field of the [ FF DB

– Manipulated ]

table to “ U ” (i.e., unknown).

401 This query updates all null values in the “ Consolidated Formation ” field of the [ FF DB

–

Manipulated ] table to “ Unknown ”

.

402 This query updates all null values in the “ Resource Type ” field of the [ FF DB

– Manipulated ]

table to “ Unknown ”

. These wells could be UOG wells

, where ERG could not identify a common formation name, COG wells, or CB M wells.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 23

Table 4

. FracFocus ® Fracturing Fluid Volumes Query Descriptions

Attac hment 5 Query # Query Description

500 This qu ery summarizes the final results of the [ FF DB

– Manipulated ] table . It includes counts of

wells by Consolidated Formation

, State, and Well Trajectory

.
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 (D CN SGE01180 ).

Subsections 4.3 through 4.8 describe analyses that ERG completed using state or formation level data sets to genera te data inputs to the PW Data tab in Attachment 1 (DCN SGE01184 .A01 ) (see Section 1.2 ).

4.3 Attachment 6

– Bakken Flowback Recovery

ERG estimated flowback recovery fo r UOG wells completed in the Bakken shale formation in North Dakota using data published by the NDIC (DCN SGE01189 ) and the results from ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE01184 .A04

- A 0 5). ERG entered the results of this analysis as inputs to the PW Data tab in Attachment 1 (DCN SGE01184 .A01 ). Attachment 6 (DCN SGE01184 .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 01189 ). 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 36

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 SGE0 1184 .A04

- A05 ). Relevant data provided in the FracFocus ® results included the following :

 Well API number

 Formation

 State

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

 Fracture date (start and end dates)

 Fracturing fluid volume (gallons)

36 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 mon th.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 24

The well A PI number is the field ERG used to link the FracFocus ® database to the NDIC data.

4.3.2 Method

s and Procedures

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

ERG filtered the results from the FracFocus ® Fracturing Fluid Volume analysis for Bakken shale wells located in North Dakota (DCN SGE01184 .A04

- .A 0 5)

, excluding wells with unknown well trajector ies

. These well records are contained in the Analysis tab of At tachment 6 (DCN SGE01184 .A06).

Step 2: Estimate Flowback Volumes in NDIC’s Production Data

ERG searched the NDIC production database for Bakken shale wells listed in the Analysis tab (from Step 1)

. For each well, ERG located the production data for the giv en month in which the well was completed, according to the FracFocus ® database. ERG recorded the produced water volume and production days 37 in the “Estimated Flowback Volume (barrels) ” and “ Production Days ” fields

, respectively

, in the Analysis tab in Atta chment 6 (DCN SGE01184 .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 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. 38 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 barrels of produced water d uring 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 SGE01184 .A06 ).

Step 3: Calculate Flowback Recovery

ERG calculated th e estimated flowback recovery as a percentage of total fracturing fluid volume using Equation 4 below . ERG performed this calculation in the “Estimated Flowback Recovery” field in the Analysis tab in Attachment 6 (DCN SGE01184 .A06) for each well record with an estimated flowback volume from Step 2 above . The total

37 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.

38 ERG made this assumption in order to make the available data in literature useful f or 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.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 25

fracturing fluid volume was obtained from ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE01184 .A04

- A 0 5).

Equation 4

Flowback Recovery ( % ) = Flowback volume
Total Fracturing Fluid Volume × 100

Note: ERG c onverted flowback volume units from barrels to gallons using 42 gallons per barrel.

Step 4 : Calculate Summary Statistics

ERG calculated 10 th percentile, 50 th percentile, and 90 th percentile statistics for the estimated flowback recovery for Bakken shale wells. The results are shown in the Results tab of Attachment 6 (DCN SGE01184 .A06)

, which also includes the number of wells analyzed. ERG excluded vertical and directional Bakken wells from the results because there were a limited number of records (less t han 10)

.

ERG calculated the 10 th percentile and 90 th percentile values to represent the typical range of the data. E RG also calculated the median number of production days associated with the flowback recovery statistics to verify it agrees with typical f lowback 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 3 0 days of production, which falls within the general ranges of flowback proces s length reported in literature , and thus verifies the methods and procedures for this analysis

.

4.4 Attachment 7

– New Mexico Flowback Recovery

ERG estimated flowback recovery for UOG wells in New Mexico using data published by the New Mexico Energy, Minerals, and Natural Resources Department (NMEMNRD) (DCN SGE00644) along with results from ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE01184 .A04

- A 0 5). This included UOG wells completed in the Avalon and Bone Spring, Wo lfcamp, Delaware, and Dakota formations. 39 ERG entered the results of this analysis as inputs to the PW Data tab in Attachment 1 (DCN SGE01184 .A01 ). Attachment 7 (DCN SGE01184 .A07 ) contains the underlying Microsoft Excel file.

4.4.1 Data Source

ERG obtained well production data from NMEMNRD (DCN SGE00644). 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); a nd

 Number of production days in each month.

39 Other UOG formations (i.e., Morrow, Mesaverde) were also identified from ERG’s analysis of FracFocusTM but were not included in the results because there were less than 10 wells.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 26

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 SGE01184 .A04

- A 0 5). Relevant data in these results included the following :

 Well API number

 Formation

 State

 W ell trajector y ( horizontal, vertical, or directional)

 Fracture date (start and end dates)

 Fracturing fluid volume (gallons)

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

4.4.2 Method

s and Procedures

To estimate typical flowback recovery , ERG used the following procedures :
Step 1 : Ide ntify New Mexico Wells from FracFocus ® Analysis

ERG filtered the results from the FracFocus ® Fracturing Fluid Volume analysis for UOG wells located in New Mexico (DCN SGE01184 .A04

- A 0 5)

, excluding wells with unknown well trajectories

. These well records are contained in the Analysis tab of Attachment 7 (DCN SGE01184 .A07).

Step 2: Identify Flowback Volumes in NMEMNRD ’s Production Data

ERG searched the NMEMNRD production database for wells listed in the Analysis tab (from Step 1). For each well, ERG located the production data for the given month in which the well was completed, according to the FracFocus ® database. ERG recorded the produced water volume and production days in the “Estimated Flowback Volume (barrels) ” and “ Produ ction Days ” fields, respectively, in the Analysis tab in Attachment 7 (DCN SGE01184 .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 da ys in addition to the volumes for the entire next month of production. 40 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

40 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.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 27

“Estimated Flowback Volume (barrels)” and “Production Days” fields

, respectively

, in the Analysis tab of Attachment 7 (DCN SGE01184 .A07 ).

Step 3 : Calculate Flowback Recovery

ERG calculated the estimated flowback recovery as a percentage of total fracturing fluid volume using Equation 4 . ERG performed this calculati on in the “Estimated Flowback Recovery” field in the Analysis tab in Attachment 7 (DCN SGE01184 .A06) for each well with an estimated flowback volume from Step 2 above. The total fracturing fluid volume was obtained from ERG’s Analysis of FracFocus ® Fractur ing Fluid Volumes (DCN SGE01184 .A04

- A 0 5).

