### i 

# Oil and Natural Gas Sector: Standards of

Performance for Crude Oil and Natural Gas Production, Transmission, and

Distribution.

Background Supplemental Technical Support Document for the

Final New Source Performance Standards

### ii April 2012

Oil and Natural Gas Sector: Standards of Performance for Crude Oil and Natural Gas
Production, Transmission, and Distribution.

U.S. Environmental Protection Agency

Office of Air and Radiation
Office of Air Quality Planning and Standards

With technical support provided by:

EC/R, Incorporated

501 Eastowne Dr, Suite 250
Chapel Hill, North Carolina 27514

ICF International

9300 Lee Hwy
Fairfax, VA 22031

RTI International

3040 East Cornwallis Road

Post Office Box 12194
Research Triangle Park, NC 27709-2194

### iii DISCLAIMER

This report has been reviewed by EPA’s Office of Air Quality Planning and Standards and has been
approved for publication. Mention of trade names or commercial products is not intended to

constitute endorsement or recommendation for use.

### iv Contents

SUPPLEMENTAL TECHNICAL SUPPO RT DOCUMENT SUMMARY ................................. vi

1.0 EVALUTION OF THE EMISSION FACT OR FOR HYDRAULICALY FRACTURED

GAS WELL COMPLETIONS A ND RECOMPLETIONS .............................................. 1-1

1.1 Emission Factor Development .............................................................................. 1-1

1.2 Data Submitted Through NSPS Comments .......................................................... 1-6

1.3 Evaluation of Alternative Emissi on Factor Calculations ...................................... 1-8

1.4 Final Emission Factor .......................................................................................... 1-13

1.5 Summary of Evaluation ....................................................................................... 1-14

1.6 Statistical Analysis: Development of a Bayesian Posterior Interval for the Emission Factor for Hydraulically Fractured Well Completions ........................ 1-15

2.0 NSPS LOW PRESSURE COMPLETION THRESHOLD ............................................... 2-1

2.1 Overview ............................................................................................................... 2-1

2.2 Development of the Pressure Equation ................................................................. 2-2

2.3 Estimated National Impacts of Implementing the Pressure Equation ................. 2-16

2.4 Conclusions ......................................................................................................... 2-21

3.0 GAS WELL RE-FRACTUR E FREQUENCY .................................................................. 3-1

3.1 Revised Gas Well Re-Fracture Frequency Methodology ...................................... 3-1

4.0 NATIONAL IMPACT OF NSPS O OOO REQUIREMENTS ON GAS WELL

COMPLETIONS ............................................................................................................... 4-1

4.1 Summary of National Im pacts Methodology ........................................................ 4-1

4.2 Descriptions of Data Used in the Impacts Analysis .............................................. 4-3

4.3 Final Impacts Results ............................................................................................ 4-5

5.0 VOLUNTARY REDUCTIONS FROM GAS WELL COMPLETIONS WITH

HYDRAULIC FRACTURING ......................................................................................... 5-1

5.1 Number of Voluntary RECs .................................................................................. 5-1

5.2 Number of Completions Even ts Eligible for RECs.................................... 5-3

5.3 Fraction of Eligible Completions with Voluntary RECs ....................................... 5-6

5.4 New Source Completions and Recompletions with Voluntary Action ................. 5-7

6.0 CENTRIFUGAL COMPRESSOR IMPACTS ................................................................. 6-1

6.1 Projected Number of Affected Units ..................................................................... 6-1

6.2 Capital Costs .......................................................................................................... 6-1

6.3 Without Revenues from Additi onal Product Recovery ......................................... 6-2

6.4 With Revenues from Additional Product Recovery .............................................. 6-2

### v 6.5 Baseline Emissions from Wet Seal Cent rifugal Compressors in the Processing

Sector ..................................................................................................................... 6- 2

6.6 Emission Reduction for Wet Seal Centri fugal Compressors in the Processing

Sector ..................................................................................................................... 6- 2

7.0 UPDATE TO TECHNICAL SUPPORT DOCUMENT FOR PROPOSED STANDARDS

OF PERFORMANCE FOR CRUDE OI L AND NATURAL GAS PRODUCTION, TRANSMISSION, AND DISTRIBUTI ON – STORAGE VESSELS ............................. 7-1

7.1 INTRODUCTION ................................................................................................. 7-1

7.2 BASELINE EMISSIONS ...................................................................................... 7-1

7.3 COST OF CONTROL TECHNIQUES ................................................................. 7-1

7.4 REGULATORY OPTIONS AND NATIONWIDE IMPACTS OF

REGULATORY OPTIONS .................................................................................. 7-4

8.0 UPDATE TO TECHNICAL SUPPORT DOCUMENT FOR PROPOSED STANDARDS

OF PERFORMANCE FOR CRUDE OI L AND NATURAL GAS PRODUCTION, TRANSMISSION, AND DISTRIBUTI ON – EQUIPMENT LEAKS ............................. 8-1

8.1 INTRODUCTION ................................................................................................. 8-1

8.2 BACKGROUND ................................................................................................... 8-1

8.3 UNIFORM STANDARDS DATA AND METHODOLOGY .............................. 8-2

8.3 RESULTS ................................................................................................................. 5

APPENDIX A: SUPPLEMENTARY DATA FO R THE EVALUTION OF THE EMISSION

FACTOR FOR HYDRAULICALLY FRAC TURED GAS WELL COMPLETIONS AND

RECOMPLETIONS ......................................................................................................... A-1

APPENDIX B: SUPPLEMENTARY ANALYSES FOR LOW PRESSURE COMPLETION

THRESHOLD .................................................................................................................. B- 1

B.1 Derivation of Density fromthe Ideal Gas Law .................................................... B-1

B.2 Water Film Impact on Inne r Tubing Diameter ..................................................... B-3

B.3 Determination of Turbulent Flow ......................................................................... B-5

B.4 Alternative Method for Calculating the Comp ressibility Factor for Natural Gas B-7

APPENDIX C: COST AND EM ISSION SPREADSHEETS OF THE LDAR ANALYSES.... C-1

### vi SUPPLEMENTAL TECHNICAL SUPPORT DOCUMENT SUMMARY

This Supplemental Technical Support Docume nt (TSD) provides bac kground and technical analyses to support the final New Source Perf ormance Standards (NSPS) for limiting volatile organic compound (VOC) and sulfur dioxide (SO 2 

### ) emissions from the Oil and Natural Gas Sector. The standards were developed according to section 111(b)(1)(B) under the Clean Air Act, which requires EPA to review and revise , if appropriate, NSPS standards. The final standards were developed followi ng consideration of public commen ts received on the standards proposed on August 23, 2011 (76 FR 52738). Secti on 1.0 presents the de velopment of the emission factor for hydraulically fractured gas we ll completions and recompletions used in the NSPS regulatory impacts analysis, including a discussion of the methodology and the data sources. This section also provides an analysis of relevant data submitted with the public comments. Section 2.0 presents the derivation of an equation to determine the pressure threshold for a “low pressure” well. In Section 3.0, change s to the gas well refracture frequency estimates from the proposed NSPS to the final standards ar e summarized. Section 4.0 presents the impacts of regulating VOC emissions from new gas well completions following hydraulic fracturing where reduced emissions completions (RECs) are required. Section 5.0 details the analysis used to estimate the number of gas well completions with hydraulic fracturing voluntarily performed with capture and combustion equi pment in the year 2015. Section 6.0 presents an estimate of the impacts related to the regulation of centrifugal comp ressors and the data used in those estimates. Section 7.0 presents an analysis of impacts associated with regulat ory options for storage vessels. Finally, Section 8.0 provides the re sults of the equipment leak cost analysis for the NSPS using

emission factors and cost data from the Unifor m Standards for Equipment Leaks rule (40 CFR part 65, subpart J) that EPA pr oposed on February 24, 2012. Appendi ces contained at the end of this TSD provide supplemental information to the main chapters described above.

The following table presents a crosswalk betwee n the sections of the proposal TSD and the sections of this document that update the proposal TSD sections.

Proposal TSD Updated by Section in

this Document Section Number Section Title

1.0 New Source Performance Background N/A

2.0 Sector Description N/A

3.0 New Source Performance Review Process N/A

4.0 Well Completions and Recompletions 1.0, 2.0, 3.0, 4.0, 5.0

5.0 Pneumatic Controllers N/A

6.0 Compressors 6.0

7.0 Storage Vessels 7.0

8.0 Equipment Leaks 8.0

### 1-1 1.0 EVALUTION OF THE EMISSI ON FACTOR FOR HYDRAULICALY

FRACTURED GAS WELL COMPLETIONS AND RECOMPLETIONS

This section details the development of the emi ssion factor used in the NSPS regulation impacts analysis, including a discussion of the methodolog y and the data sources, and then provides detail on the analysis of data presented to EP A through the public comment period of the NSPS.

1.1 Emission Factor Development

1.1.1 Previous Estimates of Methane from Natural Gas Production

EPA’s Inventory of U.S. Greenhouse Gas Emissions and Sinks 1 

### methane emissions estimates for natural gas systems depend heavily on emissions factors from a 1996 EPA/GRI study. 2


### Hydraulically fractured gas well completions and workovers are a si gnificant proportion of completions and workovers today, but were not as common during the development of the 1996 EPA/GRI study. The study calculated an emission factor for gas well completions by making several key assumptions. These assumptions were based on the data and knowledge of industry practices available at the time but which are not appropriate for hydraulically fractured wells. These assumptions included:

• Emissions that occur during th e well completion are equal to one day of the average gas production rate per gas well in 1992 base d on the American Gas Association’s Gas Facts.

• All completion emissions are flared (re ducing the methane emissions from each completion by approximately 98 percent).

Since the publication of the 1996 EPA/GRI study, th e number of hydraulically fractured gas well completions has increased significantly to 9,000 hydraulically fractured wells completed annually according to the National Energy M odeling System’s (NEMS) models. Through

extensive interactions with o il and gas companies and industry experts and through a review of best available data, EPA became aware that the assumptions made in the 1996 EPA/GRI study did not accurately characterize methane emissions from hydraulically fractured gas wells. In particular:

• The 16.97 million cubic feet per year average gas produc tion rate in 1992, which GRI used as a surrogate for the average completion flow rate, includes a large number of marginal wells. Marginal low pressure wells have significantly less gas production than newly completed hydraulically fractured wells.

• Significant quantities of gas are produ ced during the completion process for a hydraulically fractured gas well, in partic ular during the flowback period. In 2004, companies began sharing information w ith EPA on voluntary activities to reduce emissions from hydraulically fractured gas well completions, referred to as Reduced Emission Completions. Companies reporte d that the extended flowback time (as compared to conventional completions) and increased volume of natural gas during the

1 http://epa.gov/climatechange/emissions/usinventoryreport.html

2 EPA/GRI. Methane Emissions from the Natura l Gas Industry. June 1996. Available at http://www.epa.gov/gasstar/tools/related.html

### 1-2 flowback period, made it cost-effective to bri ng portable equipment on-site to capture the increased natural gas for market. EPA currently assumes an average flowback period of 3 to 10 days for hydraulically fractured wells.

• Finally, through interactions with companies at EPA and industr y events as well as public data and experiences shared by the industry, EPA is aware that not all companies are flaring the flowback gas, contrary to the assumption in the 1996 EPA/GRI study. In fact, many companies are either capturing through reduced emissions completions (RECs) or venting the gas that occurs during the comp letion of hydraulically fractured gas wells.

Based on this information, and review of ava ilable data on emissions per completions from hydraulic fracturing, EPA has concluded that the emission factor for gas well completions from the 1996 EPA/GRI study no longer repr esents the diversity of gas well completion practices in use today, and the emission rates as sociated with these practices. On the basis of the available data reported by companies carry ing out hydraulic fracturing and RECs, EPA developed an emission factor specifically for gas well completi ons with hydraulic fracturing, as described in

the section below.

1.1.2 Emission factor for completions with hydraulic fracturing

In 2010, on the basis of information reported by co mpanies carrying out h ydraulic fracturing and RECs, EPA developed an emissi on factor specifically for hydra ulically fractured gas well completions. This factor was first used in the Technical Support Document for Subpart W of Part 98, GHG reporting rule, and also in the 199 0-2009 Inventory (publish ed in April 2011).

The emission factor for gas well completions with hydraulic fracturing was developed using four data sources, together representing data from over 1,000 well completions with hydraulic fracturing. These data were provided to EPA or its techni cal contractors by industry for presentation at Natural Gas STAR technol ogy transfer workshops from 2004-2007. For each data source, EPA calculated the average gas release per gas well completion. The data from these wells collectively indicate that the true average gas release rate for a hydraulically fractured well completion is substantially higher (greater th an two orders of ma gnitude) than the 1996 GRI/EPA emission factor that is applicable to conventional well comple tions. These data also indicate that there is a high degree of variability in gas re lease rates across hydraulically fractured well completions due to geology, technology and operating conditions. The four calculated averages were each then rounded to the nearest single significant digit to reflect the precision of these averages. The resulting emissi on factors from each of the four data sources were arithmetically averaged to determine the final emission factor for gas well completions with hydraulic fracturing.

As the variability was already reflected thr ough the rounding of the rate developed from each data set, EPA elected not to r ound the final average calculated fr om the four rates. Had EPA rounded the final number, it would be 9,000 Mcf per completion or 2% lower. If EPA had not

rounded the results of the initia l studies, the final average we ll emission factor would be 11,057 Mcf per completion, or 21% higher.

### 1-3 A detailed breakdown of each source and the calculation method to determine the emission

factor is shown in Table 1-1. The calculation is as follows:

completion Mcf completion Mcf

completion Mcf

completion Mcf

completion Mcf

175

, 9 4 000

, 20 700 000

, 10 000

, 6

= ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛



### Table 1-1: Summary of Data Sources Used fo r the Original EF (9,175 Mcf per completion)

Data Source Year(s) # of Wells Total Gas

Emissions (Mcf) Average Gas

Emissions Per

Completion (Mcf) Formation Type

Industry Data

Set #1 - 106 616,887 5,820 Tight Sands

Williams 2002 to 2006 1,064 26,014,00

0 24,449 Tight Sands

Devon 2004 30 357,000 11,900 Shale

Weatherford 2004 3 2,000 667 CBM

1.1.2.1 Industry Data Set #1

In 2004, an EPA technical contractor received a data set from a natural gas production company.

The data set included information on volumes of gas sold and flared from 106 completions at wells with hydraulic fracturi ng (see Appendix A). On the ba sis of this information, the

contractor calculated a na tional-level estimate of rec overable gas from completions 3 

### . In the original work to develop the factor, EPA used the national estimate of recoverable gas from completions and information on national well counts to calculate average potential emissions per

well. 4 

### The calculated results of average value of potential emissions per well, 5,815 Mcf per completion, was rounded to the nearest 1,000 Mcf per completion (one significant figure), equaling 6,000 Mcf per completion.

The gas producer has since provided EPA with th e detailed data set, after removing identifying information such as the geographic area and comp any name. EPA used this data set on number of completions, gas flared, and sold for each comp letion to calculate aver age potential emissions

3 Green Completions. Natural Gas STAR Producer’s Technology Transfer Workshop. September 21, 2004. <http://epa.gov/gasstar/workshops/techtransfer/2004/houston-02.html> Slide 4.

4 Appendix B of the Background Technical Support Document for Subpart W of the Greenhouse Gas Reporting Rule, available at http://www.epa.gov/climat echange/emissions/downloads10/Subpart-W_TSD.pdf

### 1-4 (5,820 Mcf per completion, which also rounds to 6,000 Mcf per completion). The detailed data set is shown in Appendix A.

1.1.2.2 Williams Data

Williams Inc. reported generating 26,014 MMcf of natural gas from 1,064 completions 5



### . Therefore,

[26,014 MMcf]*[1000 Mcf/MMcf] / [1064 comple tions] = 24,449 Mcf per completion

The 24,449 Mcf per completion was rounded to th e nearest 10,000 Mcf per completion, equaling 20,000 Mcf per completion.

1.1.2.3 Devon Data

Devon Energy provided EPA 6 

### with data from 30 wells with an average rate of 11,900 Mcf natural gas recovered and sold rather than vented. To calcula te a potential emissions rate from this data, EPA assumed that 90% of the natu ral gas vented was recovered. Therefore,

[11,900 Mcf/completion] / [90%] = 13,222 Mcf per completion

The 13,222 Mcf per completion was rounded to th e nearest 10,000 Mcf per completion, equaling 10,000 Mcf per completion.

1.1.2.4 Weatherford Data

Weatherford provided data from 3 well completions 7 

### . Those completions together captured 2 MMcf of gas. Again to calculate a potential em issions factor, EPA assumed that 90% of the natural gas released wa s recovered. Therefore,

[2 MMcf/completion]*[1000 Mcf/MMcf] / ([90%]*[ 3 completions]) = 740 Mcf per completion

The 740 Mcf per completion was rounded to the nearest 100 Mcf pe r completion, equaling 700 Mcf per completion.

5 EPA. Reducing Methane Emissions During Completion Operations . Natural Gas STAR Producer’s Technology Transfer Workshop. September 11, 2007. <http ://www.epa.gov/gasstar/docum ents/workshops/glenwood2007/04_recs.pdf> Slide 14.

6 Green Completions. Natural Gas STAR Producer’s Technology Transfer Workshop. September 21, 2004. <http://epa.gov/gasstar/workshops/techtransfer/2004/houston-02.html> Slide 13.

7 Green Completions. Natural Gas STAR Producer’s Technology Transfer Workshop. September 21, 2004. <http://epa.gov/gasstar/workshops/techtransfer/2004/houston-02.html> Slide 14.

### 1-5 1.1.3 Estimating Emissions from Completions with Hydraulic Fracturing

The 9,175 Mcf per completion emission factor re presents natural gas released from the completion of a hydraulically fractured natural ga s well (i.e., potential gas emissions from the completion process in the absence of controls to capture or flare the released gas). It is very important to note that in calculating total nati onal emissions from completions with hydraulic fracturing for the Inventory of U.S. Greenhous e Gas Emissions and Sinks, the EPA adjusts

calculated methane release for methane that is actua lly not emitted (i.e., that is instead flared or controlled with certain technologies and pract ices) due to both voluntary action and State regulations. EPA uses this approach across the nati onal inventory for many source categories,

and it is consistent with internati onally agreed guidance from the IPCC. 8 

### Specifically, the development of the national emissions estimat es for unconventional natural gas wells requiring hydraulic fracture involves the following key steps:

• Start with the unmitigated national emission factor (9,175 Mcf of gas per completion).

• Adjust this factor by the average methan e content of gas (on a regional basis).

• Multiply by the number of well completions and recompletions that involve hydraulic fracturing in each region, and then sum the re gional totals to calculate total unmitigated methane emissions from the completions and workovers with hydraulic fracturing in the

U.S.

• Calculate the amount of the methane that is not emitted, using data on voluntary action and State regulations in order to develop a mo re accurate picture of actual emissions from this source category and sector.

• Deduct the calculated amount of methane that is not emitted from the calculated total unmitigated methane emissions value to de velop the net emissions estimate that is

included in national emissions totals. The EPA notes that there has been a great deal of confusion about the Inventory methods for calculating net emissions. In the 1990-2010 Inventory of U.S. Greenhouse Gas Emissions and Sinks (public review draft), EPA has provided improved information on this methodology.

The NSPS analysis takes a similar approach in the development of its baseline emissions estimates, taking into account redu ctions from voluntary action and state regulations. Please see

the RIA for more information on baseline emissions estimates.

8 IPCC 2006, 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National Greenhouse Gas Inventories Programme, Eggleston H.S., Buendia L., Miwa K., Ngara T. and Tanabe K. (eds). Published: IGES, Japan.

### 1-6 1.2 Data Submitted Through NSPS Comments

This section describes well completions emissions information received through the NSPS public

comments. Table 1-2 summarizes this information.

Table 1-2: Summary of Data Presented to EPA through NSPS Comment Period

Data Source Year(s) # of Wells Total Gas

Emissions (Mcf) Average Gas

Emissions Per

Completion (Mcf) Formation Type

Noble Energy Unknown 5 16,800 3,360 Tight Sands

ConocoPhillips 2010 101 1,276,290 12,637 Tight Sands, Shale, CBM

URS Data 2011 98 71,948 734 Tight Sands,

Shale
BP 1 2007 50 30,000 600 CBM

BP 2 2007 18 16,938 941 CBM

La Plata CEAP Unknown Unknown Unknown 1,875 CBM

Southern Ute

Tribe Unknown Unknown Unknown 5,000 CBM

1.2.1 Noble Energy Data

In a comment submitted by Noble Energy for the NSPS 9 

### , Noble provided av erage emissions per completion for 2 vertical and 3 horizontal wells. These wells were hydraulically fractured and produced from tight formations. The average fr om all 5 wells was 3,360 Mcf per completion.

The emissions estimates were determin ed using a calibrated roots meter.

1.2.2 ConocoPhillips Data

In a comment submitted by Earthworks 10 

### , Earthworks provided a re ference to a presentation given by ConocoPhillips for a Natural Gas STAR Workshop in 2009. The presentation includes 101 wells in three different formation types. The average from all wells is 12,637 Mcf per completion.

9 http://www.regulations.gov/#!document Detail;D=EPA-HQ-OAR-2010-0505-4228

10 http://www.regulations.gov/#!document Detail;D=EPA-HQ-OAR-2010-0505-4275

### 1-7 1.2.3 URS Data

A comment submitted by Devon Energy 11 

### contains a study conducted by URS for ANGA. In the study, 7 companies submitted information relating to hydraulically fractured well completions at nearly 1200 wells. Of the 7 companies, 4 submitted emissions estimates for 98 well non-green completions (i.e., completions without RECs). Emissions estimates were not included for wells with RECs, which comprised 92% of the URS data set. For each of the 98 wells without REC completions, URS provided information on pressure , flowback duration, and choke size and used Equation W-11B from Subpart W of EPA’s Gr eenhouse Gas Reporting Rule to calculate the emissions from completions. Using this equa tion, and a number of simplifying assumptions, URS calculated an average emissions rate of 765 Mcf per completion.