Step 4 : Calculate Summary Statistics

ERG calculated 10 th percentile, 50 th percentile, and 90 th percentile statistics for the estimated flowback recovery for UOG wells in New Mexico. The results are shown in the Res ults tab of Attachment 7 (DCN SGE01184 .A07)

, which also includes the number of wells analyzed. ERG excluded well trajectory and formation combinations from the results if they had less than 10 wells (e.g., directional wells in the Delaware formation).

ERG calculated the 10 th percentile and 90 th percentile to values to represent the typical range of the data. 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 30 to 31 days of production

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

.

4.5 Attachment 8

– Utica Flowback Recovery and Long

- term Produced Water Rates

ERG estimated flowback recovery and long

- term produced water generation rates for UOG wells completed in the Utica shale formation in Ohio using data published by the OH DNR along with results from ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE01184 .A04

- A 0 5)

. ERG used th is 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 estimate long

- term produced water for most other UOG formations. ERG entered the results from this analysis into the PW Data tab of Attachment 1 (DCN SGE01184 .A01) under the horizontal Utica shale well category. 41 Attachment 8 (DCN SGE SGE01184 .A08 ) contains the underlying Microsoft Excel file for this analysis

.

41 OH DNR named some of the published production files “Utica” production and others “horizontal shale” production. ERG assumed that all of the wells are horizontal shale wells completed in the Utica formation for the purpose of this analysis.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 28

4.5.1 Data Source

ERG download ed Microsoft Excel files from the OH DNR website containing oil, gas, and produced water production on a quarterly or annual basis. 42 ERG downloaded the following files and compiled all of the data in the Raw Sate Data tab in Attachment 8 ( DCN SGE01184 .A08 ) :

 2011 Utica Shale Production

– DCN SGE00559

 2012 Utica Shale Production

– DCN SGE0056 0

 2013 Quarterly Horizontal Shale Production: 1st Quarter

– DCN S GE00964

 2013 Quarterly Horizontal Shale Production: 2nd Quarter

– DCN SGE00 965

 2013 Quarterly Horizontal Shale Production: 3rd Quarter

– DCN SGE00727

 2013 Quarterly Horizontal Shale Production: 4th Quarter

– DCN SGE00737

 2014 Quarterly Horizontal Shale Production: 1st Quarter

– DCN SGE01237

 2014 Quarterly Horizontal Shale Production: 2nd Quarter

– DCN SGE0123 8

 2014 Quarterly Horizontal Shale Production: 3rd Quarter

– DCN SGE01239

 2014 Quarterly Horizontal Shale Production: 4th Quarter

– DCN SGE01240

 2015 Quarterly Horizontal Shale Production: 1st Quarter

– DCN SGE01241

 2015 Quarterly Horizontal Shale Productio n: 2nd Quarter

– DCN SGE012 42

Each file reports the following data :

 Well API number

 Year and, where applicable, quarter of production data

 Other identifier information (e.g., Owner, Well Name)

 Quarterly or annual production of oil (barrels), gas (t housand cubic feet ), and produced water (barrels) 43

 Number of production days in each quarter or year.

To obtain fracturing fluid volumes for this analysis, ERG used the FracFocus ® database described in Section 1.1 (DCN SGE01169 ). Relevant data from these results included the following :

 Well API number

 State

 Fracture date (start and end dates)

 Fracturing fluid volume (gallons)

42 P roduction data for 2013, 2014 , and 2015 is provided in quarterly files ; production data for 2011 and 2012 is provided for the entire year. 43 In these reports, OH D NR refers to produced water as "brine" which includes both flowback and long

- term produced water.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 29

The well API number is the common field ERG used to link the FracFocus ® database to the OH DNR production data. Note that the production files published by OH DNR indicate that all Utica wells 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 :
Step 1: Identify Utica Shale Wells in Ohio from FracFocus ® Analysis

ERG filtered the results from the FracFocus ® Fracturing Fluid Volume analysis for Utica shale wells located in Ohio (DCN SGE01184 .A04

- A 0 5)

, excluding wells with unknown well trajector ies . These well records are contained in the FB Analysis tab of Attachment 8 (DCN SGE01184 .A08).

Step 2: Identify Flowback Volumes in OH DNR’s Production Data

For each well listed in the FB Analysis tab (from Step 1) in Attachment 8 (DCN SGE01184 .A08) , ERG looked up the total produced water and production days in the OH DNR production data contained in the Raw State Data tab for each of the production periods listed in Table 5 ( e.g., 2011, 2012, 2013

- 1 st quarter) . Next, ERG identified the first production period in which each well produced oil, gas, and/or water and recorded the period in the “ First Production Period ” field in the FB Analysis tab . Lastly, using the calculation methods described in Table 5

, ERG recorded the produced water volume and production days in the “Estimated Flowback Volume (barrels) ” and “ Production Days ” fields, respectively, in the FB Analysis tab. As shown in Table 5

, the method ERG used
to identif y flowback volumes varied depending on the first production period for each well.

Literature reports that the flowback process lasts between 14 and 60 days (DCN SGE00951). F or the purpose of this anal ysis

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

. If the re were more than 60 production days during the first reporting period, ERG did not calculate flowback recovery for the well. 44 Further, some wells may have produced for less than 14 days in the first production period

, so the flowback recovery (calculated in S tep 3 ) may be an underestimate.

Table 5

. Calculation Methods Used for Each “First Production Period”

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

2011 If the number of production days in 2011 wa s less than 60 days, E RG divided the

2011 brine production by the fracturing fluid volume.

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

brine production by the fracturing fluid volume.

44 ERG used a slightly different approach from other analyses in Section 4.0 because the data published by OH DNR is organized on a quarterly basis, not on a monthly basis.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 30

Table 5

. Calculation Methods Used for Each “First Production Period”

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

2013

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

the 1 st quarter 2013 brine production by the fractur ing fluid volume.

2013

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

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

2013

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

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

2013

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

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

201 4

– 1 st Quarter If the number of 1 st quarter 2014 production days wa s less than 60 days, E RG divided

the 1 st quarter 2014 brine production by the fracturing fluid volume.

201 4

– 2 nd Quarter If the number of 2 nd quarter 2014 production days wa s less than 60 days, E RG divided

the 2 nd quarter 2014 brine production by the fracturing fluid volume.

201 4

– 3 rd Quarter If the number of 3 rd quarter 2014 production days wa s less than 60 days, E RG div ided

the 3 rd quarter 2014 brine production by the fracturing fluid volume.

201 4

– 4 th Quarter If the number of 4 th quarter 2014 production days wa s less than 60 days, E RG divided

the 4 th quarter 2014 brine production by the fracturing fluid volume.

201 5

– 1 st Quarter If the number of 1 st quarter 201 5 production days wa s less than 60 days, E RG divided

the 1 st quarter 201 5 brine production by the fracturing fluid volume.