The 765 Mcf per completion is an emissions av erage per completion for wells in each of 5 basins. The 765 Mcf per completion factor repr esents the simple average of the average

emissions calculated from the 5 basins. For th e calculations shown below, we have recalculated the rate per completion so that it is not weighted by basin, as the other da ta sets evaluated do not allow for separate estimates by basin. Instead, using the data from the 98 wells with emissions estimates, EPA calculated the average emissions rate of the data set to be 734 Mcf per completion.

In reviewing the data and URS’ use of the S ubpart W equation, it became apparent that the resulting flowrate from Equation W-11B was misinterpreted to resu lt in a flow rate at standard

conditions when it was in fact a flowrate at actual conditions. Converting from actual volume (actual conditions) to standard volume (standard conditions), whic h is the input intended to estimate emissions from gas well venting during completions and workove rs following hydraulic fracturing in Equation W-10A, EPA re-calculate d an average value greater than 50,000 Mcf per completion. This value is far higher than the value presented by URS (7 65 Mcf per completion) and values given in other data sets. EPA’s ev aluation shows that the URS study is significantly underestimating emissions by using the equation at actual conditions, however, due to highly conservative assumptions made by URS (e.g., 100% ga s in flowback instead of a mixture of gas and fluids, and maximum choke size and casing pressure), the reca lculated emissions average of over 50,000 Mcf per completion may also be an in accurate depiction of emissions. Given this uncertainty, EPA performed the analyses presen ted below both with (using the URS-calculated values per completion, averaged to 734 Mcf as noted above) and without the URS emissions estimates, for completeness and transparency.

1.2.4 BP

In a comment submitted by Earthworks9, the commenter referenced two BP presentations. The two data sets corresponded to we ll completions carried out in CBM formations. The first BP data set contained 50 well completions and had average emissions of 600 Mcf per completion. The second BP data set contained 18 well completi ons and had average emissions of 941 Mcf per completion.

11 http://www.epa.gov/quality/informationguidelines/documents/12003-attB.pdf

### 1-8 1.2.5 La Plata CEAP

In a comment submitted by Earthworks9, the commenter referenced a La Plata Climate and Energy Action Plan process in which two comp anies (BP and Red Cedar, the Southern Ute Indian Tribe’s gas company) estimated that green completions could recover 1,875 Mcf per completion in the San Juan Basin based on industry completion data.

1.2.6 Southern Ute Tribe

In a comment submitted by Earthworks9, the commenter referenced a figure from a Programmatic Environmental Assessment (PEA) for 80

‐ acre Infill Oil & Gas Development on

the Southern Ute Indian Rese rvation developed by Environ. The emissions estimate was 5,000 Mcf per completion.

1.3 Evaluation of Alternative Em ission Factor Calculations

In this section, EPA presents an analysis to determine whether or not the new information submitted through NSPS comments indicates a need to revise the emission factor used in the proposal, and to present and evaluate alternative emission factors.

To determine how the factor might change by including data received through the public comment period, EPA used the data submitted through NSPS comments (Table 1-2 above) in

combination with the data used for the original emission factor calculation (Table 1-1 above) to

calculate a number of alternative emission factors for consideration.

First, EPA developed two simple averages of the data: alternative factor 1, which is an average by well completion, and alternative factor 2, wh ich is an average by data source.

The data used to calculate alternative factor s 1, and 2, which includes the data used in the original emission factor and the data submitted through NSPS comments is presented in Table

1-3.

Table 1-3: Data Used for Alternative Factors 1 and 2

Data Source Year(s) # of Wells Total Gas

Emissions (Mcf) Average Gas

Emissions Per

Completion (Mcf) Formation Type

Industry Data

Set #1* Unknown 106 616,887 5,820 Tight Sands

Williams* 2002 to

2006 1,064 26,014,000 24,449 Tight Sands

Noble Energy Unknown 5 16,800 3,360 Tight Sands

### 1-9 ConocoPhillips 2010 101 1,276,290 12,637 Tight Sands, Shale, CBM

URS Data 2011 98 71,948 734 Tight Sands,

Shale

Devon* 2004 30 357,000 11,900 Shale

Weatherford* 2004 3 2,000 667 CBM

BP 1 2007 50 30,000 600 CBM

BP 2 2007 18 16,938 941 CBM

La Plata CEAP Unknown Unknown Unknown 1,875 CBM

Southern Ute

Tribe Unknown Unknown Unknown 5,000 CBM

* Denotes sources used for the origin al emission factor calculation.

1.3.1 Alternative Factor 1: Average by Well Completion

The first alternative emission factor assessed was calculated by summing the total emissions from all data sets and dividing by the total number of completions. The La Plata CEAP and Southern Ute Tribe data points cannot be include d when calculating emission factors using this method because these sources did not provide total emissions and total number of well completions. The resulting emission factor was about 20,574 Mcf per completion . Including the URS data, the calculated value is 19,256 Mcf per completion.

This method results in an emission factor heav ily affected by the number of well completions included in a given data set resu lting in bias for one formation type. Tight sands are over represented, as 86% of the well co mpletions in the data set were in tight sands, while nationally 26.5 percent of annual completions are tight sands (NEMS 2010). Further, one data source (Williams) accounts for 1,064 of the 1,377 well comple tions, which may bias the result towards the Williams data, which has an average emissions rate of 24,449 Mcf per completion.

1.3.2 Alternative Factor 2: Average by Data Source

The second alternative emission factor for asse ssment was estimated by performing a simple unweighted average of the average emissions per completion reported for each data source. This method calculated an average emission factor for each data source individually and then calculated a simple average of the 10 resulting emission factors. The average emission factors ranged from 600 Mcf per completion to 24,449 Mcf per completion. Of the 10 data sources, 3 corresponded to tight sands, 1 to shale, 5 to CBM, and 1 was a mix of all three formations. The

### 1-10 resulting emission factor was about 6,725 Mcf per completion . Including the URS data, the calculated factor is 6,180 Mcf per completion.

This method has the advantage of having no over-representation due to number of well completions included in a given da ta set resulting in bias for on e formation type. However, it does result in over-represe ntation of CBM completions due to the number of data sets including those types of completions (6 out of 10 data sources). In the U.S ., 26.9 percent of annual completions are CBM (NEMS 2010). It also results in underrepresentation of shale completions, as only 2 of the data sources included shale completions. In the U.S. 46.5% of annual well completions are in shale (NEMS 2010).

1.3.3 Alternative Factors 3 through 5

Next, a number of alternatives that weigh the fact or by formation type were developed. Based on the data EPA has evaluated, form ation type can greatly influen ce the volume of gas released per completion. Based on observations of the ava ilable data from the U.S. oil and natural gas industry, of the three formation t ypes included here, coal bed methane typically has the lowest volume of gas released per completion, and shale typically has the highest. As the national average gas release per completion will therefor e be influenced by the mix of completions nationally, here we examine factors that take th is mix into account. To develop these weighted factors, we disaggregated data sets that included more than one formation type. The Conoco Phillips data set included three formation types, and was split into three data sets, and the URS data included two formation types and was likewise split into two data sets. Table 1-5 presents this disaggregation.

Table 1-5: Data Used for Al ternative Factors 3, 4, and 5

Data Source Year(s) # of Wells Total Gas

Emissions (Mcf) Average Gas

Emissions Per

Completion (Mcf) Formation Type

Industry Data Set

#1* Unknown 106 616,887 5,820 Tight Sands

Williams* 2002 to

2006 1,064 26,014,000 24,449 Tight Sands

Noble Energy Unknown 5 16,800 3,360 Tight Sands

ConocoPhillips 2010 10 60,222 6,022 Tight Sands

URS Data 2011 41 16282 397 Tight Sands

ConocoPhillips 2010 83 1,200,000 14,458 Shale

### 1-11 Devon* 2004 30 357,000 11,900 Shale

URS Data 2011 57 55,666 977 Shale

Weatherford* 2004 3 2,000 667 CBM

BP 1 2007 50 30,000 600 CBM

BP 2 2007 18 16,938 941 CBM

La Plata CEAP Unknown Unknown Unknown 1,875 CBM

Southern Ute

Tribe Unknown Unknown Unknown 5,000 CBM

ConocoPhillips 2010 8 16,068 2,009 CBM

* Denotes sources used for the origin al emission factor calculation.

1.3.3.1 Alternative Factor 3: Weighting by 3 Formation Types Based on Production

Using all of the data for which we had inform ation on formation type, an emission factor for tight sands (9,913 Mcf per completion), an emission factor for shale (13,179 Mcf per completion), and an emission factor for CBM (1,849 Mcf per completion) were generated. 12 

### A

final emission factor was then determined us ing a weighted averag e based on ratios of production from each formation to the total production from CBM, shale, and tight sands (see Table 1-6). The resulting emission factor was about 9,984 Mcf per completion . Including the URS data, the calculated factor is 7,554 Mcf per completion.

This alternative factor has the advantage of ha ving no over-representation of a given formation type due to greater number of data sets or wells. This method recognizes within the calculation methodology that formation can be a significant variable affecting th e total emissions per completion. However, a ratio of gas producti on may not be a good surrogate for a ratio of completion flowback volumes. In addition, a rati o of gas production might not be representative of the current completions being carried out in each formation.

12 Including the URS, the calculated emissions rate for tight sands is 8,010 Mcf/completion and for shale is 9,111 Mcf/completion. The URS data set did not include data on CBM, so that rate is unaffected.

### 1-12 Table 1-6: Summary of Data Used fo r Weighting of Alternative Factor 3

Formation Type U.S. Gas

Production
(Mcf/year) Fraction of Average

Production Flow Rate
Tight Sands 6,287,544,084 0.49

Shale 4,656,526,998 0.37

CBM 1,773,088,295 0.14

U.S. Total Gas

Production 12,717,159,377 1.0

1.3.3.2 Alternative Factor 4: Weighting by 3 formation types, based on the number of completions for each formation type

The same calculated emissions rates for each of the three formation types used to calculate

Alternative Factor 3 were used to calculate A lternative Factor 4. A final emission factor was then determined using a weighted average base d on the number of well co mpletions carried out in each formation according to the NEMS models (see Table 1-7). The resulting emission factor

was about 9,263 Mcf per completion . Including the URS data, the value is 6,864 Mcf per completion.

Table 1-7: Summary of Data Used for We ighting of Alternative Factors 4 and 5

Formation Type U.S. Gas Completion

Counts % of Total

Tight Sands 2,393 26.5%

Shale 4,196 46.5%

CBM 2,426 26.9%
U.S. Total Gas Completions 9,015 100%

This alternative factor has the advantages of having no over-representation of a given formation type due to greater number of data sets, and that it represents current trends in the natural gas industry based on the formations being develope d. This method recognizes within the calculation methodology that formation can be a significant variable affecting th e total emissions per completion. This method also weighs by the numb er of completions by formation type, which is more closely corresponds to total completi on emissions per formation, than production by

formation.

### 1-13 1.3.3.3 Alternative Factor 5: Weighing by 2 form ation categories (CBM and tight sands/shale), based on number of completions in formation categories

As data for tight sands and shale showed simila r levels of emissions, EPA evaluated an option

that treated the two formation t ypes as one. To develop the fifth alternative emission factor for analysis, the data was first separated into one of two groups according to formation: tight/shale and CBM. An emission factor for tight sands/shale (11,025 Mcf per completion) 13 

### and an emission factor for CBM (1,849 Mcf pe r completion) were generated.

A final emission factor was then determined us ing a weighted average based on the number of well completions carried out in each forma tion according to the National Energy Modeling System (NEMS) models. The resulting emission factor was about 8,538 Mcf per completion

. Including the URS data, the fact or is 7,466 Mcf per completion.

This alternative factor has the advantages of having no over-representation of a given formation type due to greater number of data sets, and that it represents current trends in the natural gas industry based on the formations being developed. This method recognizes within the calculation methodology that formation can be a significant variable affecting th e total emissions per completion, but that emissions from tight sands and shale formations may not be significantly different. This method also weighs by the num ber of completions by formation type, which is more closely corresponds to total completi on emissions per formation, than production by

formation.

1.4 Final Emission Factor

The EPA evaluated all of the data (both data used to develop the original factor and data from the commenters) in several ways to determine wh ether an improved emission factor could be developed. Every calculation methodology considered had positive and negative aspects with respect to arriving at a single average emissions factor to represent U.S. flowback emissions following hydraulic fracture of a gas well. Exclud ing the URS data, 3 of the 5 analyses produced factors higher than the 9,175 factor, and 2 produced lower results. Including the URS data, 1 of the analyses produced a factor higher than 9,175, and 4 analyses produced factors lower than 9,175.

13 Including the URS data, this value is 9,969 Mcf/completion.

### 1-14 1.5 Summary of Evaluation

Table 1-11: Summary of Results

Alternative

Factor

Number Description Factor Value
(Mcf/completion)

1 Average by Well Completion 20,574

2 Average by Data Source 6,725

3 Weighting by 3 formation types based on production per formation type 9,984

4 Weighting by 3 formation types, based on the number of completions for each formation type 9,263

5 Weighing by 2 formation categories (CBM and tight sands/shale), based on number of completions in formation categories 8,538



### The alternative factors weighted by formati on type have the advantage of having no overrepresentation of a given formation type due to greater number of data sets or wells. These methods recognize within the calculation met hodology that formation can be a significant variable affecting the total em issions per completion. The factors weighted by formation type were very similar to EPA’s emission factor of 9,175.

The five different calculation methodologies incorporating new data submitted through NSPS

comments result in emission factors that fall with in the expected interval estimate calculated for EPA’s original factor in section 1.6 below. Additionally, EPA’s orig inal factor is closest to the results produced when formation type is taken in to account, which is a key factor in influencing

the emission rate. As a result of this anal ysis EPA concludes that, although it does have uncertainty, the original EPA emi ssion factor provides a valid central estimate of emissions from this source in the U.S. Therefore, EPA has d ecided to retain the data set and the methodology used to develop the original emission factor of 9,175 thousand cubic feet (Mcf) per completion.

EPA acknowledges that it did not ap ply a consistent approach to rounding of significant figures in each individual steps of the original calculation. To addr ess this inconsistency, EPA is making a minor revision by rounding the e nd result to 1 significant figure. The final emission factor is 9,000 Mcf per completion.

### 1-15 1.6 Statistical Analysis: Development of a B ayesian Posterior Interval for the Emission Factor for Hydraulically Fractured Well Completions

Overview EPA conducted a statistical analysis of the data and developed a Bayesian posterior interval to assess the validity of the emissi on factor for hydraulically fractured completions. This section describes that analysis.

Data Set for Analysis As described above, the development of the em ission factor of 9,175 Mcf per completion used data from four data sets, t ogether representing data from over 1,000 well completions with hydraulic fracturing. To calculate a robust interval estimate for the emission factor EPA used data on emissions reductions reported by industr y to EPA’s Natural Gas STAR program. The data set includes several years of data, and c ontains 56 data entries on reductions from over 9,000 completions at wells with hydraulic fracturing. This larger data set was able to provide a

robust interval estimate fo r the emission factor.

As will be shown in this section, the distributiona l characteristic of the Gas STAR data appeared

to be similar in nature to the data used to cal culate the emission factor. Based on these statistical similarities it is justifiable to use the Gas STAR data to construct prior distributions for purposes of improving the estimate of variance and interv al estimates centered on the emission factor. Specifically, the Gas STAR data is used to estimate the variance of the emission factor.

Gas Content The emission factor of 9,175 Mcf per completion re presents total potentia l gas emissions. The Gas STAR data represents potential methane emi ssions (i.e., a subset of the total potential gas emissions). To develop a meaningful compar ison for the purposes of this analysis, we’ve converted the 9,175 Mcf whole gas emission factor to a methane emission factor of 8,900 Mcf CH4 per completion, using a methane conten t value of 83.24% (ECR 2011) and the same averaging and rounding methodologies that were used in the calculation of the 9,175 factor. More detail is presented below.

Within Data Set Variation

Due to the nature of the data—data entries in Ga s STAR are aggregate, not at the well-level--a

within data set estimate of vari ance was unobtainable. All estimates of variance explored here are due to between data set variability. For th is reason, it is possible that the overall variance presented in this section is an underestimate of the true amount of variability. However, if the between source variability is significantly greater than the within source variability then the bias in the variance is likely to be small.

Bayesian Model

### 1-16 A relatively simple model was chosen for purposes of analysis 14 

### . The four observations of the

emission factors data are assumed to be normally distributed with a mean of ߤ and a known

variance of ߪ ଶ 

### set equal to the sample variance. Fr om prior knowledge, it is reasonable to

assume that the mean ߤ is normally distributed with known mean ߤ ଴ 

### and variance ߬ ଶ 

### . The mean of the prior distribution will be set to the mean of the sample, which is the current emission factor, converted to Mcf CH 4 

### per completion, of 8,900. As a result, the posterior distribution will be normal with a mean equal to the emission fact or (8,900) and variance that is a sum of inverse of the prior variance, ߬ ଶ 

### , and the inverse of the sample variance, ߪ ଶ 

### ݊ ⁄ . The sample size for the emission factor data set is 4. Therefore the pos terior variance of th e emission factor is:

ߪ

ாி ଶ


### ൌ 1 ቀ 1

߬ ଶ 

### ൅ 4

ߪ ଶ 

### ቁ

Note that the sample size is 4. The interval estimate will be based on the posterior distribution of

the mean.

Datasets

Emission Factor Data

Information from the 4 data sets used to calcula te the emission factor is shown in Table 1-8 below. The data sets together represent em issions calculated for over 1,000 well completions; however, not all of the data sets presented well-level information. As such, we were unable to analyze the within data set vari ance. The values presented below are the average emissions for

each data set. The column labeled ‘Whole Gas’ s hows the value used to develop the Mcf gas per completion value of 9,175. The column labeled ‘Modified’ is the Whole Gas column multiplied by the methane content correcti on factor of 0.8324. The final colu mn labeled ‘Rounded’ is the

values that are used to ca lculate the emission factor.

Table 1-8. Data Used to Calc ulate the Emission Factor

Data Source Whole Gas Modified Rounded

Weatherford 667 555 600

Industry Data Set #1 5,820 4,844 5,000

Devon 11,900 9,905 10,000

William 24,449 20,351 20,000

The average of the four rounded values is 8900 a nd the standard error is 4,168. Due to the small number of data sets (4) the c onfidence interval around the emissi on factor that is very wide.

14 Gelman, Andrew; Carlin, John B.; Stern, Hal S.; Rubin, Donald B. (2003). Bayesian Data Analysis, Second Edition.

Boca Raton, FL: Chapman and Hall/CRC. ISBN 1

‐ 58488

‐ 388

‐ X.

### 1-17 Using the standard distributional assumptions, th e 95% confidence interval based on the 4 data

sets is:

ݔ ഥ േ ݐ ଷ,.଴ଶହ ܵܧሺݔ ഥ ሻ



### where ݐ ଷ,.଴ଶହ 

### is a value from the T-distribution with 3 degrees of freedom. The values for ݔ ഥ and ܵܧሺݔ ഥሻ are given in Table 1-9. Using these values the 95% CI for the current emission factor is (- 8,510, 26,100). In the sections below the goal will be to obtain a more useful interval estimate

for the emission factor.

Table 1-9. Descriptive Statistics for Emission Factor Data



### Observations 4

Minimum 555
Maximum 20,351
Mean 8,900

Variance 6.95+07

Standard Error 4168.5

Gas STAR Data A key assumption for employing Bayesian analysis in this situation is that the data used to

calculate the emission factor shou ld have a similar distribution to the Gas STAR data. If this assumption appears to be reasonable then the Ga s STAR data can be used to create a prior

distribution for the emission fact or. In order to provide justif ication for this assumption the means, variances and ranges of the Gas STAR da ta are compared to the emission factor data.

The Gas STAR data set reviewed contained 55 data entries with information on completion type. The Williams observation, which was included in both the emission factor and in the Gas STAR data set, was removed from the Gas STAR data for purposes of calculating theses statistics

which are shown in Table 1-10. Inclusion of this observation would imply that the statistics calculated using the Gas STAR data are correlated with statistics from the emission factor data. This type of correlation would make th e analysis needlessly complicated.

Table 1-10. Descriptive Statis tics for all Gas STAR Data

Observations 55

Minimum 76
Maximum 65,322
Mean 9,174

Variance 1.25E+08

Mean The mean of the Gas STAR data is 9,174 Mcf CH4 per completion, which compares favorably to the converted methane emission factor of 8,900. Given the amount of variability in the data,

these values are statis tically equivalent.

Range The range of observations for the emission fact or data are (555, 20,351) and for Gas STAR the range is (76, 65,322). It should be noted that the second largest va lue in the Gas STAR data is

### 1-18 27,305. While the range of the Gas STAR data app ears to be greater than the emission factor data, it appears to be a function of one large obs ervation. If that observation is removed then the ranges of the two datasets are n early identical. The minimum for the emission factor data is 555. Of the 55 Gas STAR observations only 6 have a value less than 555. This implies that the value of 555 is not an expected minimum when onl y four observations ar e in the sample.

Variance of the Mean Assuming that the observations in the Gas ST AR dataset are indepe ndent and identically distributed, the variance of the mean is calculated by dividing the variance shown above by the sample size. Thus:

߬ ̂ ଶ


### ൌ 124733847

55 ൌ 2,267,888

The standard error of the mean is the s quare root of this value which is 1,506.

Corrected Standard Error for the Emission Factor

The estimate of the standard error for the emission factor ߪ ො

ாி 

### can now be determined using the

Gas STAR information and the emission factor data. This will be done by using Bayesian analysis. The Gas STAR data will be used to create a normal prior distribution for the mean emission factor value. This prior will has a mean of 8900 and variance ߬ ଶ 

### as defined above. The new variance of emission factor the will be determined using the following formula:

ߪ ො

ாி ଶ


### ൌ 1 ቀ 1

߬ ̂ ଶ 

### ൅ 4

ߪ ଶ 

### ቁ

where ݏ ଶ 

### is the variance of four emission fact or observations (6.95E7). This gives:

ߪ ො

ாி ଶ 

### ൌ 2,006,067

And

ߪ ො

ாி 

### ൌ 1416.3

The posterior distribution for the emissi on factor is then N(8,900, 2,006,067). The 95% prediction interval is

1416.5 כ 1.96 േ 8900

This gives bounds of (6,123, 11,676).

Summary of Results The 95% posterior interval for the converted methane emission factor of 8,900 Mcf methane per completion was determined to be (6,123, 11,676). As this is a Bayesian interval estimate the interpretation is there is a pr obability of 0.95 that the true em ission factor is between 6,123 and

### 1-19 11,676 given that the posterior distribution for the emissi on factor is N(8,900, 2,006,067).

The posterior interval shown above is calculate d for the methane emission factor of 8,900. It is likely that the emission factor of 9,175 Mcf whol e gas per completion, and the rounded factor of 9,000 Mcf whole gas per completion, would have a si milar interval estimate as that of the

methane emission factor. The center of the two in terval estimates would clearly be similar (8,900 versus 9,000 or 9,175). However, it is likely that the whole gas in terval would be wider as the variance would likely be larger. As a result, it is reasonable to assume that probability that the true emission factor for whole gas being cont ained in the interval 6,123 and 11,676 is similar to

0.95.

### 2-1 2.0 NSPS LOW PRESSURE COMPLETION THRESHOLD

2.1 Overview

Many commenters stated that not al l gas wells have the necessary re servoir pressure to flow at rates appropriate for transpor ting solids and liquid from a hy draulic fractured gas well completion into an imposed back-pressure. On e commenter provided an analysis recommending an applicability cut-off to exclude wells that do not have sufficient reservoir pressure to flow into a gathering line. In light of these comments this analysis evaluates the minimum flowback pressure determination to provide facilities subj ect to the well completion NSPS rule a means to determine when flowback gas at a facility has su fficient pressure to flow into a flow line, and when a facility does not have sufficient pressure, in which case the flowback gas must be

diverted to a combustion device. This sect ion describes the flowback condition being investigated by detailing the th ree flow regimes encountered dur ing the flowback event within the horizontal and/or vertical span of a well’s tubing:

2.2.1 Fracture Fluid Flow

After hydraulic fracture (frack) of a new or existing well, the we ll tubing is filled with frack

fluid which consists of thousands of barrels of injected liquid, i.e. wa ter (plus additives) and proppant, i.e. typically sand. This material must be evacuated to prepare the well for production. When the flowback is initiated, the vert ical column of frack fluid in the tubing is being acted upon by the forces of:

• the weight of the frack fluid column in the well tubing,

• friction from the tubing walls oppos ing the flow to the surface,

• the pressure of the gas in the formation,

• the pressure that the formation rock exerts on the frack fluid within the fracture zone(s),

• for energized fracks, the pressure exerted by the inert gas introduced into the reservoir

ahead of or with the frack water

• the pressure drop through surface equipment connected to the well which may include separators and temporary flow lines, and

• the backpressure of the gas gatheri ng destination of the flowback gas

During the initial flowback, virtua lly all of the flow output from the well consists of the frack material itself, rather than hydrocarbons from th e formation, given that the well tubing is filled with the frack fluid. During this initial flow of only frack fl uid, the pressure opposing the

direction of the flowback is hi ghest given that the vertical di stance of the tubing completely filled with frack fluid. For this analysis the density is assumed to be that of the water/sand that is present rather than with any vapor which has a lower density. As the frack fluid reaches the surface, it is typically direct ed to atmospheric pressure storage, typically in a tank.

2.2.2 Slug Flow

### 2-2 As the column of frack fluid flows to the surf ace, it is replaced with ga s (hydrocarbon from the formation and/or inert gas introduced during the frack) that enters the well tubing and flows upward towards the wellhead. The presence of the gas in the tubing, where gas has replaced liquids, decreases the weight of the material in the vertical column. As the slug flow reaches the surface, it is directed to temporary storage where the liquids portion of the slug flow is contained while the gas portion of the slug flow typically vents the atmosphere or a combustion device. Because the low density a nd viscosity of the flowback ga s relative to the frack fluid (water) there is substantial bypa ssing of gas and liquid such that the flowing fluid is multiphase slugs of gas and liquid.

2.2.3 Steady Flow of Vapor

As the frack fluid in the tubing is pushed out and replaced with vapor and frack fluid from the

fracture zone in the reservoir fo rmation, the initial steady flow of liquid transitions to slug flow of frack fluid and vapor. Over time (on the order of hours to days), the slug flow transitions to a steady flow condition where the frack fluid slugs in the tubing have been largely evacuated and there is a reasonably steady fl ow of a continuous vapor phase entraining droplets of water and/or condensate. For energize d fracks, this steady flow of vapor may, for a time, contain a significant percentage of the inert gas introduced into the formation during the frack, and over time, (on the order of hours) the steady flow of vapor transitions to primarily hydrocarbons from the formation. Depending upon the pressure of the gas after it flows to the wellhead and through any potential REC equipm ent, the steady flow of gas can be directed to surface equipment and then to a combustion device or to the flow line.

The minimum pressure equation developed in the ne xt section applies to th e steady flow of vapor condition encountered during the flowback since this is the flow that may be capable of being routed to the flow line (although an REC may be physically capable of diverting some gas from the slug flow condition into sales).

2.2 Development of the Pressure Equation

To determine whether the flowback gas at a facil ity has sufficient pressure to flow into a flow line, a model was developed to ca lculate the pressure for flowback gas exiting a well in steady flow, given its reservoir pressure and depth. The model requires inpu ts for the reservoir pressure and for the well vertical depth, wh ich are expected to be known be fore the flowback occurs. The model uses an established quantitative relatio nship for fluid flow during well cleanups to determine the gas velocity of a well during the steady flow condition of the flowback. The model then uses an energy balance to determine the pr essure drop based on the calculated velocity, and then the model accounts for pressure losses of surface equipment. The result of the model is a prediction of the pressure of the flowback gas immediately before it enters the flow line. The result can be compared to the actual flow line pressure available to the well. For wells with insufficient predicted pressure to produce into th e flow line, combustion can be specified as the control standard. For wells with sufficient pressure to produce into the flow line, gas capture in

combination with combustion can be specified as the control standard.

This section describes the steps taken to deve lop such a model in the following sections:

### 2-3 2.2.1 Pressure Drop Theory introduces the engineering principl es for the model and the model’s

structure.

2.2.2 Model Parameter Definitions and Assumptions defines all the parameters in the model and the associated assumptions.

2.2.3 Final Numerical Model combines the theoretical basis and the parameter definitions to create the complete model.

2.2.4 Linear Regression of Numerical Model Results develops a practical equation that can be used in the rule based on output s of the pressure drop model.

2.2.5 Incorporation of Pressure Threshold Equation into the Rule describes how the linear equation is used in the rule.

2.2.1 Pressure Drop Theory

The pressure of the flowback gas at the flow line during the steady flow condition is determined primarily by the reservoir pressu re and the depth of the well. St arting at the reservoir pressure, the pressure of the flowback ga s decreases due to energy losses as it travels thr ough the reservoir and into the tubing (including any horizontal segment), up the tubing, and through the surface equipment. This section describes the fundamental structure of the model, which is based on the pressure decrease as the gas travels through the reservoir, the tubing, and the REC equipment.

2.2.1.1 Pressure Decrease in Reservoir

The change in pressure as the gas travels th rough the reservoir is difficult to determine analytically because it varies fr om reservoir to reservoir and is dependent on the porosity and transport efficiency within the re servoir and near the wellbore. In addition, there is little public data available to determine the change in pressure from the reservoir to the bottom of the well at a national level. This analysis accepts the assump tion for the pressure change from the reservoir to the wellbore provided by the American Petr oleum Institute (API) in its comments on the proposed NSPS OOOO ruling 15 

### . API stated that, “...it is not unusual for the required reservoir pressure to be more than twice the bottom hole pressure...” Considering the API comment, this analysis conservatively assumed the reservoir pr essure to be twice the bottom hole pressure. Accordingly, Equation 2-2 determines the botto m hole pressure (pressure of the gas at the bottom of the tubing at the perforations) given the reservoir pressure by dividing the reservoir pressure by two.

ܲ ஻ு ൌ ܲ ோ 2

ൗ 

### (Eq. 2-2)

2.2.1.2 Pressure Decrease along Well Tubing

15 Comment submitted by Howard J. Feldman, Director, Re gulatory and Scientific Affairs, American Petroleum Institute (API) www.regulations.gov/#!doc umentDetail;D=EPA-HQ-OAR-2010-0505-4266

### 2-4 As the flowback fluid travels from the botto m of the tubing, through the tubing, and to the wellhead, the gas experiences furt her pressure losses. This pre ssure decrease can be modeled using an energy balance. Since energy must be conserved along the tubi ng (i.e. the energy into the system is equal to the ener gy out of the system), an energy balance can be constructed to characterize the energy acting on the fluid and the energy leaving the fluid moving within the tubing. This fundamental energy balance is s hown in Equation 2-3. The integration sign in Equation 2 indicates that the kinetic energy, potential energy, work, and friction losses are analyzed as they change from point 1, the bot tom of the tubing, to point 2, the surface. The kinetic energy, potential energy, work, and fricti on losses are then determined for each segment

and summed over the entire t ubing length. Figure 2-1, shows a vi sual depiction of the energy balance in Equation 2.



# ( ) 0 2

1 

## = + + + 

# ∫ dz F W PE KE (Eq. 2-3)

where,

KE = specific kinetic energy of the fluid, ft/s 2

PE = specific potential energy of the fluid, ft/s 2

F

= energy lost from the fluid due to friction, ft/s 2

W

= specific work performed by the fluid, ft/s 2

dz = height of an infinitesima l section of the tubing, ft



### The kinetic energy ( KE ) of the fluid is defined as ݑ ௗ௨

ௗ௭ 

### , where u is the velocity of the fluid, in feet

per second (ft/s), and du is the change in velocity of the fluid, in ft/s. The specific potential
energy ( PE ) of the fluid is defined as – g cos ߠ , where θ is the angle of the tubing with respect to the vertical (for a vertical tubing as assumed here θ = 0), in radians and g is gravitational

acceleration, in ft/s 2 

### . Specific work ( W ) is defined as

െ ଵ

ఘ ௗ௉

ௗ௭ 

### where dP is the change is pressure,

in absolute pounds per sq uare inch (psia), and ρ is the density of the fl uid, in cubic feet per pound

mass (ft 3 

### /lbm). Specific friction loss ( F ) is defined as ି௙௨ మ

ଶ஽ 

### where f is the Moody friction factor, u is the velocity of the fluid, in ft/s, and D is the diameter of the t ubing, in feet. Plugging these

definitions for KE

, PE

, W , and F into Equation 2 yields Equation 2-4.



# 0 2 cos 2

1 2



# = ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

−

− +

− 

# ∫ dz D fu g dP udu θ
ρ (Eq. 2-4)

Since this analysis is determining the pr essure of the gas at the flow line, the dP term is of most interest. Also, du is assumed to be negligible since the tubing has a constant cross sectional area Figure 2-1. Visual Represen tation of an Energy Balance Across a Vertical Tubing

1 2

KE F

dz PE W

### 2-5 and since dz is taken to be a small interval. This assumption is corroborated by the Natural Gas Engineering Handbook 16 

### and Perry’s Chemical Engineering Handbook 17 

### . Finally, the tubing is assumed to completely vertical, which means θ is equal to zero. Theref ore, Equation 3 is solved

for dP with ݑ݀ݑ and θ set equal to zero, yielding Equation 2-5. Equation 2-5 is the basis for the calculation to determine the change in pressu re from bottom-hole to the wellhead. Equation 4

can be found in the Natural Gas Engineering Handbook and Perry’s Chemical Engineering

Handbook

. 

# ∫ ∫ ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

+

− = 2

1 2

1 2



# 2 dz

D fu g dP ρ ρ (Eq. 2-5)

Equation 4 is a differential equa tion governing the pressure change of a fluid over a length of vertical well tubing. As shown in Appendix B.1, the density of the fluid, a mixture of natural gas, water, and sand, is a function of the temperature and pressure of the fluid, which change as the fluid moves up the tubing. In a ddition, the velocity is a functi on of the density. Based on these factors, an analytical solution of Equation 2-5 is not possible. Instead the equation is solved numerically with the known values of the para meters in a preceding fluid segment used to calculate the values in the next segment. This numerical integration proc ess yields the pressure drop across the tubing.

Numerical integration is an approximation method which involve s dividing a tubing of a given length into a finite number of segments, applying Equation 2-5 to each segment, and solving for the pressure exiting each segment in sequence beginning from the bottom. This is shown in Equation 2-6 and Figure 2-2. The pressure exitin g a segment is assumed to be the pressure entering the following segment. The pressure exiti ng a segment is also used to determine the density and velocity of the natural gas in the fo llowing segment. The pressure change from the first segment at the bottom of the well to the last segment as the surface is equal to the pressure drop over the entire tubing length, as shown in Equation 2-7. Numerical integration is an approximation method used to solve complex inte grals, which approaches the true integral solution as the height of each segment ( z i +1 

### – z i 

### ) or dz approaches zero.

16 Guo, B. Ghalambor, A. (2005) Natural Gas Engineering Handbook . Gulf Publishing Company. pg. 52.

17 Perry, R.H. (1963). Perry's Chemical Engineers' Handbook (4 th Edition). McGraw-Hill. Eq uation 5-58. pg. 5-23, Covert Fanning f to Moody f.

### 2-6 

# ( )

i i i MPi

MPi i i 

### z z D fu g P P

− ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

+

− = + + 1 2

1 

### 2 ρ ρ (Eq. 2-6)



# ( ) 

# ∑

= + 

### − ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

+

− = n

i i i i MPi

MPi BH WH 

### z z D fu g P P

0 1 2



### 2 ρ ρ (Eq. 2-7)

where,

P i +1 = Pressure fluid exiting segment i , in psia

P i

= Pressure of fluid entering segment i , in psia

n = number of segments

( z i +1 - z i ) = height of segment i or length of tubing divided by n , in feet

ρ MPi = density of the multiphase fluid, in pounds per cubic feet

P WH = pressure of fluid at the wellhead

P

R = bottom hole pressure, pressure of the fluid at the perforations



### Equation 2-6 is solved n times (i.e., for each segment) to determine the pressure drop across a tubing with a given length and bottom hole pr essure as shown by the summation term in Equation 2-7. Section 2.2 defines each parameter in Equation 2-6 and Equation 2-7 in order to

solve for P i +1 

### and subsequently P WH



### .

2.2.1.3 Pressure Decrease along REC Equipment

The pressure of the flowback gas decreases fu rther as it passes through the reduced emission completion recovery equipment and/or other su rface equipment after exiting the wellhead but before entering the flow line that leads to sales and/or the gas gathering sy stem. This decrease in pressure from surface equipment is small compared to the decrease occurring as the gas flows from the reservoir to the wellhead. This analysis a ssumes that the ratio of the pressure before the REC equipment (the wellhead pressure) and the pr essure after the REC e quipment (the flow line pressure) is constant at 1.01. Th erefore, given the wellhead pre ssure, the pressure immediately

before the flow line can be de termined using the Equation 2-8.

ܲ

௅ ൌ ܲ ௐு 1.01 ൗ 

### (Eq. 2-8)... ...

1 2

( z i+1 – z i ) i = n

i = 1 i = 2 i = 3

P i P i +1 Figure 2-2. Visual Representation of the Numerical Integration of a Vertical Tubing

### 2-7 where,

P L = the pressure of the fluid immediately before the flow line

P WH = pressure of fluid at the wellhead



### 2.2.2 Parameter Definitions and Assumptions

This section defines the parameters in Equations 2-6 and 2-7 to solve the pressure drop across each segment in the numerical integration describe d previously. The key parameters in Equations 2-6 and 2-7 are the density of the moving fluid ρ , the velocity of the fluid u , the Moody friction

factor f , and the inner tubing diameter D . The methodology to determine a value for each of these parameter is discussed in the sec tions below. The nomenclature fo r all the variables discussed is

at the end of each section.

2.2.2.1 Defining Fluid Density

The fluid inside the well tubing dur ing the steady flow regime is a mixture of natural gas, water, and sand. This analysis assumes that the multiphase fluid acts like a single phase fluid within each segment ( z i +1 

### – z i 

### ) and has a density equivalent to the weighted average of the densities for each of the components. This assumption allows for the use of the Tuner Equation, explained in section 2.2.2 for determining the velocity of th e fluid travel up the we ll bore. Equation 2-9 shows how the density of the mixture is calculat ed based on the densities of the natural gas, water, and sand weighted by their volume percent. 

# ( ) ( )
liquid sand sand water water liquid gi MPi 

## f f f f ρ ρ ρ ρ + +

− = 1 (Eq. 2-9)

The density of the fracture sand, ρ sand 

### , is assumed to be that of silica (i.e. SiO 2 

### ), the primary constituent of sand typically us ed to fracture gas wells. As Industrial Minerals states “Frac sand must be >99% quartz or silica [SiO 2 

### ].” 18 

### The fraction of sand in the water sand mixture ( f

sand 

### ) was assumed to be five percent by volume base d on expert judgment. Th e fraction of water and sand in the flowback fluid ( f

liquid 

### ) was assumed to be 5 percent by volume. Equation 2-10, the derivation of which is shown in Appendix B.1, shows that the density of the natural gas in the gas-water- sand mixture is determined using the pressure at segment i , the molecular weight of natural gas ( MW ), the compressibility factor ( Z i 

### ), the gas constant ( R ), and average fluid temperature ( T ). 

# ( )

RT Z

MW P

i

i gi 

## = ρ (Eq. 2-10)

The molecular weight ( MW ) of the natural gas was assume d to be 16 pounds per pound-mole (lb/lb-mol) representing the molecular weight of methane, the primary constituent of natural gas.

18 Zdunczyk, M. (2007) “The Facts of Frac” Industrial Minerals. Jan. 2007

<www.indmin.com/Article/1913170/The-facts-of-frac.html>

### 2-8 The natural gas compressibility factor for a given well segment i ( Z i 

### ) determined in this analysis using the Brill and Beggs correlation 19 

### . A second correlation, the Pitzer correlation 20 

### , was also performed to calculate a compressibility factor for each well segment for validation purposes,

and the two correlations were f ound to agree within 10 percent fo r pressures 3000 psi or less. A more detailed investigation of alternative met hods for calculating the comp ressibility factor can be found in Appendix B.4. The compressibility fact or accounts for the deviation of a gas from the characteristics of an ideal gas. The compressibi lity factor is a function of the pressure of the gas, temperature of the gas, and the composition of the gas. In th is analysis, the compressibility factor was determined for each segment using the pressure at each segment, the average temperature of the fluid, and the average CO 2 

### , H 2 

### S, and N 2 

### composition of the gas. The CO 2 

### , H 2 

### S, and N 2 

### composition in the gas was determined using a technical memo published in the NSPS OOOO rule making docket titl ed “Composition of Natural Gas for Use in the Oil and Natural Gas Sector Rulemaking.”

The average temperature ( T ) of the fluid was assumed to be 200 °F based on expert judgment.

This was held constant over the entire numerical integration. The gas constant ( R) is universal and is equal to approximately 10.73 ft 3 

### psia °R − 1 

### lb-mol − 1



### .

Table 2-1 summarizes the values selected to dete rmine the density of the flowback fluid for each

segment

.

Table 2-1. Summary of Parameters to determine Flowback Fluid Density

Parameter Description Method Value

P i pressure of gas Calculated by Equation 5 Varies for each segment

MW molecular weight of the gas Assumption 16 lb/lb-mol

T temperature of the gas Assumption 200 °F

Z

i compressibility factor of the

gas at P i and T Brill and Beggs

Correlation Varies for each segment with pressure ( P i )

R universal gas constant Universal constant 10.73 ft 3 psia °R − 1 lb-mol − 1

ρ MPi density of the flowback fluid, pounds per cubic feet Calculated by Equation 8 Varies for each segment with pressure ( P i )

ρ sand density of proppant, pounds per cubic feet Assumed to be same as pure silica (SO 2 ) 165 lbm/ft 3

ρ water density of water, pounds per

cubic feet Standard density

of H 2 O at STP 62 lbm/ft 3

ρ gi density of gas at P i and T, pounds per cubic feet Calculated by Equation 9 Varies for each segment with pressure ( P i )

f

water fraction of water, by volume,

in water-sand mixture Assumption 95%

19 

### Brill, J. P., and H. D. Beggs. "Two-Phase Flow in Pipes." INTERCOMP Course, The Hague,

1974.

20 J.M. Smith, H.C. Van Ness, M.M. Abbott. (2005). Introduction to Chemical Engineering Thermodynamics

. McGraw-Hill.

### 2-9 f

sand fraction of sand, by volume,

in water-sand mixture Assumption 5%

f

liquid fraction of water-sand mixture in fluid, by volume,

in flowback fluid Assumption 5%



### 2.2.2.2 Defining Fluid Velocity

The velocity of the fluid in each segment of the tubing is determined assuming the operator needs to maintain sufficient flow to clean up the well of the water and proppant mixture. This is determined using the entrained dr op model developed by R.G. Turner 21 

### specifically with well cleanup in mind. This model, henceforth referred to as the Turner veloc ity model, determines the minimum gas velocity needed to lift fluid of a known density from inside a well bore. The Turner velocity model was adapted in this analysis to determine the minimum velocity needed to lift flowback material out of the well, where all of that flowback material was conservatively assumed to have the density of the most dense component, which in this case is the sand. This adapted Turner velocity model is shown in Equation 2-11.