201 5

– 2 nd Quarter If the number of 2 nd quarter 201 5 production days wa s less than 60 days, E RG divided

the 2 nd quarter 201 5 brine production by the fracturing fluid volume.

a

— If the production days w ere reported as 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 estimated flowback recovery as a percentage of total fracturing fluid volume using Equation 4 . ERG perf ormed this calculation in the “Estimated Flowback Recovery” field in the Analysis tab in Attachment 8 (DCN SGE01184 .A08) for each well with an estimated flowback volume from Step 2 above. The total fracturing fluid volume was obtained from ERG’s Analysis o f FracFocus ® Fracturing Fluid Volumes (DCN SGE01184 .A04

- A 0 5).

Step 4 : Identify OH DNR Long

- Term Produced Water Volumes and Calculate Long

- Term Produced Water Rates

Next, ERG calculate d long

- term produced water rates using a similar methodology as described in Section 4.1.2 (DI Desktop ® long

- term produced water analysis) ; all inputs

were from OH DNR’s production data. The relevant calculations are contained i n the

“ LTPW Analysis ” tab. For each production period listed in Table 6 , ERG counted the total number of wells that produced oil, gas, and/or water in that period and summed the total produced water volume for those wells for all subsequent production periods. ERG calculated long

- term produced water rates separately for each production period group. Table 6 provides more detail about how ERG identified and calculated long

- term produced water rates
, which varied by the year and/or quarter the well first produced oil, gas, or produced water

.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 31

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

First Prod. Period 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 beginning with the

1 st quarter 2013

. a ERG divided the total 2013, 2014, and 2015 ( 1 st and 2 nd quarters only ) produced water volume by the number of calendar days b over the same period (900 days) b and by the number of wells that first produced in 2011

.

2012 E RG assumed that wells that first produced in 2012 were in the production phase beginning with the

2 nd quarter 2013

. a ERG divided the total 2013 ( 2 nd , 3 rd and 4 th quarters only ), 2014, and 2015 ( 1 st and 2 nd quarters only ) produced water volume by the number of calendar days b over the same period (810 days) b and by the number of wells that first produced in 2012

.

2013

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

beginning with the 3 rd quarter 2013

. a ERG divided the total 2013 (3 rd and 4 th quarter s only ) , 2014, and 2015 (1 st and 2 nd quarters only) produced water volume by the number of calendar days b over the same period ( 720 days) b and by the number of wells that first produced in 1 st quarter 2013

.

2013

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

beginning with the 4 th quarter 2013

. a ERG divided the total 2013 (4 th quarter only), 2014, and 2015 (1 st and 2 nd quarters only) produced water volume by the number of calendar days b over the same period (630 days) b and by the number of wells that first produced in 2 nd quarter 2013

.

2013

– 3 rd Quarter E RG assumed that wells that first produced in the 3 rd quarter 2013 were in the production phase

beginning with the 1 st quarter 2014

. a ERG divided the total 2014 and 2015 (1 st and 2 nd quarters only) produced water volume by the number of calendar days b over the same period ( approximately 540 days) b and by the number of wells that first produced in 3 rd quarter 2013

.

2013

– 4 th Quarter E RG assumed that wells that first produced in the 4 th quarter 2013 were in the production phase

beginning with the 2 nd quarter 2014

. a ERG divided the total 2014 (2 nd , 3 rd , and 4 th quarters only) and 2015 (1 st and 2 nd quarters only) produced water volume by the number of calendar days b over the same period (450 days) b and by the number of wells that first produced in 4 th quarter 2013

.

201 4

– 1 st Quarter E RG assumed that wells that first produced in the 1 st quarter 2014 were in the production phase

beginning with the 3 rd quarter 2014

. a ERG divided the total 2014 (3 rd and 4 th quarters only) and 2015 (1 st and 2 nd quarters only) produced water volume by the number of calendar days b over the same period (360 days) b and by the number of wells that first produced in 1 st quarter 2014

.

2014

– 2 nd Quarter E RG assumed that wells that first produced in the 2 nd quarter 2014 were in the production phase

beginning with the 4 th quarter 2014

. a ERG divided the total 2014 (4 th quarter only) and 2015 (1 st and 2 nd quarters only) produced water volume by the number of calendar days over the same period (270 days) b and by the number of wells that first produced in 2 nd quarter 2014.

201 4

– 3 rd Quarter E RG assumed that wells that first produced in the 3 rd quarter 2014 were in the production phase

beginning with the 1 st quarter 2015

. a ERG divided the total 2015 (1 st and 2 nd quarters only) produced water volume by the number of calendar days b over the same period (180 days) b and by the number of wells that first produced in 3 rd quarter 2014

.

201 4

– 4 th Quarter E RG assumed that wells that first produced in the 4 th quarter 201 4 were in the production phase

beginning with the 2 nd quarter 2015

. a ERG divided the total 2015 (2 nd quarter only) produced water volume by the number of calendar days b over the same period (90 days) b and by the number of wells that first produced in 4 th quarter 2014

. 201 5

– 1 st and 2 nd Quarter ERG assumed wells that first produced in the 1 st quarter 2015 and later were not in the production

phase until the 3 rd quarter 2015. Because no data from OH DNR was available after the 2 nd quarter 2015, ERG did not calculated long

- term produced water rates for these wells.

a

— ERG also skipped the entire reporting period that immediately followed the period the well was completed to avoid inadvertently including flowback volumes in the long

- term produced water calculation. ERG assumed that wells only produce long

- term produced water (i.e., not flowback) when they are in the production phase. b

— ERG used the number of calendar days instead of the production days reported by OH DNR to be consistent with ERG’s analysis of DI Desktop ® (see Section 4.1.2 ). The production days reported by OH DNR factor in down time require d for maintenance that is experience d by most wells. ERG assumed 90 calendar days per quarter.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 32

Step 5: Calculate Summary Statistics

ERG calculated 10 th percentile, 50 th perce ntile, and 90 th percentile statistics for the estimated flowback recovery and long

- term produced water rates for horizontal Utica wells in Ohio. The results are shown in the Results tab of Attachment 8 (DCN SGE01184 .A08)

, which also includes the number of wells analyzed (i.e., number of data points) and the number of flowback days (relevant only to the flowback recovery data)

.

ERG calculated the 10 th percentile and 90 th percentile values to represent the typical range of the data. ERG also calculated the m edian 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 24 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.

4.6 Attachment 9

– Wyoming Flowback Recovery

ERG estimated UOG flowback recovery for UOG wells completed 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 ® Fracturing Fluid Volumes (DCN SGE01184 .A 04

- A 0 5). This included UOG wells completed in the Mesaverde, Lance, Niobrara, Cod e ll, and Mowry formations. 45 ERG entered the results of this analysis in to the PW Data tab in Attachment 1 (DCN SGE01184 .A01 ). Attachment 9 (DCN SGE01184 .A 09 ) contains the underlying Microsoft Excel file for this analysis

.