# ( )

2 1 4 1 4 1 4 1



### 3

. 1

gi d gi sand

i 

### C u

ρ ρ ρ σ

−

= (Eq. 2-11)



### Equation 2-11 determines the minimum velocity to lift a droplet of th e flowback material assuming the density of the droplet is equivalent to that of sand. The surface tension coefficient ( σ

) and drag coefficient ( C d



### ) in Equation 2-11 are assumed to be the same assumed by R.G. Turner for water since we expect flowback wa ter to collect around the sand particles during the cleanup. R.G. Turner also adjusts the veloc ity calculated by the equation upward by 20% to match field data; this analysis accepts this ad justment which is already incorporated into Equation 2-11.

Since the density of the gas ( ρ gi 

### ) changes for each tubing segment in the numerical integration, the minimum gas velocity also ch anges for each step in the nume rical integration. The surface tension coefficient ( σ ) and drag coefficient ( C d



### ) remain constant.

Table 2-2. Summary of Parameters to determine Flowback Fluid Velocity

Parameter Description Method Value

u i Turner velocity, minimum gas velocity needed to lift a droplet Calculated by Equation 10 Varies for each segment with density ( ρ gi ) and pressure ( P i )

σ surface tension of water, dynes per centimeter Accepted value

from R.G. Turner 60 dynes/cm

21 Turner, R. G. et. al. Analysis and Prediction of Minimum Flow Rate for the Continuous Removal of Liquids from

Gas Wells . Journal of Petroleum Technology. Nov. 1969. Equation 4, pg. 1476

### 2-10 C

d drag coefficient of water Accepted value

from R.G. Turner 0.44

ρ sand density of proppant, pounds per cubic feet Assumed to be same as pure silica (SO 2 ) 165 lbm/ft 3

ρ gi density of gas at P i and T, pounds per cubic feet Calculated by Equation 9 Varies for each segment with pressure ( P i )



### 2.2.2.3 Inner Tubing Diameter

The inner diameter of the tubi ng was taken to be 2 and 7/8 th 

### inches which is a common value for gas wells. The inner tubing diameter remains cons tant over the entire numerical integration. An additional investigation was conducted to determine if the functional diameter, through which the completion fluid would flow, is smaller than the inner tubing diameter due to significant water plating on the walls of the tubing. It was determined that with a 5 percent fraction of liquid in the flowback fluid, the thic kness of the film of water plating the inner tubing wall is at the most 0.035 inches (which is mu ltiplied by two to account for both endpoints of a line passing through the cente r of the tubing cross section). Since the film of water plating the inner tubing wall is at the most only 2.5% of the tubing diamet er it was concluded that the effective tubing diameter was the same as the inne r diameter of the tubing. This calculation is shown in Appendix B.2.

Table 2-3. Summary of Parameters to determine the Tubing Diameter

Parameter Description Method Value

D Inner tubing diameter, inches Assumption 2.875 inches



### 2.2.2.4 Defining Friction Factor

The Moody friction factor is a unitless constant that accounts for the friction experienced by the moving fluid in the tubing. The Moody friction factor was determ ined assuming turbulent flow, which is the case for gas wells, a nd a correlation equation in the Natural Gas Engineering

Handbook . Appendix B.3 discusses further how the tu rbulent flow assumption is valid for gas

wells. The Nikuradse 22 

### friction factor correlation used in this analysis fo r turbulent flow in rough pipes, shown in Equation 2-12, requires the roughness factor and the tubing diameter to determine the Moody friction factor. This an alysis assumes 0.0001 inches for the average roughness. The Natural Gas Engineering recommends using a value of 0.006 inches for the roughness of tubing pipes if no information is available 23 

### . However, since the inner tubing wall will likely be plated with water, the roughness experienced by the gas/water interface is much less than the roughness of the inner tubing wall. Since this analysis also estimates a constant tubing diameter, discussed further below, the fr iction factor remains constant over the entire numerical integration, the value of which is shown in Equation 2-12.

22 Guo, B. Ghalambor, A. (2005) Natural Gas Engineering Handbook.Gulf Publishing Company. pg. 54, Equation

4.10.

23 Guo, B. Ghalambor, A. (2005) Natural Gas Engineering Handbook.Gulf Publishing Company. pg. 204

### 2-11 

## ( ) 00989

. 0

875

. 2 0001

. 0 2 log 2 74

. 1 1

2 log 2 74

. 1 1 2 2



### = ⎥ ⎥ ⎥ ⎥

⎦ ⎤

⎢ ⎢ ⎢ ⎢

⎣ ⎡

⎟ ⎠ ⎞ ⎜ ⎝ ⎛

− = ⎥ ⎥ ⎥ ⎥

⎦ ⎤

⎢ ⎢ ⎢ ⎢

⎣ ⎡

⎟ ⎠ ⎞ ⎜ ⎝ ⎛

− =

D f

ε (Eq. 2-12)

Table 2-4. Summary of Parameters to determine the Moody Friction Factor

Parameter Description Method Value



### f Moody friction factor,

unitless Calculated by Equation 11 0.00989

ε roughness of inner tubing wall, inches Assu mption 0.0001 inches

D Inner tubing diameter,

inches Assumption 2.875 inches

2.2.3 Final Numerical Model

The complete model to determine the pressu re immediately ahead of the flow line ( P

L 

### ) of a gas well during its steady flow phase of a cleanup af ter a hydraulic fracture, given its reservoir pressure ( P

R 

### ) and well depth ( L ) is depicted in the block flow diagram in Figure 2-3. First, the reservoir pressure and well depth are inputted. Next, the bottom-hole pressure ( P

BH 

### ) is determined from the reservoir pressure using Equation 2-7, and the well depth is divided into segments for the numerical integration. The number of segments ( n) equals the number of steps taken in the numerical integr ation; this analysis uses n =2,000 steps. The bottom-hole pressure is used to determine the compressibility factor of th e natural gas for the first step in the numerical integration ( Z i 

### ). Next, the density of the natural gas ( ρ gi 

### ) is determined for the first step in the numerical integration using th e bottom-hole pressure and the co mpressibility factor, using Equation 2-10. The density of the natural gas is used to determine the velocity of the gas ( u i 

### ) using the Turner veloci ty model in Equation 2-11 and the density of the flow back fluid ( ρ MPi 

### ) accounting for water and sand using Equation 2-9. Finally, the veloc ity of the gas and density of

the flow back fluid are used to determine the pressure of the gas exiting the first segment ( P i+1 

### ) using Equation 2-6. The pressure of the gas exitin g the first segment is then set equal to the pressure of the gas entering the next segment a nd the process above is repeated until the sum of the each segment’s height is equal to the well de pth. The pressure of th e gas exiting the last segment is equal to the wellhead pressure ( P WH 

### ). Finally, the wellhead pressure is used to determine the pressure immediately befo re the flow line using Equation 2-8.

### 2-12 Input Reservoir Pressure ( P

R 

### ) and

Well De p th ( L )

Calculate the Compressibility

Factor Z i 

### = f ( P i 

### )

Calculate the Natural Gas Density ( ρ gi 

### = f

( P i



### , Z i 

### )) (E i 9)

Calculate the Multiphase Density ( ρ MPi 

### = f

( ρ g i 

### ))

Calculate the Turner Velocity ( u i 

### = f

( ρ g i 

### ))

Calculate new Pressure ( P i+1 

### )

from z i 

### to z i+1 

### and set as P i 

### (Equation 5) Set initial pressure

ܲ

஻ு 

### ൌ ܲ ோ 

### 2

ൗ ൌ ܲ ௜



### Does ݅ ൌ 2000 

### ? No

i = i Yes

Output Wellhead

Pressure ( P i 

### = P WH 

### ) Calculate the pressure immediately before flow

line ( P

L 

### ) (Equation 7) Declare well tubing segments (n) of equal length and begin at the bottom-most segment Figure 2-3. Block Flow Dia g ram of the Model used to Det ermine the Pressure Immediatel y Ahead of the Flow Line, for a Hydraulically Fractured Gas Well Completion Flowback in the Steady Flow Condition

### 2-13 2.2.4 Linear Regression of Numerical Model Results

A linear regression was used to develop a simplified linear equation that yields similar line pressures outputs as the model d escribed above for a given well depth and reservoir pressure. Two steps were taken to arrive at the linear pressure threshold equation in the NSPS OOOO ruling using the results of the num erical model described above.

2.2.4.1 Generate Line Pressures using Numerical Model

First, the numerical model was run for variou s plausible combinations of well depths and reservoir pressures. Well depths ranging from 50 0 feet to 20,100 feet in increments of 400 feet and reservoir pressures ranging from 100 pounds per square inch absolute (psia) to 9,850 psia in increments of 250 psia were input ted into the numerical model to determine a line pressure for each combination of well depth and reservoir pre ssure. The depth and pressure increments used to generate the matrix of test cases are differe nt than the numerical integration increments

discussed in section 2.3.3. The matrix of test cases yielded about 2,000 numerical model runs with calculated flowback gas pr essures after exiting surface equipm ent varying from 3 psia to 4,827 psia.

2.2.4.2 Regress the Line Pressure Outputs from the Numerical Model

Second, a regression was developed based on th ese 2,000 numerical model runs. Some model run flowback gas pressure outputs were low, and some were high, as described in the previous section. Two options were evaluated on how to conduct the regression. One option was to develop a regression over the entire range of mode l runs so that the st andard error would be minimized equally across the range. The second op tion was to select a sub set of the range in which to regress, so that the sta ndard error is minimized in that region of interest. The region of interest in this analysis was the line pressur es outputted by the numerical model less than 1,000 psia. The regression was performed on line press ures less than 1,000 psia because most flow

lines that will receive flowback b ack are at less than 1,000 psia. Subsequently, the standard error of the correlation was minimized for line pressure s less than 1000 pisa. There were 418 model runs with line pressures less than 1,000 psia . These model runs were regressed against the reservoir pressure and well depth to generate a simple linear equation that estimates the line pressure of a well given its rese rvoir pressure and well depth. Th e resulting regression equation is shown in Equation 12.

ܲ

௅ ൌ 0.445 ൈ ܲ ோ െ 0.038 ൈ ܮ ൅ 67.578 

### ) Eq. 2-13)



### This regression is an approximation of the numer ical model results for line pressures less than 1,000 psia and therefore has an associated erro r when estimating line pressures. The regression analysis yielded a standard error of 24.3 ps ia for line pressures less than 1,000 psia, which means the average deviation between the line pressure determined by Equation 12 and the line pressure determined by the numerical model is 24. 3 psia for line pressu res less than 1,000 psia. Since the regression was performe d for line pressures less than 1,000 psia, the standard error increases as the resulting line pressures increase above 1,000 psia.

### 2-14 The coefficient of determination ( R 2 

### ) is a parameter that quantifies the fit of the regression. The

coefficient of determination indicates how we ll the linear regression equation approximates the model runs regressed. A coefficient of determination equal to one indicates th at the line perfectly fits the regressed data, whereas co efficient of determination valu es less than one indicate a less than perfect fit. The regression performed in th is analysis has an R 2 

### value of 0.992 for flow line pressures less than 1000 psia.

Figure 2-4 

### compares the line pressures as determined by the numerical model and the linear regression equation. On the x-axis of

Figure 2-4 

### is a selection of the 2,000 model runs in the region of interest, each assigned a number, representing a combination reservoir pressure and well depth that was inputted into the numerical model and the linear regression equation. For each combination of reservoir pressure and well depth, the numerical model and lin ear regression equation outputted a flow line pressure, which is plotted on the y-axis in

Figure 2-4 

### . The blue diamonds represen t the numerical model line pr essures and the red squares represent the linear regression line pressures. Wh ere the red squares and blue dots seem to overlap indicates the numerical model and the li near regression equation outputted similar flow line pressures for the same reservoir pressure and well depth inputs. Conversely, where the red squares and blue dots deviate significantly indicates the numer ical model and the linear regression equation outputted different flow lin e pressures for the same reservoir pressure and well depth inputs.

### 2-15 Figure 2-4. Comparison between Line Pressures fr om the Linear Regression and Numerical Model



### Figure 2-4 

### shows how for the same reservoir pressure and well depth, Equation 2-8 correlates

well with the numerical model fo r line pressures less than 1,000 psia but has some deviation from the numerical model at line pressures greater than 1,000 psia. This analysis accepts the decrease in accuracy for line pressu res above 1,000 psia because actual flow line pressures above 1,000 psia are uncommon, so that at pressures of this magnitude it is expected that flowback gas can enter most flow line systems.

Equation 2-13 indicates that when the reservoir pressure is zero and the well depth is zero the line pressure is 67.5784, which is not intended to have a physical meaning given this is a

correlation rather than the model itself. A linear regression is an approxima tion that has inherent uncertainty in modeling the line pressure at a gi ven depth and reservoir pressure. Therefore, since the regression is already an approximation, th is analysis does not use a zero-intercept at the cost of not fitting the numerical model results the best.

2.2.5 Incorporation of Pressure Threshold Equation into the Rule ‐ 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000

1 101 201 301 401 501 601 701 801LinePressure(pisa)

Model Run f (Reservoir Pressure, Well Depth) Numerical Model Linear Regression

### 2-16 The Final NSPS OOOO Rule includes Equation 2- 13 for operators to determine if they are required to combust flowback gas or perform g as capture plus combustion. Operators will input the reservoir pressure and vertical well depth for their new source gas well with hydraulic fracturing into Equation 2-13 and determine a calcu lated pressure of the gas immediately before

it would be routed to the flow line. If the calculated line pressu re is greater than the actual line pressure to be used by the operator, then the rule requires natural gas from the completion flowback to be captured in comb ination with combustion. If th e calculated line pressure is less than or equal to the actual line pressure to be used by the operator, th en the rule requires the natural gas from the completion flowback to be sent to a combustion device. The rule instructs operators to round the result of th e linear equation to th e nearest 10 psi to re flect the appropriate precision of the equation given how pressure setti ngs vary within a gathering line. Rounding to the nearest 100 psia would be too coarse since gathering line pressures ar e typically on the order of hundreds of psia, and rounding to the nearest one psia is too precise gi ven the sensitivity of

the model.

2.3 Estimated National Im pacts of Implementing the Pressure Equation



### As part of the NSPS proposal rulemaking proc ess, the EPA assessed the regulatory impacts of the proposed NSPS OOOO. This section describes the potential effect of implementing the pressure determination equation shown in Equation 2-13 to the national impacts. To determine the impacts of implementing a pres sure equation, three di fferent investigations were carried out. The investigations diffe red in the methodology and data used. All investigations employed Equation 2-13 to calculate the pressure of the flowback gas as it exits

the well.

For these analyses, a line pressure of 500 psia was assumed. If the calculate d pressure of the well exceeded 500 psi, then the well was considered to be captured by the regulation. This assumption

was used due to the lack of av ailable gathering line pressures by producing areas in the U.S. and the understanding that such pressures typically range from 80 to 500 psia based on expert judgment. Depending on the producing area gath ering line pressures will differ. The line pressure of 500 psia is therefore a conservati vely high value of pressure in any field. The three different investigations and the final conclusions drawn from the impacts estimates are

listed below and discussed in the rest of this section:

2.3.1 Impacts Based on 2008 Well Completions uses characteristics of well completions from

2008 in all formations.

2.3.2 Impacts Based on All Completions from 2000 – 2010 uses characteristics of well completions from 2000 to 2010 in all formations.

2.3.3 Impacts Based on Individual Basins or Formations uses characteristics of well completions carried out in specific basins or formations.

2.3.1 Impacts Based on 2008 Well Completions

The data used for this first investigation is an output from an HPDI database query (HPDI is a data service company supplying products that aggregate U.S. production data). The query

### 2-17 provided the total depth and the fo rmation type (tight gas, shale, and coal bed methane) of all new gas wells in 2008 (where formation type was determined based on an assessment of each

well’s location and other characteri stics). Using the total depth a nd an expert assumption of the pressure gradient per unit of distance for each fo rmation type, the bottom-hole pressure could be estimated. Table 2-5 summarizes the pressure gradients used.

Table 2-5. Pressure Gradients for each Formation Type

Formation Type Pressure Gradient (psi per vertical foot)

Gas Shale 0.7 Tight Gas 0.7

CBM 0.465



### The bottom-hole pressure—calculated using the pressure gradients listed above—and the total depth for each new gas well in 2008 was entered into Equation 12. The resulting pressure was compared to an assumed flow line pressure of 500 psia. If the calculated pressure was greater than 500 psia, the well was considered to be capable of complying with the REC requirements of

the rule.

This investigation led to the conclusion that approximately 90% of well completions would be able to overcome a flow line pressure of 500 ps ia. The remaining 10% had an estimated pressure below 500 psia, according to the equation and parameters used. Figure 2-5 illustrates this

distribution.

Figure 2-5. Distribution of 2008 Gas Wells Above and Below the 500 psi Flow Line Pressure

0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 20,000NumberofGasWellsin2008 Above Pressure of 500 psi

Below Pressure of 500 psi

### 2-18 This investigation did not make any distinctions for exploratory and delineation wells. It includes all new gas wells in tight, shale, and CBM formations in 2008.

2.3.2 Impacts Based on All Completions from 2000 – 2010

The data used for this second investigation al so originated from an HPDI query. The query provided the total depth and the fo rmation type (tight gas or shal e) of all gas wells that began producing from 2000 to 2010. Using the total depth and an assumption of the pressure gradient per unit of distance for each formation type as shown above in Table 2-5, the bottom-hole pressure could be estimated.

The bottom-hole pressure—calculated using the pressure gradients listed above—and the total depth for each gas well that began producing from 2000 to 2010 were entered into Equation 2- 13. The resulting pressure was compared to an assumed flow line pressu re of 500 psi. If the calculated pressure was greater than 500 psia, the well was co nsidered to be capable of complying with the REC requirements of the rule.

This investigation led to the conclusion that approximately 98% of well completions would be able to overcome a flow line pressure of 500 ps i. The remaining 2% had an estimated pressure below 500 psi, according to the equation and pa rameters used. Figure 2-6 illustrates this

distribution.

Figure 2-6. Distribution of 2000 to 2010 Gas Wells Above and Below the 500 psi Flow Line Pressure



### This investigation did not make any distinctions for exploratory and delineation wells. It includes all gas wells in tight and shale formations that began producing sometime between 2000 and

2010. 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000NumberofGasWellsfrom2000to2010
Above Pressure of 500 psi

Below Pressure of 500 psi

### 2-19 2.3.3 Impacts Based on Individual Basins or Formations

The data used for the third investigation origin ated from a variety of references including the Pennsylvania Department of Environmenta l Quality, the Wyoming Department of Environmental Quality, oil a nd gas service providers, and the Department of Energy 24 

### . The data collected from these references were reservoir pre ssures and well depths that were then inputted directly into Equation 2-13.

Several references provided a multitude of values for reservoir pressure and/or well depth. Therefore, within a given formation, this invest igation paired the lower reservoir pressures with the lower depths, the average reservoir pressu res with the average depths, and the higher reservoir pressures with the deeper depths to assess the impacts. For this investigation, the selection of pr oduction areas represented by the researched data

included:

• Marcellus shale

• Barnett shale

• Eagle Ford shale

• Haynesville shale

• Powder River Basin

The summary of the findings from this investigat ion are summarized in Table 2-6. N/A indicates that the researched data did not provide mu ltiple values for reservoir pressure and depth.

Table 2-6. Summary of Calculated Flow Line Pressures from Individual Basins

Region Formation Type Bottom-Hole Pressure (psia) Total Depth (ft) Eq. 12 Calculated Flow Line Pressure (psia)

Marcellus

(Lower Bound) Gas Shale 1,700 3,000 710

Marcellus

(Average) Gas Shale 4,000 7,000 1,582

Marcellus

(Upper Bound) Gas Shale 5,760 12,000 2,175

Barnett

(Lower Bound) Gas Shale 2,750 5,000 1,101

24 Table 3.4 of http://treichlerlawoffice. com/radiation/HillNY.pdf, Table 2 of http://www.sooga.org/studies/Marcellus%20Shale%20Decline%20Analysis%20-%202010%20- %20Brandon%20Baylor.pdf, http://www.t ransformsw.com/papers-and-presentations/studies.html#Barnett, Table A6 (pg 212) Reservoir Pressure Profile on pg 50 (Fig 2-12) of http://www.fe.doe.gov/programs/oilgas/p ublications/coalbed_methane/PowderRiv erBasin2.pdf, Tables 2-4 and 3-13 (Additional depths in Tables 3-3 to 3-11) of http://www.fe.doe.gov/programs/oilgas /publications/coalbed_methane/PowderRiverBasin2.pdf, page 6 of http://www.halliburton.com/pub lic/solutions/contents/Shale /related_docs/ H063771.pdf, http://www.transformsw.com/papers-and-pr esentations/studies.html#Eagle Ford

### 2-20 Barnett

(Average) Gas Shale 4,000 7,500 1,563

Barnett

(Upper Bound) Gas Shale N/A N/A N/A

Eagle Ford

(Lower Bound) Gas Shale N/A N/A N/A

Eagle Ford

(Average) Gas Shale 5,200 11,500 1,945

Eagle Ford

(Upper Bound) Gas Shale N/A N/A N/A

Haynesville

(Lower Bound) Gas Shale 5,690 16,600 1,969

Haynesville

(Average) Gas Shale 8,500 12,000 3,394

Haynesville

(Upper Bound) Gas Shale N/A N/A N/A

Powder River

Basin

(Lower Bound) CBM 165 500 122

Powder River

Basin

(Average) CBM 490 1,250 238

Powder River

Basin

(Upper Bound) CBM 2,161 5,270 829



### Based on the results summarized above, it is possible to draw the following conclusions:

• Most of the wells in Marcellus, Barne tt, and Haynesville would be capable of overcoming a flow line pressure of 500 psia based on the pressure model developed in

this section.