4.6.1 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:

 Mo nthly 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 SGE01184 .A04

- A 0 5). Relevant data in these results included the following :

 Well API number

 Formatio n

 State

 Well trajectory ( horizontal, vertical, or directional)

 Fracture date (start and end dates)

45 Other UOG formations (i.e., Muddy J) were also identified from ERG’s analysis of FracFocusTM b ut were not included in the results because there were less than 10 wells.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 33

 Fracturing fluid volume (gallons)

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

4.6.2 Methods and Procedure s
To estimate typical flowback recovery , ERG used the following procedures :
Step 1: Identify WY UOG Wells in the FracFocus ® Database

ERG filtered the results from the FracFocus ® Fracturing Fluid Volume analysis for UOG wells located in Wyoming (DCN SGE01184 .A04

- A 0 5)

, excluding wells with unknown well trajector ies . The well records are contained in the Analysis tab of Attachment 9 (DCN SGE01184 .A09).

Step 2: Download WOGCC’s Production Data

ERG searched the WOGCC database for the list of well API numb ers identified in step 1 using the “Download Production” feature on the WOGCC website. ERG downloaded the results in Microsoft Excel format and copied them into the Raw State Data tab of Attachment 9 (DCN SGE01184 .A09).

Step 3 : Identify Flowback Volumes in WOGCC’s Production Data

ERG searched the WOGCC production data in the Raw State Data tab for wells listed in the Analysis tab (from Step 1). For each well, ERG located the production data for the given month in which the well was completed, according to t he FracFocus ® database. 46 ERG recorded the produced water volume and production days in the “Estimated Flowback Volume (barrels) ” and “ Production Days ” fields, respectively, in the Analysis tab in Attachment 9 (DCN SGE01184 .A09).

Literature reports that t he 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 volume for the entire next month of production. 47 For example, a wel l 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

46 In the Raw State Data tab, the “Flowback Indicator _ERG ” field is flagged as “flowback” durin g periods of potential flowback. Flowback periods were identified by searching for the month and year that the well was fractured according to FracFocsTM.

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 individua l wells may have been lower or higher than the recovery ERG estimated.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 34

“Estima ted Flowback Volume (barrels)” and “Production Days” fields respectively in the Analysis tab of Attachment 9 (DCN SGE01184 .A 09 ).

Step 4 : Calculate Flowback Recovery

ERG calculated the estimated flowback recovery as a percentage of total fracturing fluid volume using Equation 4 . ERG performed this calculation in the “Estimated Flowback Recovery” field in the Analysis tab in Attachment 9 (DCN SGE01184 .A09) for each well with an estimated flowback volume from Step 3 above. The total fracturing fluid volume was obtained from ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE01184 .A04

- A 0 5).

Step 5 : Calculate Summary Statistics

ERG calculated 10 th percentile, 50 th percentile, and 90 th percentile statistics for the estimated flowback recovery for UOG wells in Wyoming. The results are shown in the

“ Results ” tab of Attachment 9 (DCN SGE01184 .A09)

, which also includes the number of wells analyzed and t he total number of wells. ERG excluded well trajectory and formation combinations from the results if they had less than 10 total wells (i.e., Column I) (e.g., vertical wells in the Niobrara formation ).

ERG calculated the 10 th percentile and 90 th percentile values to represent the typical range of the data. ERG also calculated the median number of production days associated with the flowback recovery statistics to verify it agrees with typical flowbac k 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 27 to 31 days of production, depending on the formation, which falls within the gener al ranges of flowback process length reported in literature, and thus verifies the methods and procedures for this analysis.

4.7 Attachment 1 0

– Codell

- Niobrara Flowback Recovery and Long

- term Produced

Water Rates

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

- Niobrara formation located in the Denver Basin ) using data generated by Bing Bai in 2013 (DCN SGE00501). The u nderlying data and results are shown in t he Analysis tab of Attachmen t 10 (DCN SGE01184 .A 10 ). ERG entered the results of this analysis into the PW Data tab of Attachment 1 (DCN SGE01184 .A01 ).

4.7.1 Data Source

ERG used data from an article published in the Journal of Petroleum Science and Engineering b y 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 consolidated all of these formations in to the "Codell

- Ni obrara" formation forUOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 35

the purpose of this analysis

. 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.

4.7.2 Meth ods 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 5 (shown as Equation 2 in DCN SGE00501)

. As reported by Bai, 2013, Equation 5 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 5

q = 264

. 4 e − 0

. 043 t

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 6 below (shown as Equation 3 in DCN SGE00501)

. As reported by B ai, Equation 6 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 )

. Equation 6

q = 88

. 86 ( 1 + 0

. 0447 t )

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 7 below (shown as Equation 1 in DCN SGE00501). As reported by Bai, Equation 7 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 7

q = 1

. 981 e − 0

. 1614 tUOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 36

Where:
q = flow rate

, barrels per day
t = time since completion , days
Step 4: Calculate Summary Statistics

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

term produced water rates separately for horizontal and vertical wells. ERG calculated the 10 th percentile and 90 th percentile values to represent the typical range of the data. For horizontal wells o nly

, 48 ERG also calculated the flowback rates over the first 30 days of production , based on engineering judgement, to estimate total flowback volume

. 49 ERG presents the results in the Results tab in Attachment 10 (DCN SGE01184 .A 1 0 ). 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 SGE01184 .A01 ).

4.8 Attachment 1 1

– Colorado Flowback Recovery

ERG estimated flowback recovery for UOG wells completed 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 SGE01184 .A04

- A 0 5). This included UOG wells completed in the Niobrara, Codell, Codell

Niobrara, Mancos

, and Muddy J UOG formations

. ERG entered the results of this analysis as inputs to the PW Data tab in Attachment 1 (DCN SGE01184 .A01 ). Attachment 1 1 (DCN SGE01184

. A11 ) contains the underlying Microsoft Excel file.

4.8.1 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 SGE01184 .A04

- A 0 5). Relevant data in these results included the following :

 Well API number

 Formation

 State

 Well trajectory ( horizontal, vertical, or directional)

 Fracture date (start and end dates)

 Fracturing fluid volume (gallons)

48 Bai (2013) only provided an equation to calculate flowback rates for horizontal wells.

49 Literature reports that the flowback process lasts anywhere between 14 and 60 days

. (DCN SGE00951).UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 37

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

4.8.2 Methods and Procedures

Step 1: Identify Colorado Wells from FracFocus ® Analysis

ERG filtered the results from the FracFocus ® Fracturing Fluid Volume analysis for UOG wells located in Colorado (DCN SGE01184 .A04

- A 0 5)

, excluding wells with unknown well trajectories . The well records are contained in the Analysis tab of Attachment 11 (DCN SGE01184 .A11).

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

ERG searc hed the COGCC production database for the wells listed in the Analysis tab (from Step 1). For each well, ERG located the production data for the given month in which the well was completed, according to the FracFocus ® database. ERG recorded the produced wa ter volume and production days in the “Estimated Flowback Volume (barrels) ” and “ Production Days ” fields, respectively, in the Analysis tab in Attachment 11 (DCN SGE01184 .A11).

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 that had fewer than 14 prod uction days in the completion month , ERG recorded the volume for these days in addition to the volumes for the entire next month of production. 50 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 1 1 (DCN SGE01184 .A 11 ).

Step 3: Calculate Flowback Recovery

ERG calculated the estimated flowback recovery as a percentage of total fracturing fluid volume using Equation 4 . ERG performed this calculation in the “Estimated Flowback Recovery” field in the Analysis tab in Attachment 11 (DCN SGE01184 .A11) for each well with an estimated flowback volume from Step 2 above. The total fracturing fluid volume was obtained from ERG’s Analysis of FracFocus ® Fracturing Fluid Volumes (DCN SGE01184 .A04

- A 0 5).

50 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 rec overy ERG estimated.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 38

Step 4: Calculate Summary Statistics

ERG calculated 10 th percentile, 50 th percentile, and 90 th percentile statistics for the estimated flowback rec overy for UOG wells in Colorado . The results are shown in the Results tab of Attachment 11 (DCN SGE01184 .A11)

, which also includes the number of wells analyzed and the total number of wells . ERG excluded well trajectory and formation combinations from the results if they had less than 10 wells (e.g., horizontal wells in the Codell

- N iobrara formation).

ERG calculated the 10 th percentile and 90 th percentile values to represent the typical range of the data. ERG also calculated the media n 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 29 to 30 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.

5.0 A DDITIONAL UOG P RODUCED W ATER C HARACTERIZATION D ATA : A NALYSES U SING

N ATIONAL AND S TATE

- L EVEL D ATASETS
The following subsections describe analyses that ERG completed using national

- and
state

- level datasets to generate data inputs to the UOG Wastewater Characterization D atabase in Attachment 1 3 (DCN SGE01184

. A13 ) (see Section 3.0 )

.

5.1 USGS Data Used for UOG Produced Water Constituent Characterization

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

level produced water characterization dataset published by USGS. The analyses and underlying data appear in Attachments 14 and 15 (DCN SGE01184

. A14

- .A1 5 ).

5.1.1 Data Source

The U SGS Produced Water Geochemical Database v. 2. 1 (PROVISIONAL) (USGS database) contains geochemical and other information for produced waters from both conventional and unconventional well types (DCN SGE01260 ) . The database is a compilation of 25 individual databases, publications, or reports . ERG used the USGS database to obtain produced water constituent data to include in the UOG Wastewater Characterization Database in Attachment 1 3 (DCN SGE01184

. A13 ).

ERG obtained data from the USGS d atabase from the USGS website on August 24 , 201 5 and aggregated the data for inclusion in the “ Raw Data 3

- USGS Data ” table in the “ UOG Wastewater Characterization ” database in Attachment 13 ( DCN SGE01184

. A13 ). The “USGS National Produced Waters Geochemical Database v. 2

. 1 (PROVISIONAL)

– Documentation” file (DCN SGE01260 ) provides additional background about this database and defines all of the fields within the tables in the database.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 39

5.1.2 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 15 (DCN SGE01184

. A15 )

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

, then deleted entries from reference s that were already included in the UOG Wastewater Characterization 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 fo llowing 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 15 ( DCN SGE01184

. A15 ) into the USGS Data tab in Attachment 14 ( DCN SGE01184

. A14 ) . Within Attachment 14 , ERG first removed any negative v alues 51 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 14

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

Step 4: “Un

- Crosstab” Data

ERG exported the results of the Median Summary_Del Blank Col tab from Attachment 14 ( DCN SGE01184

. A14 ) into the “USGS Median Summary Data (f rom Excel)” table in Attachment 15 ( DCN SGE01184

. A15 )

. 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 52 to pull the results 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” 53 process on the “USGS_Temp” table in Attachment 15 (DCN SGE01184

. A15 ) to make the data more usable in Step 5

.

51 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 f

ind 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 ERG would not expect a conce ntration value below zero.

52 Union queries combine the results of several similar select queries.

53 The “un

- crosstab” process refers to the process of translating data from columns into rows.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 40

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 values based on the data i n the “un

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

5.1.3 Attachment

s 14 and 15

– Query Descriptions

Table 7 describes the queries and their results used to perform the analyses in Attachment s 14 and 15 (DCN SGE01184

. A14 and A1 5 ).

Table 7

. USGS Produced Water Database: Query Descriptions

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

.

1 5 001 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 appended 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 4 54

“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 a nd 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 5 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 create 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

54 Attachment 14 (DCN SGE01184 .A14) is an Excel attachment in whi ch ERG completes the median calculations that cannot be performed in the Access database in Attachment 15 (DCN SGE01184 .A15). Attachment 15 lists Query 200 as a placeholder entry for the step in which ERG exports the data to Excel to perform these median

c alculations.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 41

Table 7

. USGS Produced Water Database: Query Descriptions

Query(s) Query Description Relevant Memorandum Attachment Parameter column headers) into a table with individual 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.

5.2 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 16 (DCN SGE01184

. A16 ) and the QC procedures are described in Section 5.3

.

5.2.1 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 strat ified 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 Potent ial Impacts of Hydraulic Fracturing on Drinking Water Resources: Progress Report (Docket ID: EPA

- HQ

- ORD

- 2010

- 0674 )

. 55 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 5.3

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

- O RD_All_Data_Manipulated ” table in the “ UOG Wastewater Characterization ” database in Attachment 13 (DCN SGE01184

. A13 ).

55 These data are referred to by the relevant Docket ID instead of by DCN in the relevant attachments.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 42

ERG received a non

- CBI 56 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 13 (DCN SGE01184

. A13 )

.

5.2.2 Method

s and Procedures

ERG ’s analysis of the ORD data is shown in Attachment 16 (DCN SGE01184

. A16 ). 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 16 ( DCN SGE01184

. A16 )

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

. Queries 00 through 05 in Attachment 16 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 16 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 SGE01180 )

. 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 16, DCN SGE01184

. A16 ) . ERG also deleted any data where the associated formation name was blank (see Query 12 in Attachment 16 , DCN SGE01184

. A16 ) . ERG used Microsoft Access functions to calculate the number of days since fracturing, based on the date repo rted in the ORD dataset and the completion date reported in the DI Desktop ® dataset (see Query 13 in Attachment 16 , DCN SGE01184

. A16 ) . Finally, ERG updated the wastewater type to “UOG wastewater” for all data because the ORD dataset did not identify wastew ater as flowback or long

- term produced water (see Query 14 in Attachment 16 , DCN SGE01184

. A16 )

. Step 4 : Generate Final Table

ERG imp orted the final table (“All_Data_Final” table in Attachment 16 , DCN SGE01184

. A16 ) into the W astewater C haracterization database in Attachment 13 ( DCN SGE01184

. A13 ) and standardized the data using the methods described in Section 3.2 of this memorandum.

56 EPA 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.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 43

5.2.3 Attachment 1 6

– Query Descriptions

Table 8 describes the queries used for the analyses performed in Attachment 16 (DCN SGE01184

. A16 ).

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”

.

5.3 WY OGCC Data Used for UOG Wastewater Constituent Characterization

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

- level produced water characterization dataset published by the Wyoming Oil and Gas Conservation Commission (WY OGCC). The analyses and underlyin g data appear in Attachment 17 (DCN SGE01184.A17).