• The average gas wells in Eagle Ford woul d be capable of overcoming a flow line pressure of 500 psia based on the pressure model developed in this section.

• The average gas wells in the Powder Rive r Basin would not be able to overcome a flow line pressure of 500 psia based on the pr essure model developed in this section.

Some wells in these basins would be capable of overcoming such a pressure as evidenced by the upper bound for the Powder River Basin.

### 2-21 2.4 Conclusions



### This analysis examined the pressure drop situat ion for the steady flow condition of a flowback after a hydraulic fracture, for a variety of well reservoir pressures and depths. A mathematical model describing well cleanup is appropriate to describe the diversity of conditions in hydraulically fractured gas wells. This model a pproach accounts for the range of conditions including well depth and reservoir pressure to more accurately depict the flowback pressure immediately before the flow line. The model acknowledges that a number of factors influence the pressure of the flowback g as and represents the effects of those factors us ing fluid flow equations paired with the best available parame ters or assumptions based on expert judgment. Other factors that may determine when to vent, combust, and/or capture are gas combustibility, fire hazards, and other fi eld parameters, however, these were not incorporated into this model.

Given the very limited data on actu al flow line pressures, the na tional impacts were determined based on a characteristic 500 psia flow line pressu re which is expected to be a maximum value for most situations. When using available actual field data with Equation 2-13, the result was

determined to be reasonable. Based on the limite d research into flow line pressures, this analysis expects from a national impacts perspective that about 90 percent of annu al affected facilities will be required to do gas capture in combinati on with combustion with provisions for venting.

### 3-1 3.0 GAS WELL RE-FRACTURE FREQUENCY



### This section summarizes changes to the gas we ll refracture frequency estimates from the proposed NSPS rule to the final rule. The NSPS proposed rule estimated the number of existing natural gas wells that are fract ured each year (i.e., refractur ed or recompleted) using an assumption from a publically available study 25 

### that estimated wells were refractured on average every 10 years (i.e., 10% of the total fractur ed gas well count is the number of gas well recompletions with hydraulic fracture in a give n year). In response to comments, the EPA has reevaluated this assumption. This review includ ed an evaluation of all comments received and

other information available to EPA through the development process for the annual estimates in the Inventory of U.S. Gr eenhouse Emissions and Sinks.

3.1 Revised Gas Well Re-Fracture Frequency Methodology



### Comments received on the proposed rule suggested that the number of wells refractured each year is less than EPA’s estimates. Comments stated that the number of hydraulically fractured gas wells recompleted per year is less than EPA’s estimate, ranging from 1 percent to 5 percent. No new data was provided speci fic to hydraulically fractured wells. One commenter cited a 1996 Gas Research Institute study 26 

### , which the commenter stated shows a refracture rate of 2 to 3 percent. Another commenter pr ovided records for 2008, 2009, a nd 2010 showing the number of producing gas wells, the number of gas we ll completions, and the number of gas well recompletions. In both of these cases, the data set includes both wells that were and were not hydraulically fractured, and did not distinguish between the two; therefore, it is not possible to break out the specific number of wells that were refractured.

In the evaluation of comments received, EPA cons ulted other data available to the Agency. This

data included two sets of data provided by two separa te industry representatives through the development process for annual estimates in th e Inventory of U.S. Greenhouse Emissions and Sinks, and are shown below. A petroleum and natura l gas industry entity (Entity X) provided the data shown in Table 3-1. Entity X provided th e number of operating gas wells in all states associated with this entity except those in Alask a and Hawaii, the total number of fractured stimulation jobs per year, the number of initial stimulations completed per year, and the number of fractured stimulation jobs conducted each ye ar on previously fractur ed stimulated wells (referred to in Table 3-1 as the numbe r of workovers per year). The term fractured stimulated

workovers was defined by Entity X as existing fractured gas wells re-stimulated with fracturing after 30 or more days of the initial fracture stimulation. Entity X averaged the number of operating gas wells and number of workovers per years from 2004 to 2010 then divided the averages to yield the re-fractured frequency per year as a percen tage of the number of operating gas wells, which was 0.27%. Therefore, the aver age re-fracture frequency for Entity X is 0.27% ranging from 0.50% in 2006 to 0.11% in 2010.

25 ARI/ICF (2008) Greenhouse Gas Life-Cycle Em issions Study: Fuel Life-C ycle of U.S. Natural Ga s Supplies and International

LNG . Prepared for Sempra LNG. < http://www.adv-res.com/pdf/ARI_LCA_NOV_10_08.pdf >

26 

### Assessment of Technology Barriers a nd Potential Benefits of R estimulation R&D for Natural Gas Wells”, Final Report, GRI- 96/0267, July, 1996.

### 3-2 Another petroleum and natural gas entity (Entit y Y) submitted the data shown in Table 3-2. Entity Y provided its number of produced gas we lls that have been completed with hydraulic fracturing, the number of gas wells that were re-completed using hydrau lic fracturing, and the percent of unconventional gas wells recomplete d with hydraulic fracturing for 2008, 2009, and 2010. The percent of unconventional gas well recompleted with hydraulic fracturing is equivalent to the percentage of gas wells that are re -fractured annually. The average re-fracture frequency for Entity Y from 2008 to 2010 is 0.61% and ranges from 0.8% in 2008 to 0.4% in

2010.

These two new data sources (submitted by Entity X and Y) and comments received on the proposed rule show a refracture frequency rate well below the 10% rate EPA used in the proposal. Based on analysis of this data and co mments received, the estimate used in the final rule impacts analysis is 1%.3-3Table 3-1. Workover Frequency for EachYear from 2004 to 2010 from Entity X

### 3-4 Table 3-2. Workover frequency for each year from 2008 to 2010 from Entity Y

### 4-1 4.0 NATIONAL IMPACT OF NSPS OOO O REQUIREMENTS ON GAS WELL

COMPLETIONS

4.1 Summary of National Impacts Methodology



### This section summarizes the approach for estimati ng the impacts of regul ating volatile organic compound (VOC) emissions from new gas well completions following hydraulic fracturing where reduced emissions completions (REC) are re quired. A description of the data and how it was used is provided. A simila r procedure as the one shown he re was used to estimate the impacts from recompletions following hydraulic fracturing and for the portion of affected

facilities where combustion is used for VOC cont rol instead of the comb ination of combustion and gas capture. Below is the list of steps ta ken to estimate each aspect of the impacts.

Estimate Emissions from Representative Individual Source



### 1. Develop a methane emission factor for hydr aulically fractured well completions (see
section 1.0 of this TSD)

2. Develop a conversion of mass of methane to mass of VOC (see separate docket memo:
Composition of Natural Gas for Use in the Oil and Natural Gas Sector Rulemaking)

Estimate Reductions from Representative Individual Source



### 1. Determine the control efficiency of implementing a REC (see separate docket memo:
Percent of Emissions Recovered by Redu ced Emission Comple tions, May 19, 2011)

2. Multiply the control efficiency by the VOC emissions from a representative source

Estimate the Cost of Compliance for Representative Individual Source



### 1. Determine average cost per day of a REC (see Section 4.4.2.3 of Proposal Technical
Support Document)

2. Determine average duration of REC in days (see Section 4.4.2.3 of Proposal Technical
Support Document)

Estimate the Cost-Effectiveness of VOC Control



### 1. Divide the reductions from a representative s ource by the cost for a representative source

Estimate Total Emissions from All Hydr aulically Fractured Gas Well Completions



### 1. Estimate the number of gas well co mpletions in a re presentative year

2. Multiply the number of gas well completions by the representative emissions from an

individual source

Estimate Total Reductions from All Hydraulically Fractured Gas Well Completions



### 1. Estimate the number of gas well co mpletions in a re presentative year

2. Multiply the number of gas well completions by the representative emissions reductions

from an individual source

### 4-2 Estimate Total Cost of Compliance for All Hy draulically Fractured Gas Well Completions



### 1. Estimate the number of gas well co mpletions in a re presentative year

2. Multiply the number of gas well completions by the cost of compliance for a
representative individual source

Figure 4-1 illustrates the gene ral process by which each aspect of the impacts was determined.

Methane Emission

Facto r Conversion of

Methane to VOC

VOC Emissions per Gas Well Completion REC Control Efficiency

VOC Reductions per Gas Well Completion Average Cost of REC per Day Average Duration

of RECs

Cost of REC per Well Completion Cost-Effectiveness of

VOC Control

Total VOC

Reductions Total Cost of Compliance

Total VOC

Emissions Number of Hydraulically

Fractured Gas Well Completions per year 

### Figure 4-1: Flow Diagram of Impacts Estimations

### 4-3 4.2 Descriptions of Data Used in the Impacts Analysis



### This section describes the data used for the impacts calculations. The data is also discussed in related docket memos and in the proposed TSD. The list of the data is:

• Methane emission factor for hydraulica lly fractured gas well completions

• Conversion of mass of me thane to mass of VOC

• REC control efficiency

• Average cost of REC per day

• Revenues from natural gas product recovery

• Average duration of RECs

• Number of hydraulical ly fractured gas well completions per year

4.2.1 Methane Emission Factor

The emission factor for gas well completions with hydraulic fracturing was developed using four data sources, together representing data fr om over 1,000 well completions with hydraulic fracturing. The data included tight sands form ations, shale formations, and coal bed methane (CBM) formations.

EPA evaluated both data used to develop the or iginal factor and data received through comments in several ways to determine whether an impr oved emission factor coul d be developed. As a result of this assessment, the EPA concludes that, although it does ha ve uncertainty, the original EPA emission factor provides a vali d central estimate of emissions from this source in the U.S. Therefore, the EPA has decided to retain the da ta set and the methodology used to develop the original emission factor for well completions

For more information on the development of the original emission factor and the evaluation of data submitted through NSPS commen ts, please see the section 1 of this Background Supplemental Technical Support Document titled “Evaluation of the Emission Factor for Hydraulically Fractured Gas Well Completions and Recompletions.”

4.2.2 Conversion of Mass of Methane to Mass of VOC

A conversion of mass of methane to mass of VO C was determined using composition data from 9 different references. Based on this data, it was possible to generate an average composition profile for produced gas, and subsequently, a ratio of mass of meth ane to mass of VOC. For more information regarding the development of this ratio as well as the raw data on which it is based, please see the memo from EC/R to Bruce Moore titled “Composition of Natural Gas for use in the Oil and Natural Gas Sector Rulemaking”.

4.2.3 REC Control Efficiency

### 4-4 Based on the results reported by 4 different Natu ral Gas STAR Partners who performed RECs, it was possible to estimate a representative contro l efficiency of using RECs. The companies provided both recovered and total produced gas, allowing for the cal culation of the percentage of the total gas which was recovere d. This estimate was based on data for more than 12,000 well completions.

4.2.4 Average Cost and Duration of RECs

The average cost and duration of RECs was obtai ned from data also shown in the Natural Gas STAR Lessons Learned document titled “Reduced Emissions Completions for Hydraulically

Fractured Natural Gas Well s” and is available at: http://epa.gov/gasstar/documents/reduced_emissions_completions.pdf . The impacts calculations use the cost per day for gas capture and the duration of gas ca pture along with a setup/takedown/transport cost and a flare cost to represent the total cost . The cost is then annualized across the time horizon under study. Th e average cost and duration information is

also covered in the TSD.

4.2.5 Revenue from Recovered Products

The costs were depicted in tw o different ways: without accoun ting for the value of the product recovered as a result of controlling VOC, and with the revenue from recovered products. To estimate the revenue from recovered products, th e estimated value of the recovered gas was added to the estimated value of the recovered condensate. 90% of the gas emitted (ie 90% of the emission factor per completion event) was depict ed as being captured and sold (see separate

docket memo: Percent of Emissions Recovere d by Reduced Emission Completions, May 19, 2011). This saved gas was multiplied by a charac teristic gas price of $4 per Mcf gas. A characteristic amount of gas conde nsate was determined to be 34 ba rrels per completion, and this number of barrels was multiplied by its char acteristic market value of $70 per barrel.

4.2.6 Number of Hydraulically Fract ured Gas Well Completions per Year

The number of hydraulically frac tured gas well completions was estimated using the National Energy Modeling System analysis consistent with the Annual Energy Outlook 2011 Reference

Case. It is estimated that th ere would be 11,403 gas well comple tions in tight, shale, and CBM formations. From this total, three deductions were made:

1. The first deduction was for wildcat and delineation wells

a. 446 well completions

b. According to Annual Energy Outlook 2011 Reference Case

2. The second deduction was for RECs alre ady required by state regulations

a. 1,644 well completions

b. 15 percent of gas well completions (aft er subtracting wildcat and delineation
wells)

c. Explained in Section 4.3.3 of Pr oposal Technical Support Document

3. The third deduction was for low pressure wells

### 4-5 a. 931 well completions

b. 10 percent of gas well completions (after subtracting wildcat and delineation gas
wells and the gas well completions alre ady controlled by state regulations)

c. Based on the analysis conducted in Section 2.0 of this TSD

4. The fourth deduction was for completi ons performed with voluntary RECs

a. 4,275 well completions

b. 51 percent of gas well completions (after subtracting wildcat and delineation gas
wells, the gas well completions already controlled by state regulations, and low
pressure completions)

c. Based on the analysis conducted in Section 5.0 of this TSD

Table 4-1 summarizes the breakdown of the estimated number of gas well completions.

Table 4-1: Number of Hydraulically Fractured Gas Well Completions

Source Required to perform RECs

not already performed voluntarily Estimated to be
performed with

voluntary

RECs Required to

Combust
Completion

Emissions * Completions Already Regulated by States Total Hydraulically

Fractured

Gas Well Completions Hydraulical ly Fractured

Gas Well Completion 4,107 4,275 1,377 1,644 11,403

* Note that the gas well completions required to combust th e completion emissions are not prohibited from performing RECs. However, for the impacts assessment, thes e well completions are assumed to cont rol emissions through a combustion device only.



### 4.3 Final Impacts Results



### The Tables 4-2 through 4-4 provide the final rule impacts for well completions when REC are performed estimated using the methodologies, data, a nd parameters described in this section, in the docket memos, and in the TSD.

Table 4-2: Estimated Impa cts per Individual Hydraulically Fractured Gas Well Completion When REC is Performed

Source Uncontrolled

VOC

Emissions (tons) VOC

Emissions

Reductions (tons) Cost of Compliance

(without savings) Cost of Compliance (with savings)

Individual Hydraulically

Fractured Gas Well Completion 22.691 21.500 $33,237 -$1,543

### 4-6 Table 4-3: Estimated Impacts for All Hydr aulically Fractured Gas Well Completion When REC is Required

Source Uncontrolled

VOC

Emissions (tons) VOC

Emissions

Reductions (tons) Cost of Compliance

(without savings) Cost of Compliance (with savings)
All Hydraulically

Fractured Gas Well Completions 93,198 88,305 $136,511,391 -$6,336,330

Note: An additional 29,608 tons of 31,246 tons of VOC emissi ons are estimated to be reduced via completion combustion for hydraulically fractured gas well completions that are not requi red to implement a REC but are required to combust emissions.



### Table 4-4: VOC Control Cost Effect iveness when a REC is Performed

Source VOC Control Cost Effectiveness ($/ton)— without savings VOC Control Cost Effectiveness ($/ton)— with savings All Hydraulically Fractured Gas Well Completion $1,546 per ton VOC -$72 per ton VOC

### 5-1 5.0 VOLUNTARY REDUCTIONS FROM GAS WELL COMPLETIONS WITH

HYDRAULIC FRACTURING



### This section discusses an analysis which estimates the number of hydraulically fractured gas well completions performed with voluntary use of ca pture and combustion equi pment. The analysis uses data from 2008 through 2010 and then projects that data to a 2015 basis to be consistent with the Regulatory Impacts Analysis. The an alysis concludes that 51% of hydraulically fractured gas well completions and recompletions not already under stat e regulation and with sufficient pressure to perform a REC w ill implement RECs voluntarily in 2015.

The baseline emissions estimates in the proposed Regulatory Impacts Analysis for natural gas well completions and other emissions sources take into account emissions reductions conducted pursuant to state regulations covering these ope rations. Based on public co mments and reports to

the EPA's Natural Gas STAR Pr ogram, the EPA acknowledges that some producers conduct well completions using reduced emission completion (REC) techniques voluntar ily. This analysis acknowledges this voluntary activ ity by estimating the number of hydraulically fractured gas well completions performed with voluntary use of capture and combustion equipment in 2015.

The number of hydraulically frac tured gas well completions perf ormed with voluntary use of capture and combustion equipment in 2015 is de termined in the three following steps:

5.1 Number of Voluntary RECs 

### calculates the number of gas well completions with hydraulic fracturing performed with vol untary reduction emission comple tion techniques in 2008, 2009,

and 2010.

5.2 - Number of Completions Events Eligible for RECs 

### calculates the number of gas well completions with hydraulic fracturing not under st ate regulation and with sufficient pressure to perform an REC.

5.3 - Fraction of Eligible Completions with Voluntary RECs 

### assumes that the average fraction of gas well completions with hydrauli c fracturing performed with voluntary reduction emission completion techniques in 2008, 2009, a nd 2010 as the fraction of gas well completions with hydraulic fracturing perfor med with voluntary reduction emi ssion completion techniques in

2015.

5.1 Number of Voluntary RECs



### Voluntary methane reductions from capturing and combusting methane when performing a reduced emission completion are reported by Partne rs and published annua lly in aggregate by the Natural Gas STAR Program. This analysis uses th is data to estimate the number of gas well completions with hydraulic fracturing c onducted using REC tec hniques voluntarily.

Table 5-1 shows the total methan e reductions reported to the Natural Gas STAR Program from Partners performing RECs from 2008 to 2010. These figures are published annually on the

### 5-2 Natural Gas STAR website under the Accomplishments webpage. 27 

### The figures published on the Natural Gas STAR website, however, are not updated for reports received from Partners after the reported year (e.g. 2010 REC reductions reported in 2011). Table 5-1shows the most up-to-date total emission reductions reported from Natura l Gas STAR Partner perf orming RECs including 2010 REC reductions reported in 2011.

Table 5-1. Number of Voluntary Reduced Emission Completions Performed

Year REC iSTAR Methane Reductions (short tons/year) Estimated Number of Voluntary RECs

Performed


### 2008 975,905 6,600

2009 504,480 3,412

2010 590,724 3,995

The annual REC reductions shown in Table 5-1 were divided by the average methane reductions per completion, shown in Equation 5-1 to dete rmine the number of completions with voluntary RECs, also shown in Table 5-1.

The average methane reductions per completion w as determined using the emission factor for gas well completions with hydraulic fracturing, the average methane content for gas well completions, and the average reduction effectiven ess for RECs. The emission factor for gas well completions with hydraulic fracturing is 9,000 Mcf. This is discussed in section 1.1.2 of this

document. A memo titled Composition of Natural Gas for use in the Oil and Natural Gas Sector Rulemaking , which can be found in the rule making docket, indicates, in Table 8, that the average composition of methane in gas well completions is 83.081%. In addition, this analysis assumes that an REC reduces methane emissions from gas well completions by 95 percent. Based on an 83.081 percent methane composition, a reduction effectiveness of 95 percent, and the conversion of 48.04 thousand cubic feet per short ton, the 

### average methane reductions per completion and recompletions is 147.86 thousand cubic feet. The calculation to determin e the average methane reductions per completion is shown in Equation 5-1.

ܴ ൌ ܥ ൈ ܯ ൈ ܨܧ

48.04 ൌ 147.86 ݏ݊݋ݐ ݐݎ݋݄ݏ

݊݋݅ݐ݈݁݌݉݋ܿ 5-1 .Eq



### where,

R = average methane reductions per completion

EF = average natural gas emissions pe r completion (9,000 Mcf/completion)

M = average methane composition for gas well completions (83.081%)

27 EPA. (2012) Accomplishments. <www.epa.gov/gasstar/accomplishments/index.html>

### 5-3 C

= reduction effectiveness (95%)

48.04 = conversion factor 48.04 thousa nd cubic feet equals 1 short ton

5.2 Number of Completions Events Eligible for RECs



### The historical number of gas well completions w ith hydraulic fracturing not required by state regulation and with sufficient pressure to perf orm an REC is determined using the total successful developmental and exploratory gas co mpletions with hydraulic fracturing in 2008, 2009 and 2010, the fraction of gas well completions with hydraulic fracturing impacted by state regulation, and the fraction of low pressure completions.

5.2.1 Historical Gas Well Completions with H ydraulic Fracturing from the EIA NEMS Model

The total gas completions with hydraulic fr acturing in 2008, 2009 and 2010 are determined by

the National Energy Modeling System (NEMS). NEMS is a model of U.S. energy economy developed and maintained by the Energy Information Administration (EIA) 28 

### . NEMS is used to produce the Annual Energy Outlook, a reference publication that provides detailed forecasts of the energy economy from the current year to 2035. The NEMS database defines unconventional reservoirs as those in shale, tight sand, and coal bed methane formations and distinguishes those from wells drilled in conventional reservoirs. This analysis assumes new successful natural gas wells in shale, tight sand, and coalbed methane formations are completed with hydraulic fracturing. Table 5-2 shows the total successful developmental and exploratory gas well completions with hydraulic fracturing for 2008, 2009, and 2010. Equation 5-2 shows the number of developmental completions is the total completions less the exploratory completions.



### ܥܧ െ ܥܶ ൌ ܥܦ 5-2 .Eq



### where,

DC = total developmental gas well completions with hydraulic fracturing

TC = total gas well completions with hydraulic fracturing

EC = total exploratory gas well co mpletions with hydraulic fracturing

28 U.S. Energy Information Administration. Annual Energy Outlook 2011 . Energy Information Administration.

### 5-4 Table 5-7. Total Successful Developmental an d Exploratory Gas Well Completions with Hydraulic Fracturing

Year Total Gas Completions with Hydraulic Fracturing Exploratory Gas Completions with Hydraulic Fracturing Developmental Gas Completions with Hydraulic Fracturing



### 2008 16,862 0 16,862

2009 10,275 0 10,275

2010 9,015 312 8,703

5.2.2 Completions with Hydraulic Fracturing under State Regulation

The fraction of gas well completions and recomp letions with hydraulic fracturing impacted by state regulation is determined using the analysis from the Technical Support Document (TSD) for the proposed NSPS OOOO rule. 29 

### The TSD determines fraction of gas well completions and recompletions with hydraulic fracturing impacted by state regulation accounting for regulations in Wyoming and Colorado. Since this analysis is considering historical da ta, when the respective Wyoming and Colorado regulations were implemented was considered. The Wyoming regulation was in place in 2008 30 

### and the Colorado regulati on was implemented in 2009 31



### . Therefore, the TSD analysis was revisited to de termine the fraction of gas well completions and recompletions with hydraulic fracturing impact ed by only the Wyoming regulation, for the 2008 estimate. The result was approximately 9.6 per cent. This is shown in Equation 5-3, while Equation 5-4 shows that the number of devel opmental gas completions without hydraulic fracturing with RECs due to state regulations is determined using the 15 percent for both the WY and CO regulations, used in the 2009 and 2010 estimates.

ܥܦ ௢௡ௌ௧௔௧௘ 

### ൌ ܥܦ ൈ ሺ1 െ 9.6%ሻ Eq. 5-3

ܥܦ ௢௡ௌ௧௔௧௘ 

### ൌ ܥܦ ൈ ሺ1 െ 15%ሻ Eq. 5-4



### where,

DC NoState 

### = total developmental gas well completions with hydraulic

29 EPA. (2011) Oil and Natural Gas Sector: Standards of Performance for Crude Oil and Natural Gas Production, Transmission, and Distribution. Background Technical Support Document for Proposed Standards . EPA-453/R-11- 002. pg. 4-12

30 State of Wyoming Department of Environmental Quality, Air Quality Division. Well Completions/Recompletions Permit Application. Page 2. August 2010. http://deq.state.wy.us/aqd/Oil%20and%20Gas/AQDOG11_Green%20Completion%20Application.pdf

31 Colorado Oil and Gas Conservation Commission. 2 CCR-404-1. http://oilgas.state.co.us/RuleMaking/FinalDraf tRules/COGCCFinalDraftRules_110708.pdf

### 5-5 fracturing not under state regulation

15% = fraction of gas well completions and recompletions with hydraulic fracturing impacted by both WY and CO state regulations

9.5% = fraction of gas well completions and recompletions with hydraulic fracturing impacted by bot h WY state regulations

DC = total developmental gas well completions with hydraulic fracturing

Table 5-8. Total Successful Developmental Gas Well Completions with Hydraulic Fracturing Not Under State Regulation

Year Developmental Gas Completions with Hydraulic Fracturing Developmental Gas Completions with Hydraulic Fracturing with

RECs due to State Regulations Developmental Gas Completions with Hydraulic Fracturing

not under State Regulation



### 2008 16,862 1,616 a 

### 15,246

2009 10,275 1,554 b 

### 8,722

2010 8,703 1,316 b 

### 7,387 a. Only the Wyoming regulation is in place (9.5% of completions) b. Both the Colorado and Wyoming regula tions are in place (15% of completions)

5.2.3 Completions with Hydrau lic Fracturing with Low Pressure

The fraction of gas well completions with low pr essure (i.e. insufficient to capture and direct flowback gas from the well to a flow line) is 10 percent as determined in section 2.0 of this

document

. Table 5-4 shows how the total developmental gas well completions with hydraulic fracturing for 2008, 2009, and 2010 not under state regulation is used to determine the 

### gas completions with hydraulic fracturing with su fficient pressure to perform a REC and not under state regulation in 2008, 2009, and 2010 . Equation 5-5 shows how this calculation is performed.



### DC NSNLP 

### ൌ DC N୭S୲ୟ୲ୣ 

### ൈ ሺ1 െ 10%ሻ Eq. 5-5



### where,

DC NSNLP 

### = historical gas completions with hydrau lic fracturing with sufficient pressure perform a REC and not under state regulation

10% = fraction of gas well completions a nd recompletions with hydraulic fracturing

### 5-6 impacted by state regulation

DC NoState 

### = total developmental gas well completions with hydraulic fracturing not under state regulation

Table 5-9. Total Developmental Gas Well Comp letions with Hydraulic Fracturing with

Sufficient Pressure to Perform a RE C and Not Under State Regulation

Year Developmental Gas Completions with Hydraulic Fracturing

not under State Regulation Low Pressure Gas Completions with Hydraulic Fracturing incapable of performing

RECs Total Developmental Gas Well Completions with Hydraulic

Fracturing with Sufficient

Pressure to Perform a REC and Not Under State Regulation



### 2008 15,246 1,525 13,722

2009 8,722 872 7,850

2010 7,387 739 6,648

5.2.4 Historical Completions with Hydraulic Fr acturing with Sufficient Pressure to Perform a REC and not under State Regulation

Table 5-4 shows the total gas well completions with hydraulic fracturing from the EIA NEMS model is finally reduced to the gas well comple tions with hydraulic fr acturing not under state regulation and with sufficient pressure to perform and REC in 2008, 2009, and 2010.

5.3 Fraction of Eligible Comp letions with Voluntary RECs



### The final step in this analysis determines the percent of completions no t under state regulation and with sufficient pressure to perform an REC that were conducted with voluntary REC techniques in 2015. This is done by first dividi ng the number of comple tions with voluntary RECs (from Table 5-1) by the number of historical gas comple tions with hydraulic fracturing with sufficient pressure to perform a REC and not under state regulation (from Table 5-4) for each year 2008, 2009, and 2010. The results of this calculation for 2008, 2009, and 2010 are

shown in Table 5-5.

Table 5-5. Percent of Completions that were Conducted with Voluntary RECs

Year Estimated Number of Voluntary RECs

Performed Total Developmental Gas Well Completions with Hydraulic Fracturing with

Sufficient Pressure to

Perform a REC and

Not Under State Regulation Percent of Completions not under State Regulations, with

Sufficient Pressure that were

Conducted with Voluntary

RECs

### 5-7 2008 6,600 13,722 48%

2009 3,412 7,850 43%

2010 3,995 6,648 60%

Secondly, a three-year average from 2008 to 2010 w as taken of the histori cal percentages shown in Table 5-5 to represent the variability in the implementation of voluntar y RECs. The result of averaging 48%, 43%, and 60% is about 51%. The analysis and other NSPS OOOO regulation impacts analyses will assume that this 51% will be the fraction of hydraulically fractured gas well completions not already unde r state regulation and with su fficient pressure to perform a REC that will implement RECs voluntarily in 2015.

5.4 New Source Completions and Recompletions with Voluntary Action



### The EPA estimates the number of gas completi ons with hydraulic fracturing with sufficient pressure to perform a REC and not under state re gulation in 2015 is 8,382. Therefore, assuming 51% of these completions will perform a RE C, the remaining 4,107 will constitute the completions impacted by this NSPS OOOO rule.

In addition, final TSD indicates that the number of gas recompletions wi th hydraulic fracturing with sufficient pressure to perform a REC a nd not under state regula tion in 2015 is 1,085. Therefore, assuming 51% of these recompletions will perform a REC, the remaining 532 will constitute the recompletions impacted by this NSPS OOOO rule.

### 6-1 6.0 CENTRIFUGAL COMPRESSOR IMPACTS



### This section provides additional information on pa rameters used in the centrifugal compressor regulatory impact analysis. This section also provides the affect ed facility emissions reduction estimates and cost estimates, as they have been u pdated in the final rule as compared to the proposed rule. Below are the parameters with si gnificant updates along with text descriptions of those changes.

6.1 Projected Number of Affected Units



### The final rule projects the number of affected units to be 13 wet seal centrifugal compressors annually. This is based on 16 new centrif ugal compressor units expressed in the TSD 32 

### with a ratio applied to represent just wet seal units . The Inventory of Greenhouse Gas Emissions and Sinks 1990 to 2009 includes an improvement that distinguishes between wet seal vs dry seal

units 33 

### . This data was used to create a ratio of new wet seal units versus new dry seal units. From table A-121 of the inventory annex, ther e were 646 wet seal compressors and 140 dry seal compressors in processing. It was decided to u se this inventory ratio in lieu of the general understanding that 90% of new centrifugal compressors are dry seal 34 

### so that the worst-case impacts can be represented.

6.2 Capital Costs



### Based on comment s received, it is evident that vapor captured from cen trifugal compressor seal oil degassing is not always r outed to a flare but in many cases routed back to the compressor suction or fuel system. The cost of a system of this type in which the seal oil degassing vents are routed to fuel gas, compressor suction, or an existing flare is estimated to be $22,000 35 

### . The estimated cost includes an intermediate pressure degassing drum, new piping, gas demister/filter, and a pressure regulator for the fuel line. Si nce a new flare or othe r combustion source is expected to be available in gas processing facilities, it was not included in the capital cost for this control option, whereas the proposed rule did incl ude the cost of a flare. For other facilities types, the EPA estimate is that zero new affect ed facilities will come into existence each year 36



### . Therefore the capital costs (before applying the capita l recovery factor) for an affected facility in the final rule is $22,000 for seal oil degassing capture as compared to $67,918 in the proposed rule’s TSD for the gas capture system and flare 37 

### , and as compared to the proposal costs of $75,000 for use of dry seals used in the TSD 38



### .

32 Table 6-14 page 6-30 of the TSD at www.regulations.gov/#!documentDe tail;D=EPA-HQ-OAR-2010-0505-0045

33 Page A-153 of epa.gov/climatechange/emissions/downloads11/US-GHG-Inventory-2011-Annex-3.pdf Table A121

34 Page 6-27 of the TSD

35 www.epa.gov/gasstar/documents/ngspartnerup_spring09.pdf

36 Table 6-14 on page 6-30 of the TSD depicts the number of new sources per year for production and gathering & boosting to be zero each. Additionally, page 6-19 of the TS D states that new sources w ill be located in only the processing and transmission segments.

37 Table 6-12 on page 6-26 of the TSD

38 Table 6-12 on page 6-22 of the TSD

### 6-2 6.3 Without Revenues from Addi tional Product Recovery



### The per unit annual cost is calculated by taki ng the cost of $22,000 multiplied by an annualized capital recovery factor (explai ned further in the TSD) of 0.1 424.The total annual cost for wet seal centrifugal compressors without revenue from additional product recovery is estimated to be $40,720. This is based on a total annual cost per unit of $3,132 multiplied by 13 new units per

year.

6.4 With Revenues from Additional Product Recovery



### The per unit annual cost savings is calculated by taking the value of the gas that is not emitted and routed to a useful purpose as a result of the VOC control, assu ming that all gas that is not emitted is being routed to a useful purpose which is reasonable given the available information

on the destination of recovered se al oil degassing streams. The va lue of the gas is estimated as

95% 39 

### of the 13,186 Mcf/yr 40 

### of natural gas emitted per unit. The total annual cost for wet seal centrifugal compressors with revenue from addi tional product recovery is estimated to be - $610,657. This is based on a total annual cost per unit of -$46,974 multiplied by the 13 new units

per year.

6.5 Baseline Emissions from Wet Seal Centrifu gal Compressors in the Processing Sector



### The baseline emissions from a representative ne w source are summarized in Table 6-1 based on the emissions factors and gas composition profile s in the TSD. The VOC and HAP emissions are estimated using a conversion from mass of meth ane to mass of VOC or HAP and a weighted average based on the assumption that 75% of ce ntrifugal compressors in the processing segment will compress transmission quality gas.

Table 6-1. Wet Seal Centrifuga l Compressor Baseline Emissions

Source VOC
(tpy) 

### Methane
(tpy) 

### HAP
(tpy)
Emissions per New Wet Seal Centrifugal Compressor 20.534 227.529 0.736

Total Emissions from ALL Ne w Wet Seal Centrifugal Compressors 267 2,958 10



### 6.6 Emission Reduction for Wet Seal Centrifu gal Compressors in th e Processing Sector



### The emissions reductions for wet seal centrifuga l compressors in the processing sector are summarized in Table 6-2 using a 95% control efficiency.

39 Page 6-23 of the TSD

40 47.7 scf methane / minute in Table 6-2 of the TSD * 43.6% annual operating factor on page 6-19 of the TSD, converted to Mcf/year and using a conversion factor of me thane to natural gas of 82.9 volume percent found in the gas composition memo dated July 28, 2011.

### 6-3 Table 6-2. Wet Seal Centrifugal Compresso r Emission Reductions – 95 Percent Control

Source VOC
(tpy) 

### Methane
(tpy) 

### HAP
(tpy)

Emissions Reductions Per Ne w Wet Seal Centrifugal Compressor 19.508 216.152 0.699

Total Emissions Reductions from ALL New Wet Seal Centrifugal Compressors 253.60 2,810 9.09

### 7-1 7.0 UPDATE TO TECHNICAL SUPP ORT DOCUMENT FOR PROPOSED

STANDARDS OF PERFORMANCE FO R CRUDE OIL AND NATURAL GAS PRODUCTION, TRANSMISSION, AND DI STRIBUTION – STORAGE VESSELS

7.1 INTRODUCTION



### On August 23, 2011, the U.S. Environmental Protection Agency (EPA) proposed new source performance standards (NSPS) for new sources in the crude oil and na tural gas production, transmission, and distribution s ource category. The NSPS includes standards for storage vessels with throughput greater than 1 barrel of condensate per day (bpd) and crude oil storage vessels with throughput greater than 20 bpd of crude oil under the authority of se ction 111 of the Clean Air Act (CAA). The public comment period clos ed on November 30, 2011, and EPA received comments regarding the throughput th resholds and cost impacts of the proposed amendments to the storage vessel standards.

In response to these comments, we evaluated changes to the storage vessels new source standards. The purpose of this section is to present this analysis.

7.2 BASELINE EMISSIONS



### In the technical support document (TSD) for the proposed standards, 41 

### we developed model tank batteries to represent the predominant population of tanks (e.g., condensate and crude oil tanks). These model tank batteries are presented in Tables 7-1 and 7-2. Using these model tanks, we developed nationwide baseline emissions (i.e., na tionwide emissions in the absence of a federal rulemaking). The nationwide baseline em issions are presented in Table 7-3.

7.3 COST OF CONTROL TECHNIQUES



### We evaluated two control techni ques, a vapor recovery unit (V RU) and a combustor; both of which can reduce VOC emissions by 95 percent. A de tailed discussion on the development of the

costs associated with a VRU and a combustor is presented in the TSD.

41 

### EC/R Incorporated. Oil and Na tural Gas Sector: Standards of Performance for Crude Oil and Natural Gas Production, Transmi ssion, and Distribution. Tech nical Support Document for Proposed Standards. Prepared for U.S. Envi ronmental Protection Agency. Research Triangle Park, NC. Publication No. EPA-453/R-11-0012. July 2011. Docket No. EPA-HQ-OAR-2010-

0505-0045.

### 7-2 Table 7-1. Model Condensate Tank Batteries

Model Condensate Tank Battery

Parameter E F G H 

### Condensate throughput (bbl/day) 15 100 1,000 5,000 Condensate throughput (bbl/yr) 5,475 36,500 365,000 1,825,000 Number of fixed-roof product storage vessels 210 barrel capacity 4 2 500 barrel capacity 2 2 1,000 barrel capacity 2 4 Estimated tank battery p opulation (1992) 12,000 500 100 70 Estimated tank battery p opulation (2008) 14,038 585 117 82 Total number of storage vessels (2008) 56,151 2,340 468 328 Percent of number of storage vessels in model condensate tank battery 94.7% 3.95% 0.789% 0.552% Percent of throughput per model condensate tank battery 26% 7% 15% 51% Total tank battery condensate throughput (MMbbl/yr) 32.8 9.11 18.2 63.8 Condensate throughput per model condensate battery (bbl/day) 6.41 42.7 427 2,135 Condensate throughput per storage vessel (bbl/day) 1.60 10.7 106.8 534
Minor discrepancies may be due to rounding.

a Model condensate tank battery development presented in the TSD for the prop osed rule. (Reference 

### 41 ).



### Table 7-2. Model Crude Oil Tank Batteries a



### Parameter Model Crude Oil Tank Battery

E F G H



### Percent of number of conde nsate storage vessels in model size range 94.7% 3.95% 0.789% 0.552% Number of storage vessels 491,707 20,488 4,098 2,868 Percent of throughput across condensate tank

batteries 26% 7% 15% 51% Crude oil throughput per model plant category (MMbbl/yr) 351 97.5 195 683 Crude oil throughput per storage vessel (bbl/day) 1.96 13.0 130 652
Minor discrepancies may be due to rounding.

a Model crude oil tank battery development presented in the TSD for the proposed rule. (Reference 

### 41 ).

### 7-3 Table 7-3. Nationwide Baseline Emissions for Storage Vessels a



### Model Tank Battery

E F G H Total

Model Condensate Tank Batteries 

### Total number of storage vessels (2008) 56,151 2,340 468 328 59,286 Total projected number of new or modified storage vessels (2015) b 

### 4,630 193 39 27 4,889 Number of uncontrolled storage vessels in absence of federal regulation c 

### 1,688 70 14 10 1,782

Uncontrolled VOC Emissions from storage vessel at model tank battery d 

### 3.35 22.3 223 1,117 1,366

Total Nationwide Uncontrolled VOC Emissions 5,657 1,572 3,143 11,001 21,373

Model Crude Oil Tank Batteries 

### Total number of storage vessels (2008) 491,707 20,488 4,098 2,868 519,161 Total projected number of new or modified storage vessels (2015) b 

### 40,548 1,689 338 237 42,812 Number of uncontrolled storage vessels in absence of federal regulation c 

### 14,782 616 123 86 15,607

Uncontrolled VOC Emissions from storage vessel at model tank battery d 

### 0.4 2.80 28 140 171

Total Nationwide Uncontrolled VOC Emissions 6,200 1,722 3,444 12,055 23,421
Minor discrepancies may be due to rounding

a Nationwide baseline emissions were presented in the Technical Support Document for Proposed Standards (Reference 

### 41 )

b Calculated by applying the expected 8.25 percent in dustry growth to the number of storage vessels in

2008.

c Calculated by applying the estimated 36 percent of st orage vessels that are uncontrolled in the absence of a Federal Regulation to the total projected numbe r of new or modified storage vessels in 2015.

d VOC Emissions from individual stor age vessel at model tank battery.

### 7-4 Cost data for a VRU was obtained from an Initial Economic Impact Analysis (EIA) prepared for the proposed State-only revisi ons to a Colorado regulation. 42 

### We assumed that the cost data in the EIA were presented in 2007 dollars. For this an alysis, we escalated the costs to 2008 dollars using the Chemical Engineering (CE) Indices for 2007 (525.4) and 2008 (575.4). 43 

### Total capital investment was estimated to be $98,186 and is pr esented in Table 7-4. We estimated total annual costs to be $18,983 per year.

For combustors, we also obtained the cost data from the initial EIA prepared for State-only revisions to the Colorado regulation.42 In additi on to these cost data, we added a line-item for operating labor. This is consistent with the guidelines outlined in EPA’s OAQPS Control Cost Manual (OCCM) for combustion devices. 44 

### However, the OCCM recommends that combustion devices would require 630 hours per year of operati ng labor. Since we believe that most of these

sites will be unmanned and would most likely be operated remotely, an estimate of 2 hours per day seems unreasonable. Therefore, we assumed th at the operating labor would be more similar

to that estimated for a conden ser in the OCCM, 130 hours per year . We estimated a total capital investment of $32,301and a total annual cost of $19,580/yr. The costs for a combustor are presented in Table 5.

7.4 REGULATORY OPTIONS AND NATIONW IDE IMPACTS OF REGULATORY

OPTIONS



### 7.4.1 Consideration of Regulatory Options for Condensate and Crude Oil Storage Vessels

The VOC emissions from storage vessels vary si gnificantly, depending on the rate of liquid entering and passing through the vessel (i.e., its th roughput), the pressure of the liquid as it enters the atmospheric pressure storage vessel, the liqui d’s volatility and temperature of the liquid. Some storage vessels have negligible emissions, su ch as those with very l ittle throughput and/or handling heavy liquids entering at atmospheric pr essure. Therefore, in order to determine the most cost effective means of controlling the st orage vessels, a threshold was evaluated to limit the applicability of the sta ndards to these storage vessels. We originally proposed the applicability threshold for stor age vessel control requirements in terms of throughput because we believed that this would simplify applicability determinations for sources, particularly small sources. However, because emission factors va ry widely, we now recognize that it is inappropriate to develop liquid throughput thr esholds based on averag e emission factors.

42 

### Initial Economic Impact Analysis for Propo sed State-Only Revisions to the Air Quality

Control Commission’s Regulation Number 7, “Emissions of Volatile Organic Compounds.” September 18, 2008.

43 

### Economic Indicators: Chemical Engineering Plant Cost Index. Ch emical Engineering

Magazine.

44 

### OAQPS Control Cost Manual: Fourth Editi on (EPA 450/3-90-006, January 1990). U.S.

Environmental Protection Agency . Research Triangle Park, NC.