5.3.1 Data Source

EPA requested data from WY OGCC and received a dataset output on September 3, 2015 containing the raw data found in the “WY OGCC Raw Data” table in Attachment 17 (DCN SGE01184.A17) 57 . The raw WY OGCC dataset contains wastewater characterization data at the well level for wastewater from both conventional and unconventional well types (DCN SGE01244.A01). ERG used the WY OGCC data to obtain produced water constituent data to include in the UOG Wastewater Characterization Database in Attachment 13 (DCN SGE01184.A13).

5.3.2 Methods and Procedures

ERG performed the following steps to analyze the WY OGCC data:

57 ERG excluded some of the raw data from WY OGCC due to data quality concerns. The WYOGCC Water Data Memorandum (DCN SGE01244) provides more detail about the data quality concerns in the underlying, raw data from WY O GCC.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 44

Step 1: Remove Duplicates

ERG reviewed the WY OGCC dataset and determined that some of t he data were duplicative with data from the USGS Produced Water database version 2.1 (DCN SGE01260 ) that was also reviewed and analyzed in this memorandum (see Section 5.1 )

. In an effort to eliminate duplicates, ERG compared the WY OGCC data to the USGS data. ERG compared the following five data fields, and if the data in all five fields were exact duplicates, ERG excluded the WY OGCC data from the UOG Wastewater Ch aracterization Database in Attachment 13 (DCN SGE01184.A13) :

 API number

 pH

 Total dissolved solids (TDS)

 Calcium (Ca)

 Chloride (Cl)

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

ERG compiled a list of unique wells, based on the following WY OGCC database fields: API number, well name, field name, formation name, and sample location. ERG assigned each unique well in the extracted dataset a “Well ID” that was used to aggregate constituent data by well.

Step 3 : “Un

- Crosstab” Data

Next, because the raw WY OGCC constituent data were in a crosstab

- type format where the parameter names were stored in the column headings, ERG created a union query 58 to pull the results of each column into a single table with three columns containing Well ID, Parameter, an d Value. This query created one row for each measurement, which is the format that Microsoft Access typically requires to aggregate data.

Step 4 : Extract Relevant Data

ERG compared the WY OGCC data to the DI Desktop® data (DCN SGE01180.A01) to identify the wastewater characterization data associated with UOG wells. ERG cross reference d the data in the WY OGCC dataset to the “Active Oil and Gas Wells” table in the DI Desktop ® dataset by API number to get a list of UOG wells

. ERG used the

“ Res ource Type ” (e.g., shale, tight) and “ Consolidated Formation ” (e.g., Fayetteville) fields in the DI Desktop® dataset to determine the list of UOG wells

. Where the

“ Resource Type ” and/or “ Consolidated Formation ” fields we re blank, ERG excluded the wells fro m the UOG Wastewater Characterization Database in Attachment 13 (DCN SGE01184.A13) because we could not determine if the data were associated with UOG or COG wells.

58 Union queries combine the results of several similar select queries.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 45

Step 5 : Import Relevant Data into UOG Wastewater Characterization Database

T he final table was formatted for import into the UOG Wastewater Characterization database in Attachment 13 (DCN SGE01184.A13)

. ERG imported the table as “ Raw Data

- WY OGCC

- Not Final ”.

Step 6: Summarize Data by Basin, Formation, and Parameter

In an effort to equally weigh the available data for all basins and formations in the United States 59 , ERG collapsed the data from WY OGCC into one median value for each basin, formation, and parameter . Because Microsoft Access does not support median calculations, ERG exported th e “ Raw Data

- WY OGCC

- Not Final ” table in Attachment 1 7 ( DCN SGE01184.A1 7 ) into the Raw Data

- WY OGCC

- Not Final tab in Attachment 18 ( DCN SGE01184.A18). Within Attachment 18, ERG used Excel functions to calculate the median values and number of sample s for each unique Basin, Formation, and Parameter on the Import_Raw Data 4

- WY OGCC tab in Attachment 18.

Step 7 : Import Summarized Data into UOG Wastewater Characterization Database

ERG imported the Import_Raw Data 4

- WY OGCC tab into the UOG Wastewater Characterization database in Attachment 13 (DCN SGE01184.A13). ERG named the table “ Raw Data 4

- WY OGCC ”

.

5.3.3 Attachment 17

– Query Descriptions

Table 9 describes the queries and their results used to perform the analyses in Attachment 17 (DCN SGE01184.A17).

Table 9 . WY OGCC Database: Query Descriptions

Query(s) Query Description

000 Initialize d [ WY OGCC Data Without Dups ] table

. 001 Compared [WY OGCC Raw Data] with [USGS Raw Data] using API No, Ca, Cl, TDS, and pH

values to find duplicate data. 002 Appended non

- duplicate WY OGCC data to [WY OGCC Data Without Dups ] table

. 003 Created a union query to pull “ WellID ” and value for each Paramete r . This query convert s the data

from a crosstab type query (WellID row headers and Parameter column headers) into a table with individual line entries for each Well ID, Parameter, and Value. 004 Combined the results of query 003 with the well data (API No, Well Name, Formation), using the

“ WellID ”

. 005 Queried the [Act ive Oil and Gas Wells] table from the DI Desktop® Well File Database (DCN

SGE01170) to summarize unique API Nos. with associated [Consolidated Formation] names. Note: only entries with a valid [Consolidated Formation] and/or [Resource Type] were assumed to be UOG wells.

59 The other large data sets that ERG used for the UOG wastewater characterization analyses represented data for the entire United States. Since the WY OGCC data only represented da ta from basins/formations in WY, including each data point as a unique value in ERG’s analysis caused unintentional weight to be given to the data from these basins/formations.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 46

Table 9 . WY OGCC Database: Query Descriptions

Query(s) Query Description

006 Combined the results of queries 004 and 005 using API No.

007 A ppend ed the results of 006 into [ WY OGCC Data

– for Export ] table

. 008 Assigned unique “ SGE_ID ” values to [ WY OGCC Data

– for Export ] entries for use in the UOG

Wastewater Characterization database (DCN SGE01184.A13)

6.0 Q UALITY A SSURANCE ( QA ) 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 collecting, 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 rulemaking. ERG staff entered reference information for relevant sources into the UOG Literature Review datab ase. The ERG index keeper reviewed all reference information, assigned each reference a Document Control Number (DCN ), imported the reference information into the UOG Project File Index database, and saved referenced files in the Electronic Project File fo lder.

ERG also used the procedures described in Section 3 of the SQAPP when collecting existing data for use in the UOG rulemaking. ERG used a combination of sources, including reports, papers, and online databases from state regulatory agencies

, such as d epartments of environmental protection and oil and gas commissions. As shown in Table 10 , ERG assigned a source flag (A, B, C or D) to all references used in these an alyses

. 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 60 source that in clude 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 verified and that do not include citati on information.

60 ERG considered sources as verified if we were able to find information about the author outside of the reference document. ERG primarily verified information by looking for company/organization websites that confirmed the author’s affiliation with the UOG industry.UOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 47

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 performed in state

- specific Access databases, one t eam 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 member familiar with ELGs and the UOG rulemaking rev iew 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 5.2 ):

 ERG performed a 20 percent check of the data entry from the raw UOG well operator data to the compiled spreadsheet. 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 ERG identified a discrepancy between the data, ERG correct ed the data in the

“ Raw Data 2

- ORD_All_Data_Manipulated ” table in the “UOG Wastewater Characterization” database in Attachment 13 (DCN SGE01184 .A 13 ).