### 7-5 As a result, we evaluated a threshold based on VOC emissions instead of liquid throughput. We

believe that the use of a VOC em issions threshold is a more flexible approach, ensuring that controls will be required only on those storage vessels where they can be applied costeffectively. Therefore, we ev aluated the costs of controllin g storage vessels with varying

emissions to determine which level of emissions would provide the most cost effective control option.

We evaluated an emission reduction of 95 percen t, which, as discussed above, could be achieved

with a VRU or a combustor. A combustor is an option for tank batteries because of the operational issues associated with a VRU. While the use of a VRU is preferable to a combustor because a combustor destroys, rath er than recycles, valuable r esources and there are secondary impacts associated with the use of a combustor, the cost impacts associated a combustor installed for the control of storage vessels were evaluated. This is a conservative approach, because the cost of a combustor is (slightly ) higher than that of a VRU.

Table 7-4. Total Capital Investment and Total Annual Cost of a Vapor Recovery Unit

Cost Item a Capital

Costs

($) NonRecurring,

One-time Costs ($) Total Capital

Investment ($) b O&M Costs ($) Savings due

to Fuel Sales ($/yr) Annualized

Total Cost

($/yr) c

VRU $78,000 Freight and Design $1,500

VRU Installation $10,154

Maintenance $8,553

Recovered natural

gas ($1,063) Subtotal Costs (2007) $78,000 $11,654 $8,553 ($1,063)

Subtotal Costs (2008) d $85,423 $12,763 $98,186 $9,367 ($1,164)

Annualized costs (using 7% interest, 15 year equipment life) $9,379 $1,401 n/a n/a $18,983 Minor discrepancies may be due to rounding

a Assume cost data provided is for the year 2007. Reference 

### 42

. b Total Capital Investment is the sum of the subt otal costs for capital costs and nonrecurring one-time

costs.

c Total Annual Costs is the sum of the annualized capital and recurring costs, O&M costs, and savings

due to fuel sales.

d Costs are escalated to 2008 dollars using th e CE Indices for 2007 (525.4) and 2008 (575.4).

Reference 

### 43

.

### 7-6 Table 7-5. Total Capital Investment and Total Annual Cost of a Combustor

Cost Item a 

### Capital

Costs

($) NonRecurring,

One-time Costs ($) Total Capital

Investment ($) b 

### O&M Costs ($) Annualized

Total Cost

($/yr) c



### Combustor $16,540 Freight and Design $1,500

Combustor Installation $6,354 Auto Igniter $1,500 Surveillance System d 

### $3,600

Pilot Fuel $1,897 Operating Labor e 

### $9,743

Maintenance $2,000
Data Management $1,000 Subtotal Costs (2007) $21,640 $7,854 $14,640 Subtotal Costs (2008) f 

### $23,699 $8,601 $32,301 $16,033 Annualized costs (using 7% interest, 15 year equipment life) $2,602 $944 n/a $19,580
Minor discrepancies may be due to rounding

a Assume cost data provided is for the year 2007 (Reference 

### 42 ).

b Total Capital Investment is the sum of the subt otal costs for capital costs and nonrecurring one-time

costs.

c Total Annual Costs is the sum of the annuali zed capital and non-recurring costs, O&M costs.

d Surveillance system identifies when pilot is not lit and attempt to relight it, documents the duration of time when the pilot is not lit, and notifi es and operator that repairs are necessary.

e Operating labor consists of labor resources for t echnical operation of device (130 hr/yr), supervisory labor (15 percent of technical labor hours), and main tenance labor hours (130 hr/yr). Labor rates are $33.51/hr (for technical and maintenance labor) and $52.85 (supervisory labor) (Reference 45).

f Costs are escalated to 2008 dollars using th e CE Indices for 2007 (525.4) and 2008 (575.4) (Reference 

### 43 ).

45 

### Employer Costs for Employee Compensation Hi storical Listing March 2004 – December 2010 ftp://ftp.bls.gov/pub/special.requests/ocwc/ect/ececqrtn.pdf.

### 7-7 To conduct this evaluation, we considered th e following four regulat ory options, which are presented in Table 7-6:

• Regulatory Option 1: Control condensate storage vessels with VOC emissions greater than 3 tpy;

• Regulatory Option 2: Control condensate storage vessels with VOC emissions greater than 6 tpy;

• Regulatory Option 3: Control condensate storage vessels with VOC emissions greater than 12 tpy; and

• Regulatory Option 4: Control condensate storage vessels with VOC emissions greater than 30 tpy.

As shown in Table 7-6, Regulator y Option 1 is not cost effectiv e for condensate storage vessels with emissions greater than 3 tpy. Therefore Re gulatory Option 1 is rejected. Since the cost

effectiveness associated with Regulatory Option 2 is accepta ble ($3,435/ton), this option was selected. As shown in Table 7-3, Model Condens ate Storage Vessel Categor ies F, G, and H have emissions greater than 6 tpy. Therefore, for th e purposes of determining impacts, the populations of new and modified condensate storage vessel s associated with categories F, G, and H are assumed to be required to reduce their emissions by 95 percent, a total of 94 new or modified condensate storage vessels by 2015.

A similar evaluation was performed for crude oil vessels and is also presented in Table 6 for the following regulatory options:

• Regulatory Option 1: Control crude oil storage vessels with emissions greater than 0.3 tpy;

• Regulatory Option 2: Control crude oil storage vessels with emissions greater than 1.5 tpy;

• Regulatory Option 3: Control cr ude oil storage vessels with em issions greater than 6 tpy;

and

• Regulatory Option 4: Control crude oil storage vessels with emissions greater than 15 tpy.

As shown in Table 7-6, Regulat ory Options 1 and 2 are not cost effective crude oil storage vessels with a emissions of 0.3 and 1.5 tpy, r espectively. Therefore Re gulatory Options 1 and 2 are rejected. Since the cost effectiveness associ ated with Regulatory Option 3 is acceptable ($3,435/ton), this option was selected. As show n in Table 3, Model Crude Oil Storage Vessel Categories G and H have emissions greater th an 6 tpy. Therefore, for the purposes of determining impacts, the populati ons of new and modified crude oil storage vessels associated with categories G and H are assumed to be requir ed to reduce their emissions by 95 percent, a total of 209 new or modified condensate storage vessels by 2015.

### 7-8 Table 7-6. Options for VOC Emission s Thresholds for Storage Vessels

Regulatory Option VOC

Emissions

Threshold (tpy) VOC

Emission

Reduction (tpy) a 

### Annual

Costs for

Combustor ($/yr) b 

### Cost

Effectiveness ($/ton VOC) Number

of impacted

units c


### Condensate Storage Vessels



### 1 3 2.85 $19,580 $6,870 1782
2 6 5.70 $19,580 $3,435 94
3 12 11.40 $19,580 $1,718 94
4 30 28.50 $19,580 $687 24 Crude Oil Storage Vessels



### 1 0.3 0.28 $19,580 $70,584 15607
2 1.5 1.39 $19,580 $14,117 825
3 6 5.70 $19,580 $3,435 209
4 15 14.25 $19,580 $1,374 209
Minor discrepancies may be due to rounding

a Calculated using 95 percent reduction

b Refer to Table 5 for Combustor Annual Costs.

c Number of impacted units determined by evalua ting which of the model tank batteries and storage vessel populations associated with each model tank battery (refer to Table 7-3) would be subject to each regulatory option. A storage vessel at a model tank battery was considered to be impacted by the regulatory option if its emissions were greater than the thresholds for the option.

### 7-9 7.4.2 Nationwide Impacts of Regulatory Options

This section provides an analys is of the primary environmental impacts (i.e., emission reductions), cost impacts and secondary environmental impacts related to Regulatory Option 2 for condensate storage vessels and Regulatory Opti on 3 for crude oil storage vessels which were selected as viable options for setting standards for storage vessels. In addition, combined impacts for a typical storage v essel are presented.

Primary Environmental Impac ts of Regulatory Options

Regulatory Option 2 (condensate stor age vessels) and 3 (crude oil storage vessels) were selected as options for setting standards for storage vessels as follows:

• Regulatory Option 2 (Condensate Storage Vesse ls): Reduce emissions from condensate storage vessels with average em issions greater than 6 tpy.

• Regulatory Option 3 (Crude Oil Storage V essels): Reduce emissions from crude oil storage vessels with average em issions greater than 6 tpy.

Because the emissions threshold does not depend upon the type of liquid being stored in the storage vessel, the regulations will apply to all storage vessels, rega rdless of contents. However, for the purposes of estimating impacts, we only included populations for condensate and crude oil storage vessels. The number of storage vessels that would be s ubject to the regulatory options listed above are presented in Table 7-6. It was estimated that, by 2015, th ere would be 94 new or modified condensate storage vess els not otherwise subj ect to State regulations and impacted by Regulatory Option 2 (conde nsate storage vessels). As shown in Table 7-6, in 2015, 209 new or modified crude oil storage vessels not otherwise s ubject to State regulati ons would be impacted by Regulatory Option 3 (cr ude oil storage tanks).

Table 7-7 presents the nationwide emission re duction estimates for each regulatory option. Emissions reductions were estimated by applying a 95 percent control efficiency to the VOC emissions presented in Table 7-3 for each storag e vessel in the model condensate and crude oil tank batteries and multiplying by the number of im pacted storage vessels. For Regulatory Option 2 (condensate storage vessels), the total nationwide VOC emission reduction was estimated to be 15,061 tpy and 14,710 tpy for Regulatory Op tion 3 (crude oil storage vessels).

7.4.3 Nationwide Cost Impacts

Cost impacts of the individual control techni ques (VRU and combustors) were presented in

Tables 7-4 and 7-5. For both re gulatory options, it was assumed that 50 percent of facilities would install a combustor and 50 percent a VRU. This accounts for the operational difficulties of using a VRU. Therefore, the average capital cost of control for each storage vessel was estimated to be $65,243 (the average of the total capital investment fo r a VRU of $98,186 and $32,301 for7-10Table 7-7. Nationwide Impacts of Regulatory OptionsModelTankBatteryNumberof NewSourcessubject toRegulatory Optionby 2015aVOCEmissionsfor aTypicalStorageVessel(tpy)CapitalCostforTypicalStorageVesselb($)Annual Cost for aTypical StorageVesselb($/yr)NationwideEmissionReductions (tpy)cVOC CostEffectiveness($/ton)Methane CostEffectiveness($/ton)Total Nationwide Costs(million $/year)WithoutSavingsWithSavings VOC MethanedWithoutSavingsWithSavingsWithoutSavingsWithSavingsCapitalCostAnnualwithoutsavingsAnnualwithsavingsRegulatory Option 2: Condensate Storage VesselsF 70 22.3 65,243 19,864 19,281 1,483325 938 910 4284 4158 4.57 1.39 1.35G 14 223 65,243 19,864 19,281 2,966649 94 91 428 416 0.913 0.278 0.270H 10 1117 65,243 19,864 19,281 10,6122323 19 18 86 83 0.652 0.199 0.193Total for Regulatory Option 2 15,061 3,2966.13 1.87 1.81Regulatory Option 3:Crude Oil Storage VesselsG 123 28 65,243 19,864 19,281 3,272716 747 725 3412 3312 8.02 2.44 2.37H 86 140 65,243 19,864 19,281 11,4382503 149 145 682 662 5.61 1.71 1.66Total for Regulatory Option 314,710 3,22013.6 4.15 4.03Combined ImpactseTypicalStorageVessel304 103 65,243 19,864 19,281 29,746 6,511 203 197 927 900 19.8 6.04 5.86Minor discrepancies may be due to roundingaNumber of storage vessels in each model tank battery (refer to Table 7-3) determined to be subject to the regulatory option asoutlined in Table 7-6.bIt was assumed for the purposes of estimating nationwide impacts that 50 percent of facilities would install a combustor and 50percent a VRU. This accountsfor the operational difficulties of using aVRU. Capital and Annual Costs determinedusing the average of costs presented in Tables 7-4 and 7-5.cNationwide emission reductions calculated by applying a 95 percent emissions reduction to the VOC emissions for a typical storage vessel multiplied by thenumber of sources subject to the regulatory option.dMethane Reductions calculated by applyingthe average Methane to VOCfactor from the E&P Tanks Study (see Appendix A). Methane:VOC = 0.219eFor purposes of evaluating NSPS impact, impacts were determined for an average storage vessel by calculating total VOC emissions from all storage vesselsand dividing by the total number of impacted storage vessels to obtain an average VOC emissions per storage vessel.

### 7-11 a combustor from Tables 7-4 and 5, respectively). Similarly, the average annual cost for a typical storage vessel was estimated to be $19,864/yr (average of the total annual co st for a VRU of $20,147/yr and $19,580/yr for a combustor from Tables 7-4 and 7-5, r espectively) without including any cost sav ings due to fuel sales and $19,281/yr (ave rage of the total annual cost for a VRU of $18,983/yr and $19,580/yr for a combusto r from Tables 7-4 and 7-5, respectively) including cost savings.

Nationwide capital and annual co sts were calculated by applying the number of storage vessels subject to the regulatory option. As shown in Table 7-7, th e nationwide cap ital cost of Regulatory Option 2 (condensate storage vessels) was estimated to be $6.13 million and for Regulatory Option 3 (crude oil st orage vessels) nationwid e capital cost was es timated to be $13.6 million. Total annual costs without fuel savings were estimated to be $1.87 million/yr for Regulatory Option 2 (condensate storage vessel s) and $4.15 million/yr for Regulatory Option 3 (crude oil storage vessels). Total annual costs with fuel savings were estimated to be $1.81 million/yr for Regulatory Option 2 (condensate storage vessels) and $4.03 million/yr for Regulatory Option 3 (crude oil storage vessels).

For purposes of evaluating the impact of a fede ral standard, impacts were determined for an average storage vessel by calculating the tota l VOC emissions from all storage vessels and dividing by the total number of impacted stor age vessels (304) to obt ain the average VOC emissions per storage vessel (103 tpy). Therefore, the nationwide annual costs were estimated to be $6.041 million/yr. A total nationwide VOC emi ssion reduction of 29,746 t py results in a cost
effectiveness of $203/ton.

### 8-1 8.0 UPDATE TO TECHNICAL SUPPOR T DOCUMENT FOR PROPOSED

STANDARDS OF PERFORMANCE FO R CRUDE OIL AND NATURAL GAS PRODUCTION, TRANSMISSION, AN D DISTRIBUTION – EQUIPMENT

LEAKS

8.1 INTRODUCTION



### On August 23, 2011, the U.S. Environment Pr otection Agency (EPA) proposed new source performance standards (NSPS) for new sources in the crude oil and na tural gas production, processing, transmission, and distribution sour ce category (40 CFR part 60, subpart OOOO). The NSPS includes standards for equipm ent leaks at natural gas process ing plants under the authority of section 111 of the Clean Air Act (CAA). The public comment period closed on November 30, 2011, and EPA received comments on the emission re ductions and cost impacts associated with equipment leaks at natural gas processing plants.

In response to these comments, we evaluated revisi ons to the equipment leak requirements in the proposed standards. The purpose of this memorandu m is to present the resu lts of the equipment leak cost analysis for the NSPS using emission factors and cost da ta from the Uniform Standards for Equipment Leaks rule (40 CFR part 65, subp art J) that EPA proposed on February 24, 2012.

In addition to the emission factors and cost data, the methodology outli ned in the supporting documentation for the Uniform Standards for Equipment Leaks 46 

### was used to estimate emission reductions for this revised analysis.

8.2 BACKGROUND



### Nationwide emissions for the propo sed rule were calculated using the model plant approach for estimating emissions. Baseline model plant emissions for the gas production, processing, and transmission segments were calculat ed using average component counts 47 

### for each of these segments. The emissions and emission reductions we re calculated using emission factors and the control effectiveness methodology provided in the EPA equipment leak protocol 48 

### . Annual emissions were calculated assuming 8,760 hours of operation each year. The emissions factors were provided for total organi c compounds (TOC) and included non-VOCs such as methane and

ethane. The emission factors fo r the production and processing segments and the transmission segments that were used to estimate the new sour ce emissions are available in Chapter 8 of the Technical Support Document 49 

### (TSD) for the proposed rule. Emissions for VOC, hazardous air pollutants (HAP), and methane were calculated using TO C weight fractions also available in the

TSD.

46 Memorandum from Cindy Hancy, RTI International to Jodi Howard, EPA/OAQPS, Analysis of Emission Reduction Techniques for Equipment Leaks, D ecember 21, 2011. EPA-HQ -OAR-2002-0037-0180

47 GRI/EPA Research and Development, Methane Emissions From The Natural Gas Industry Volume 8: Equipment Leaks, June 1996. EPA-600/R-96-080h

48 EPA, Protocol for Equipment Leak Emission Estimates, November 1995. EPA-453/R-95-017

49 EPA, Oil and Natural Gas Sector: Standards of Pe rformance for Crude Oil and Natural Gas Production, Transmission, and Distribution - Background Technical Support Document for Proposed Standards, July 2011. EPA-HQ-OAR-2010-0505-0045

### 8-2 The current NSPS regulation (40 CFR part 60, subpart KKK) requires new and reconstructed natural gas processing f acilities to comply with 40 CFR part 60 subpart VV standards to control emissions from equipment leaks. Equipment leaks are fugitive emissions emanating from valves, pump seals, flanges, compressor seals, pressu re relief valves, open-ended lines, and other process and operation components. The standards require that the facility establish a leak detection and repair (LDAR) program to lim it VOC emissions from pumps in light liquid service, compressors, pressure relief valves in gas/vapor service, sampling connection systems, valves in gas/vapor and light liq uid service, pumps and valves in heavy liquid service, and pressure relief devices in light liquid or heavy liquid service and connectors. These equipment leaks are detected using a detec tion instrument which reads the ai rborne concentration of volatile organic carbons at a potential leak point on a pa rts per million (ppm) basis. If the leak exceeds the threshold definition of the app licable regulation, repair of the leaking equipment is required. Equipment leaks also may be defined on the basi s of visual observation of certain types of equipment. For most components, subpart VV defines an equipment leak as a measured instrument reading of 10,000 ppm or greater.

For the proposed subpart OOOO rule, the follo wing regulatory options were considered for reducing equipment leaks from na tural gas processing facilities:

• Regulatory Option 1: Require the implementation of a subpart VVa LDAR program;

• Regulatory Option 2: Require the implementation of a co mponent subpart VVa LDAR

program;

• Regulatory Option 3: Require the implementation of the al ternative work practice in §60.18 of 40 CFR Part 60;

• Regulatory Option 4: Require the implementation of a modifi ed alternative work practice in §60.18 of 40 CFR Part 60 that removes th e requirement for annual monitoring using a

Method 21 device.

Based on a review of these op tions in the TSD, the implemen tation of a subpart VVa LDAR program was determined to be the best syst em of emission reduction (BSER) for equipment leaks at natural gas processing plants. The cost effectiveness of this regulatory option was calculated to be $3,352 per ton of volatile organic compounds (VOC).

8.3 UNIFORM STANDARDS DATA AND METHODOLOGY



### Since proposal, EPA has gathered equipment leaks data and cost information for the development of the Uniform Standards for Equipmen t Leaks. We believe this data represents the most up-to-date information that is available fo r equipment leaks from the oil and gas sector. The Uniform Standards for Equipment Leaks memora ndum identifies the base line control option as a combination of LDAR program elements, eq uipment design standards, and performance standards. The baseline control option is equi valent to the subpart VV LDAR program and represents the same set of requirements that appl y to natural gas proces sing plants under 40 CFR part 60, subpart KKK.

The memorandum also provides emission factors a nd equipment leak frequency data for valve and connector control options. The leak freque ncy refers to the estimated percentage of

### 8-3 equipment that will be found leak ing at a given leak definition. The leak frequencies were used

to calculate both cost and emi ssion estimates and were estimated using several sources including the Protocol for Equipment Leak Emissions Esti mates and industry data . Emission factors are the estimated leak rates of an equipment type at a given leak definition and are normally given in kg/hr/piece of equipment. Two control options from the Uniform Standards memorandum were used to evaluate the proposed subpart OOOO LDAR program. The Valve 1 Option lowers the leak definition of Valves Gas/Light Liquid to 500 ppm, and the Connectors Option 1 adds instrument monitoring for Connectors Gas/Light Liquid at 500 ppm. These valve and connector options are equivalent to a subpart VVa LDAR program and the data from these options were used to evaluate this control option. Th e Uniform Standards memorandum assumes that the annual monitoring would not provide any additi onal emissions reductions from pressure relief devices or open-ended lines.

Emission reductions were calculated from the baseline requirements. For this analysis, the leak frequency and emission factors fr om the Uniform Standards memora ndum were used to calculate

the emission reductions and costs. The Baseline da ta from these tables were used to calculate the subpart VV LDAR emissions and costs. The Valves Option 1 and Connectors Option 1 data

were used to calculate the emissions and costs for the s ubpart VVa LDAR program. The initial and annual monitoring fees for each of the co mponents were obtained from the Uniform Standards memorandum. The natural gas pro cessing plant component counts were obtained

from the GRI/EPA document 50 

### . A summary of the equipment leak frequencies used for this analysis are presented in Table 8- 1. Tables 8-2 and 8-3 present th e emission factors used for the LDAR analysis for each of the sectors. The Un iform Standards memorandum did not present an emission factor for pressure relief valves at the ba seline level of control. Therefore, the pressure

relief valve emission factors for subpart VV and VVa were assumed to be leaking at the rate of emissions below a 500 ppm leak defi nition using EPA leak rate curves. 51



### Table 8-1. Summary of Equipment Leak Frequency Percent for Model Plants

LDAR Program a Valves Connectors

Baseline 1.18/1.18 NA

Valves Option 1 5.95/1.91 NA

Connectors Option 1 NA 1.70/0.81 Data Source: Memorandum from Cindy Hancy, RT I International to Jodi Howard, EPA/OAQPS, Analysis of Emission Reduction Techniques for Equipment Leaks, December 21, 2011, Table 5.

a The leak frequencies provided in the tables are presented as initial leak frequency/subsequent leak frequency.