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

7.0 R EFERENCES

Table 10 lists the sources ERG used along with their DCN and source flag (see Section 6.0 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 10

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

SGE00002 Volz, Conrad; Ferrar, Kyle; Michanowicz, Drew et. al. 2011.

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

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

Associated Media Composition in Colorado B X

SGE00006.A04 McElreath, D. 2011. Comparison of Hydraulic Fracturing

Fluids Composition with Produced Formation Water Quality Following Fracturing. C X

SGE00007.A13 Hayes, T. 2011. Characterization of Marcellus Shale and

Barnett Shale Flowback Waters and Technology Development for Water Reuse C XUOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 48

Table 10

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

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

- Continent

Water Management for Stimulation Operations B

SGE00011 Veil, John A. 2010. Water Mgmt Technologies Used by

Marcellus Shale Gas Producers. Prepared by Argonne National Lab. Prepared for U.S. DOE NETL. A X

SGE00064 Williams, John. 2011. Marcellus Shale

- Gas Development

and Water

- Resource Issues. USGS: New York Water Science Center. A X

SGE00070 Acharya, Harish; Matis, Hope; Kommepalli, Hareesh;

Moore, Brian; Wang, Hua. 2011. Cost Effective Recovery of Low

- TDS Frac Flowback Water for Re

- use. A X X

SGE00090 NYSDEC. 2011. Suppl. Generic Env. Imp. Statement on Oil,

Gas, & Soln. Mining Reg. Prgm. Prelim. Rev. Draft. A X

SGE00091 Rimassa, Shawn; Howard, Paul; Blow, Kristel;

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

SGE00110 Bruff, Matthew. 2011. An Integrated Water Treatment

Technology Solution for Sustainable Water Resource Management in the Marcellus Shale. A X

SGE00155 U.S. Energy Information Administration. 2010. Tight Sands

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

SGE00241 Rowan, E.L., et al. 2011. Radium content of oil and gas field

prod uction waters in the n o rth e rn App Basin. USGS Scientific Investigations Report 2011

– 5135. A X

SGE00275 U.S. EPA. 2012. Site Visit Report: Citrus Energy

Corporation Marcellus Shale Gas Operations. (January 22). A X

SGE00276 U.S. EPA. 2012. Meeting with XTO Energy, Inc. about

Unconventional Oil and Gas Sanitized. A X

SGE00280 U.S. EPA. 2013. Site Visit Report: Anadarko Petroleum

Corporation Marcellus Shale Gas Operations. (January 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, Thomas et al. 2012. Barnett and Appalachian Shale

Water Management and Reuse Technologies. RPSEA 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. C 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 POTWs C XUOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 49

Table 10

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

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

Technology Institute. B X

SGE00333 Horn, A. 2009. Breakthrough Mobile Water Treatment

Converts 75% of Fracturing Flowback Fluid to Fresh Water and Lowers CO2 Emissions. SPE

- 121104

- PP 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 James Welsh. Hydraulic Fracturing Regulatory Processes in

Louisiana. Louisiana Department of Natural Resources. A X

SGE00344 Haluszczak, L.O.; Rose, A.W.; Kump, L.R. 2012.

Geochemical Evaluation of Flowback Brine from Marcellus Gas Wells in Pennsylvania, USA. A X

SGE00345 Lewis, Aurana. 2012. Wastewater Generation and Disposal

from Natural Gas Wells in Pennsylvania. Duke University. B X

SGE00350 Stepan , D.J., et. al. 2010. Bakken Water Opportunities

Assessment

- Phase 1. Energy & Env Research Cntr, Univ of ND. Prepared for Nat'l Energy Tech Lab A X X

SGE00359 Robert Kimball. 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. RPSEA A X X

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

Systems for Handling Produced Water. Source Energy. C X

SGE00442.A06 Murray, K.E. 2013. Examining Water Production Volumes

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

SGE00465 Jean

- Philippe Nicot and Bridget Scanlon. 2012. Water Use

for Shale

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

SGE00480 Richard Luedecke. 2012. Energy Water Conservation &

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

SGE00486 U.S. 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. A X

SGE00507 Boschee, Pam. 2012. Handling Produced Water from

Hydraulic Fracturing. Oil & Gas Facilities. B X

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

Disposal (SWD) Wells as Part of the Shale Revolution. B X

SGE00518 Colorado Oil and Gas Conservation Commission (COGCC).

COGIS

- Production Data Inquiry. A XUOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 50

Table 10

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

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

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

SGE00555 New York State Department of Environmental Control

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

SGE00556 Nicot, Jean

- Philippe, et al. 2011. Current and Projected

Water Use in the Texas Mining and Oil and Gas Industry. 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

SGE00592 U.S. DOE. 2013. Water Issues Dominate Oil and Gas

Production. E&P Focus. (Fall). A X

SGE00607 U.S. EPA. 2012. Conference Call with Quicksilver

Resources, Inc. About Shale Gas Operations Sanitized. (October 11) A X

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

Wastewater Treatment and Related Modeling. (April 18) A X

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

Fayetteville Shale Gas Operations. Sanitized. A X

SGE00629 Warner et al. 2013. Impacts of Shale Gas Wastewater

Disposal on Water Quality in Western PA. Environmental Science & Technology 47(20):11849

– 11857 A X

SGE00632 Williams, John. n.d. The Marcellus Shale Gas Play:

Geology, Development, and Water

- Resource Impact Mitigation. USGS: New York Water Science Center. A X

SGE00635 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. Univ of TX at Austin. (September) A X

SGE00640 Mingazetdinov, Ildus. 2012. Predictions Of Produced Water

Quality And Quantity For Spatially

- Distributed Wells In Niobrara Formation B X

SGE00641 Nicot, Jean

- Philippe. 2013. Geographical, Geological, and

Hydrogeological Attributes of Formations in the Footprint of the Eagle Ford Shale. A X

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

and Intensity of Oil and Gas Recovery in Wattenberg field. (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 XUOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 51

Table 10

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

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

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

SGE00710 Slutz, J; Anderson, J; Broderick, R; Horner, P. 2012. Key

Shale Gas Water Management Strategies: An Economic Assessment Tool. (September 11). B X

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

of Completion Techniques in Five Emerging U.S. Shale Plays. (December). B X

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

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

SGE00731 Silva, J; Gettings, R; Kostedt, W; Watkins, V. 2013.

Pretreatment Targets for Salt Recovery from Marcellus Shale Gas Produced Water. A X

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

2013 Quarterly Horizontal Shale Production: 4th Quarter. X

SGE00774 Ziemkiewicz, P. 2013. Water Quality Literature Review and

Field Monitoring of Active Shale Gas Wells. (February 15). A X

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

Management. Water Management for Shale Plays Conference. (May 28). 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 NYSDEC. 1999. An Investigation of Naturally Occurring

Radioactive Materials (NORM) in Oil and Gas Wells in New York State. DEC Publication. A X

SGE00950 EERC (NGPWC) Bakken Water Opportunities Assessment

North Dakota Petroleum Council Annual Meeting September 2009. C X

SGE00951 NYSDEC. 2011. Supplemental Generic Environmental

Impact Statement (SGEIS) on the Oil, Gas, and Solution Mining Regulatory Program: Info Requests. A X

SGE00954 Palacios, Virginia. 2012. Baseline Groundwater Quality

Testing Needs in the Eagle Ford Shale Region April 2012 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

SGE00964 Ohio Department of Natural Resources (OH DNR). 2014.

2013 Quarterly Horizontal Shale Production: 1st Quarter. X

SGE00965 Ohio Department of Natural Resources (OH DNR). 2014.

2013 Quarterly Horizontal Shale Production: 2nd Quarter. X

SGE01028 PA DEP. 2015. Technologically Enhanced Naturally

Occurring Radioactive Materials (TENORM) Study Report. A XUOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 52

Table 10

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

SGE01165 Maguire

- Boyle, S.J. and Barron, A.R. 2014. Organic

compounds in produced waters from shale gas wells. Royal Society of Chemistry. A X

SGE01169 FracFocus. 2015. FracFocus Database. Accessed on July 22. A X

SGE01170 DrillingInfo, Inc. 2015. DI Desktop® March 2015

Download_CBI. B X

SGE01171 DrillingInfo, Inc. 2015. HPDI Data Coverage. (March 30). B X

SGE01172 OH DNR. 2015. Utica/Point Pleasant Shale Cumulative

Permitting Activity through 12/07/2013. Downloaded on 9/6/2015. Last updated on 8/29/2015. A X

SGE01175 Kansas Geological Survey. 2015. Horizontal or Slant Wells

in Kansas. Accessed on 9/9/2015. A X

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

SGE01181 ERG. 2016. Unconventional Oil and Gas (UOG) Drilling

Wastewater Memorandum A X

SGE01182.A03 ERG. 2016. Analysis of Pennsylvania Department of

Environmental Protection’s Oil and Gas Waste Reports

- Attachment 3

- Data Calculations. A X

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

Effluent Limitations Guidelines and Standards for Oil and Gas Extraction. A X X

SGE01189 NDIC. 2015. Basic Subscription Services Well Index.

Department of Mineral Resources, Oil and Gas Division. Last Accessed on 9/15/2015. A X

SGE01190 U.S. Energy Information Administration. 2015. Assumptions

to the Annual Energy Outlook 2015. A X

SGE01191 U.S. Energy Information Administration. 2015. Lower 48

States Shale Plays. Prepared by EIA Office of Oil and Gas. (April). A X

SGE01237 Ohio Department of Natural Resources (OH DNR). 2015.

2014 Quarterly Horizontal Shale Production: 1st Quarter. A X

SGE01238 Ohio Department of Natural Resources (OH DNR). 2015.

2014 Quarterly Horizontal Shale Production: 2nd Quarter. A X

SGE01239 Ohio Department of Natural Resources (OH DNR). 2015.

2014 Quarterly Horizontal Shale Production: 3rd Quarter. A X

SGE01240 Ohio Department of Natural Resources (OH DNR). 2015.

2014 Quarterly Horizontal Shale Production: 4th Quarter. A X

SGE01241 Ohio Department of Natural Resources (OH DNR). 2015.

2015 Quarterly Horizontal Shale Production: 1st Quarter. A X

SGE01242 Ohio Department of Natural Resources (OH DNR). 2015.

2015 Quarterly Horizontal Shale Production: 2nd Quarter. A X

SGE0 1259 USGS. 201 5 . USGS Produced Water Database Accessed in

September 2015

. A X

SGE0 1260 U.S. Geological Survey (USGS). 2014. National Produced

Waters Geochemical Database v2. 1 (Provisional). A X

SGE01262 Earthworks. 2015. Gaps in Water and Waste Reporting for

Oil and Gas Production: A Five State Review. B XUOG Produced Water Volumes and Characterization Data Compilation Memorandum

June 7, 2016 Page 53

Table 10

. UOG Extraction Wastewater Characteristics Data Sources

DCN Source Citation Source Flag a WW Volumes WW

Char.

SGE01334 ERG. 2016. Memorandum Providing a Crosswalk between

Tables and Figures in the Proposed and Final Technical Development Document for Effluent Limitations Guidelines and Standards for Oil and Gas Extraction

. A

-- --

a

— Source Flag A

— J ournal articles and documents prepared by or for a government agency (e.g., 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.

8.0 A TTACHMENTSA TTACHMENT 1: UOG PW D ATA C OMPILATION (DCN SGE01184 .A01 )A TTACHMENT 2: DI D ESKTOP L ONG

- TERM P RODUCED W ATER G ENERATION R ATES (DCN SGE01184 .A02 )A TTACHMENT 3: DI D ESKTOP L ONG

- TERM P RODUCED W ATER G ENERATION R ATES (DCN SGE01184 .A03 )A TTACHMENT 4: F RAC F OCUS F RACTURING F LUID V OLUMES (DCN SGE01184 .A04 )A TTACHMENT 5: F RAC F OCUS F RACTURING F LUID V OLUMES (DCN SGE01184 .A05 )A TTACHMENT 6: B AKKEN F LOWBACK R ECOVERY (DCN SGE01184 .A06 )A TTACHMENT 7: N EW M EXICO F LOWBACK R ECOVERY (DCN SGE01184 .A07 )A TTACHMENT 8: U TICA F LOWBACK R ECOVERY AND L ONG

- TERM P RODUCED W ATER R ATES (DCN SGE01184 .A08 )A TTACHMENT 9 : W YOMING F LOWBACK R ECOVERY (DCN SGE01184 .A0 9 )A TTACHMENT 1 0 : C ODELL

- N IOBRARA F LOWBACK R ECOVERY AND L ONG

- TERM P RODUCED W ATER R ATES (DCN SGE01184 .A1 0 )A TTACHMENT 1 1 : C OLORADO F LOWBACK R ECOVERY (DCN S GE01184 .A11 )A TTACHMENT 1 2 : UOG W ASTEWATER C HARACTERIZATION A NALYSIS (DCN SGE01184 .A 1 2 )A TTACHMENT 1 3 : UOG W ASTEWATER C HARACTERIZATION D ATABASE (DCN SGE01184 .A 1 3 )A TTACHMENT 1 4 : USGS P RODUCED W ATER E XCEL F ILE (DCN SGE01184 .A 1 4 )A TTACHMENT 1 5 : USGS P RODUCED W ATER D ATABASE (DCN SGE01184 .A 1 5 )A TTACHMENT 1 6 : ORD N ON

- CBI O PERATOR D ATA (DCN SGE01184 .A 1 6 )A TTACHMENT 17: WY OGCC C HARACTERIZATION D ATA (DCN SGE01184.A17)A TTACHMENT 18: WY OGCC E XCEL C ALCULATIONS (DCN SGE01184.A18)