50 GRI/EPA Research and Development, Methane Emissions From The Natural Gas Industry Volume 8: Equipment Leaks, June 1996. EPA-600/R-96-080h

51 EPA, Protocol for Equipment Leak Emission Estimates, November 1995. EPA-453/R-95-017

### 8-4 Table 8-2. Summary of VOC Equipment Le ak Emission Factor s for Production, Gathering & Boosting and Processing Model Plants

Component Uncontrolled (kg/comp-hr) Baseline a (kg/comp-hr) Valve Option 1 b
(kg/comp-hr) Connector Option 1 b
(kg/comp-hr)

Valves 3.71E-04 2.24E-04 8.85E-05 NA

Connectors 1.04E-04 1.04E-04 NA 3.95E-05

Open-Ended Lines 2.30E-03 7.34E-05 NA NA

Pressure Relief Valves 1.60E-01 9.8E-02 NA NA Data Source: Memorandum from Cindy Hancy, RT I International to Jodi Howard, EPA/OAQPS, Analysis of Emission Reduction Techniques for Equipment Leaks, December 21, 2011, Table 7.

a The baseline option is assumed to be equi valent to a subpart V/VV LDAR program.

b The valve and connector option 1 were assumed to be equivalent to a subpart VVa LDAR program.



### Table 8-3. Summary of Methane Equi pment Leak Emission Factors for Transmission and Storage Model Plants

Component Uncontrolled a (Ton/comp-yr) V/VV b
(Ton/comp-yr) VVa b
(Ton/comp-yr)

Valves 0.0496 0.0300 0.0118

Connectors 0.0084 0.0084 0.0032

Open-Ended Lines 0.6408 0.0205 0.0205

Pressure Relief Valves 0. 3547 0.2171 0.2171 Data Source: GRI/EPA Research and Development, Methane Emissions From The Natural Gas Industry Volume 8: Equipment Leaks, June 1996, Ta bles 4-17 (Transmission) and 4-24 (Storage).

a The uncontrolled volumetric methane emission factors were converted to a mass based emission factors assuming that methane is an ideal gas.

b The emission factors for the V/VV and VVa LDAR options were calculated assuming the same emission reductions in Table 2 for each of the LDAR options.



### The monitoring costs for LDAR programs were based on the following assumptions:

• Initial monitoring and setup costs are $23. 80 for valves, $1.10 per connector, $122 for pressure relief valve disks, $6,374 for pressure relief valve disk holder and valves, and $141 for open-ended lines.

• Subsequent monitoring costs are $1.50 fo r valves, $2.50 for connectors, $2.00 for pressure relief valve disks, and $5.00 for pressure relief valve devices and open-ended

lines.

• A wage rate of $66.24 per hour was used to determine labor costs for repair.

### 8-5 • Administrative costs and initial planning and training costs are based on 320 hours for planning and training and 250 hour s per year for reporting an d administrative tasks at $92.72 per hour.

• The capital cost for purchasing a TVA or OVA monitoring system was estimated to be $10,800 and $14,500 for a data collection system.

8.3 RESULTS



### In the proposed rule, it was determin ed that only processing plants were cost effective to control emissions of VOC. However, since a new methodology was being used to calculate emission reductions from processing plants, we decided to re-evaluate the L DAR options for each of the oil and natural gas segments. The production, ga thering and boosting, tr ansmission and storage segments were evaluated for the subpart VV a nd subpart VVa options from their current

uncontrolled baseline.

Table 8-4 provides a summary of the VOC co st effectiveness of going from uncontrolled emission level to a subpart VV or subpart VVa LDAR program for the production, gathering and boosting, transmission, and stor age segments. For processing pl ants the table provides the incremental cost effectiveness of going from a subpart VV to a subpart VVa LDAR program. The average VOC cost effectiveness of the producti on pads were calculated to be $7,964 per ton of VOC reduced for the subpart VV LDAR optio n and $7,379 per ton of VOC reduced for the subpart VVa LDAR option. For gathering a nd boosting stations, the average VOC cost effectiveness were calculated to be $4,265 pe r ton of VOC reduced fo r the subpart VV LDAR option and $4,131 per ton of VOC reduced for the subpart VVa LDAR option. The average

VOC cost effectiveness of the transmission and storage segment s were calculated to be $112,127 and $27,201 per ton of VOC reduced, respectively, for the subpart VV LDAR option and $57,144 and 23,819 per ton of VOC reduced, respec tively, for the subpart VVa LDAR option.

The incremental VOC cost effectiveness for proc essing plants was calculated to be $2,691 per

ton of VOC reduced. The incr emental emission reductions from going from a subpart VV to a subpart VVa LDAR program is estimated to be 4. 56 tons per year of VOC. In addition, 0.172 tons per year of HAP, and 16.4 tons per year of methane will also be removed. Appendix C provides a summary of the em issions calculations using th e subpart VV and VVa emission

factors from the Uniform Standa rds document, and a summary of the capital and annual costs of implementing the subpart VV and subpart VVa LDAR programs using co st data from the

Uniform Standards memorandum. These results will be used to calculate the regulatory impacts of requiring a subpart VVa LDAR progr am in the final subpart OOOO rule.

### 8-6 Table 8-4. Summary of VOC Cost Effectiveness of the LDAR Options for each of the Oil and Natural Gas Segments

LDAR Option Total Capital

Investment Annual LDAR Cost ($/yr) VOC Emission

Reduction

(Ton/yr) VOC Cost

Effectiveness ($/Ton of VOC)

Well Pads

V/VV $101,100 $55,365 6.95 $7,964

VVa $102,543 $57,534 7.80 $7,379

Gathering & Boosting

V/VV $374,334 $135,821 31.8 $4,265

VVa $379,571 $143,807 34.8 $4,131

Processing a

VVa $8,041 $12,261 4.56 $2,691

Transmission

V/VV $151,669 $78,728 0.702 $112,127

VVa $156,332 $85,601 1.50 $57,144

Storage

V/VV $571,841 $206,513 7.59 $27,201

VVa $582,574 $222,970 9.36 $23,819

a Processing plants are already required to do a subpart VV LDAR program under subpart KKK. The costs and emissions from this sector are the incremental costs from going from a subpart VV to a subpart VVa LDAR program.

# Oil and Natural Gas Sector: Standards of

Performance for Crude Oil and Natural Gas Production, Transmission, and

Distribution.

Background Supplemental Technical Support Document for the

Final New Source Performance Standards

Appendices

### A-1 APPENDIX A: SUPPLEMENTARY DATA FOR THE EVALUTION OF THE

EMISSION FACTOR FOR HYDRAU LICALLY FRACTURED GAS WELL

COMPLETIONS AND RECOMPLETIONS

A.1 Industry Data Set #1 

### This section contains Industry Data Set #1. Th is data set includes vertical gas wells drilled before 2004, that were in tight sand and hydrauli cally fractured and were used to assist in development of the Reduced Emissions Completi ons Lessons Learned study. This data set was used in developing the first depiction of nati onal methane emissions po tential from hydraulic fracturing completion, presented in a Gas STAR workshop September 21, 2004.

The data set is provided in the below table. Each row contains one well completion at a well with hydraulic fracture. The colu mns report the total gas flared during the completion event, the total gas sold (recovered by reduced emissions co mpletion methods into the flow line), and the sum of the flared and sold volumes which repr esents the total gas produc ed by the well during the completion event.

At the bottom of the table are th e sums for the total completions, total gas flared, total gas sold, and total gas produced. The sums are then used to calculate an average emissions factor.

Well Completion

Number Flared Gas (Mcf) Gas Sold (Mcf) TOTAL Mcf

PRODUCED

PER

COMPLETION



### 1 878 6,919 7,797 2 3,293 8,638 11,931 3 3,348 2,386 5,734 4 1,670 2,339 4,009 5 7,095 800 7,895 6 2,884 11,549 14,433 7 1,553 4,503 6,056 8 4,005 169 4,174 9 6,614 363 6,977 10 2,536 3,377 5,913 11 2,043 5,203 7,246 12 1,010 3,792 4,802 13 3,586 149 3,735 14 12,659 4,692 17,351 15 4,307 970 5,277 16 4,053 1,105 5,158 17 3,987 12,058 16,045 18 1,320 964 2,284 19 1,576 2,133 3,709 20 2,752 3,903 6,655 21 4,063 2,629 6,692 22 5,591 12,652 18,243

### A-2 23 2,550 3,696 6,246 24 1,057 7,429 8,486 25 2,206 9,085 11,291 26 1,274 6,832 8,106 27 4,333 6,558 10,891 28 4,626 941 5,567 29 1,091 23 1,114 30 861 278 1,139

31 324 7 331 32 774 1,197 1,971 33 1,503 4,489 5,992 34 6,525 7,398 13,923 35 1,125 2,027 3,152 36 1,894 1,723 3,617 37 1,398 4,876 6,274 38 2,104 11,331 13,435 39 1,149 3,641 4,790 40 803 420 1,223 41 2,619 445 3,064 42 889 2,532 3,421

43 153 0 153 44 1,749 3,986 5,735 45 1,450 1,248 2,698 46 807 277 1,084 47 1,833 0 1,833 48 1,577 3,508 5,085 49 1,219 1,552 2,771 50 1,557 4,444 6,001 51 1,880 5,795 7,675 52 2,501 4,096 6,597 53 5,698 211 5,909 54 2,355 1,922 4,277 55 971 2,034 3,005 56 6,213 159 6,372 57 2,599 2,592 5,191 58 1,502 8,212 9,714 59 2,219 931 3,150 60 6,114 1,925 8,039 61 1,020 740 1,760 62 594 2,727 3,321 63 2,189 5,840 8,029 64 1,350 1,528 2,878

65 0 0 0 66 2,674 3,872 6,546 67 2,424 3,352 5,776 68 941 3,639 4,580

### A-3 69 1,126 4,683 5,809 70 1,264 2,117 3,381 71 1,833 1,953 3,786 72 1,513 4,940 6,453 73 9,157 9,568 18,725 74 3,026 7,770 10,796 75 3,026 501 3,527 76 16,849 5,802 22,651 77 1,768 2,137 3,905 78 9,234 1,027 10,261 79 2,191 4,017 6,208

80 0 0 0 81 5,300 1,260 6,560 82 1,694 2,022 3,716 83 673 1,234 1,907 84 313 2,651 2,964

85 0 0 0 86 3,883 5,211 9,094 87 1,800 4,296 6,096 88 1,468 3,237 4,705 89 2,946 8,984 11,930 90 1,059 1,715 2,774 91 2,381 5,754 8,135 92 882 658 1,540 93 255 1,933 2,188 94 742 2,356 3,098

95 889 0 889 96 844 3,606 4,450 97 1,052 2,863 3,915 98 1,006 581 1,587 99 502 723 1,225 100 3,470 3,079 6,549 101 2,529 5,688 8,217 102 4,725 3,283 8,008 103 523 1,203 1,726 104 2,469 5,548 8,017 105 602 1,571 2,173 106 812 4,782 5,594

Total Well Completions Total Flared Gas (Mcf) Total Gas Sold (Mcf) Total Produced

Gas (Mcf) 106 267,323 349,564 616,887



### EF Calculation:

### A-4 

# completion Mcf

s completion Mcf 820

, 5 106 887

, 616

=

### B-1 APPENDIX B: SUPPLEMENTARY ANALYSES FOR LOW PRESSURE COMPLETION

THRESHOLD

B.1 Derivation of Density from the Ideal Gas Law


### This appendix shows how this analysis determin es the density of natural gas as a function of the temperature and pressure using the ideal gas law.

Ideal Gas Law 

# nRT PV = (Eq. B.1-1)



### Step 1 – Multiply both side by the molecular weight MW 

# () () MW nRT PV MW = (Eq. B.1-2)



### Step 2 – Divide both sides by the volume 

# ( ) ( )

V

MW nRT

V PV MW

= (Eq. B.1-3)



### Step 3 – The volumes on the left hand side cancel. 

# ( ) ( )

V

MW nRT MW P = (Eq. B.1-4)



### Step 4 – Knowing n ( MW ) is equal to the mass of the ideal gas, substitute m for n ( MW ) 

# ( )

V mRT MW P = (Eq. B.1-5)



### Step 5 – Knowing m / V is equal to the density of ideal gas, substitute ρ for m / V 

# ( ) RT

MW P ρ = (Eq. B.1-6)



### Step 6 – Solve for ρ 

# ( )

RT MW P

= ρ (Eq. B.1-7)



### Nomenclature

P = pressure of the ideal gas (Pa)

V = volume of the ideal gas (m 3 

### )

R = ideal gas co nstant, 8.314 m 3 

### Pa mol -1 

### K -1

### B-2 T = temperature of the ideal gas (K)

n = moles of the ideal gas (moles)

m = mass of the ideal gas (g)

MW = molecular weight of the ideal gas (g/mol)

ρ = density of the ideal gas (g/m 3 

### )

### B-3 B.2 Water Film Impact on Inner Tubing Diameter



### This appendix shows the steps ta ken to determine the extent to which water plated on the tubing wall restricts the cross sectional area of the tubing that is available for gas flow. The purpose of the appendix is to show that th e restriction in cross sectional area is negligible, which in turn has a negligible effect on the change in flow velocity . The appendix calculates the thickness of a film of water deposited along the walls of a well tubi ng based on the percent of water by volume in the tubing. Since water is expected to adhere to the walls of the tubing, this analysis assumes that the largest film thickness occurs where all the water in the tubing is plating on the inner tubing wall rather than remaining in the bulk flow. The following equations determine the thickness of this film of water on the inner tubing wall.

Step 1a ܸ ் ൌ ܸ ௐ ൅ ܸ ீ (Eq. B.2-1a)

Step 1b ݂ ௅ ൌ ܸ ௐ
ܸ

் ൌ ܸ ௐ
ܸ

ௐ ൅ ܸ ீ (Eq. B.2-1b)

Step 1c ܸ ௐ ൌ ݂ ௅ ܸ ீ
1 െ ݂ ௅ (Eq. B.2-1c)

Step 2 ܸ ் ൌ ൬ ݂ ௅
1 െ ݂ ௅ ൰ ܸ ீ ൅ ܸ ீ (Eq. B.2-2)

3 Step ܦߨ ் ଶ

4 ൌ ൬ 1 ൅ ݂ ௅
1 െ ݂ ௅ ൰ ܦߨ ீ ଶ

4 (Eq. B.2-3)

4 Step ܦ ் ଶ

ൌ ൬ 1

1 െ ݂ ௅ ൰ ܦ ீ ଶ (Eq. B.2-4)

Step 5 ܦ ீ ൌ ට ܦ ் ଶ ሺ 1 െ ݂ ௅ ሻ (Eq. B.2-5)

Step 6 ߜ ௪௔௧௘௥ ൌ ܦ ் െ ܦ ீ
2 (Eq. B.2-6)

Step 7 ߜ ௪௔௧௘௥ ൌ ܦ ் െ ට ܦ ் ଶ ሺ 1 െ ݂ ௅ ሻ

2 (Eq. B.2-7)

Step 8 ߜ ௪௔௧௘௥ ൌ 2.875 െ ඥ 2.875 ଶ ሺ 1 െ 0.05 ሻ

2 ൌ 0.036 ݅݊. (Eq. B.2-8)

### B-4 Step 9 2ߜ ௪௔௧௘௥
ܦ ் ൈ 100 ൌ 2.5% (Eq. B.2-9)



### According to the result from Step 8, given the vo lume of water in the tubing is 5 percent of the

total volume the thickness of the film of water is about 0.035 in ches. Therefore, as shown in Step 9, above, the percent of th e inner tubing diameter that is displaced by the film of water is

about 2.5%.



### Nomenclature

V

W 

### = total volume of water in tubing, cubic inches

V

G 

### = total volume of gas in tubing, cubic inches

V

T 

### = total volume of t ubing, cubic inches

D T 

### = inner diameter of the tubing, in inches

D G 

### = diameter of the gas in tubing, in inches f

L 

### = fraction of water-sand mixt ure in fluid, by volume, in flowback fluid, unitless

δ water 

### = thickness of water film along tubing wall, in inches

### B-5 B.3 Determination of Turbulent Flow



### This analysis assumes that gas wells are in turb ulent flow during steady vapor flow condition of a flowback following a hydraulic fracture. The Re ynolds number is defined as the ratio of fluid

momentum force to viscous shear force and shown in Equation C-1 below. The Reynolds number can be used as a parameter to distingu ish between laminar and turbulent fluid flow.

ܰ

ோ௘ ൌ ߩݑܦ

ߤ ) Eq. B.3-1)

where,

N

Re = Reynolds Number

D = inner diameter of tubing, in meters

ρ = fluid density, in kilograms per cubic meter

μ = fluid viscosity, Pascal-seconds



### The change from laminar to tu rbulent flow occurs at a Reyno lds numbers around 2,100 for flow in a circular pipe. By inspection of a fr iction factor versus Reynolds number diagram 52 

### , for circular pipes, the Reynolds number needs to be above 10 4 

### for the flow to be in the turbulent regime.

To prove the Reynolds number falls in the tur bulent regime for most gas wells, the Reynolds number was calculated for a range of flowing pr essures and velocities assum ing a conservatively constant diameter and gas viscos ity. Appendix B.1 shows that the gas density is calculated as a function of the molecular weight, temperatur e, pressure, and the compressibility factor. Therefore, the density is calcula ted assuming the temperature of the gas is 200 °F, the molecular weight is 0.016 kilograms per mole, and calculati ng the compressibility factor using the BrillBeggs correlation. The gas viscosity is also a function of the pressu re and temperature, and it is calculated using the Carr, Kobayashi, and Burrows correlation from the Natural Gas Engineering Handbook 53 

### . The tubing diameter was assumed to be 2.875 inches, which is equal to 0.073 meters. The resulting Reynolds numbers are shown in Table B.3-1 below. The pressures

and velocities in Table B.3-1 were selected be cause they fall within a range of the conditions experienced by gas wells during hydraulic completion flowback.

Table B.3-1. Reynolds Numbers for Various Gas Velocities and Pressures

P (psia) u (ft/s) N R e 

### 500 10 3.043E+05

1000 20 1.174E+06

1500 10 8.463E+05

2000 20 2.159E+06

2500 10 1.284E+06

52 Perry, R.H. (1963). Perry's Chemical Engineers' Handbook (4 th Edition). McGraw-Hill. pg. 5-20

. 53 Guo, B. Ghalambor, A. (2005) Natural Gas Engineering Handbook.Gulf Publishing Company. pg. 17

### B-6 3000 20 2.913E+06

3500 10 1.596E+06

4000 20 3.410E+06

4500 10 1.784E+06

5000 20 3.675E+06

All the Reynolds numbers in Table B.3-1 are we ll above the region for la minar flow indicating that for natural gas pressures and velocities common in gas wells turbulent flow is most often the

case.

### B-7 B.4 Alternative Method for Calculating th e Compressibility Factor for Natural Gas



### For further comparison, this appe ndix tests the accuracy of the Brill-Beggs correlation chosen for this pressure model using another method to esti mate the compressibility factor. This method uses a correlation developed by Pitzer and others 54 

### for the second virial coefficient B in a common form of the truncated eq uation of state shown below:

ܼൌ1൅ ஻௉

ோ் 

### ൌ1൅ܤ ሶ ௉ ೝ

் ೝ 

### ( Eq. B.4-1)



### Where ܤ ሶ 

### is a reduced second virial coefficient given by ܤ ሶ ൌ ܤܲ
௖ 

### /ܴܶ

௖ 

### . Pitzer proposed a correlation to yield values for ܤ ሶ 

### :

ܤ ሶ ൌ ܤ ଴ 

### ൅ ܤݓ ଵ 

### ( Eq. B.4-2)



### B 0 

### and B 1 

### are approximate values that are functions of reduced temperature only. Therefore, by combining Equations D-1 and D-2 above, the eq uation used to estimate the compressibility factor for comparison to Brill-Beggs was:

ܤ൅1ൌܼ ଴ ௉ ೝ

் ೝ 

### ܤݓ ൅ ଵ ௉ ೝ

் ೝ 

### ( Eq. B.4-3)



### where:

ܤ ଴ 

### ൌ 0.083 െ ଴.ସଶଶ

் ೝ భ.ల 

### ( Eq. B.4-4)

ܤ ଵ 

### ൌ 0.139 െ ଴.ଵ଻ଶ

் ೝ ర.మ 

### ( Eq. B.4-5)



### The equations for B 0 

### and B 1 

### , along with the accentric factor w , represent an approximation of the

reduced second virial coefficient ܤ ሶ 

### . Using the reduced temperature (which was assumed constant throughout the well), reduced pressure (calculated incrementally using the pressure at each well depth), and the accentric factor for methane, a compressibility factor was calculated for each segment of the vertical well. This allowed for a side-by-side comparison of the compressibility factor at each well depth using both the Brill-Beggs method and Pitzer correlation. The two methods showed agreement for lower pressu res between 500 and 2000 pound per square inch. Table D-1 below compares the compressibility factor s for the Brill-Beggs co rrelation used in this analysis and the Pitzer compr essibility factor correlation.

Table B.4-1. Compressibility Factor for Various Pressures at 200°F

P (psia) Compressibility Factor (Brill-Beggs) Compressibility Factor (Pitzer)



### 500 0.98 0.98

1000 0.96 0.96

1500 0.95 0.94

54 J.M. Smith, H.C. Van Ness, M.M. Abbott. (2005). Introduction to Chemical Engineering Thermodynamics

. McGraw-Hill.

### B-8 2000 0.94 0.92

2500 0.94 0.90

3000 0.94 0.87

3500 0.95 0.85

4000 0.96 0.83

4500 0.98 0.81

5000 1.01 0.79

The Pitzer correlation for the second virial co efficient was chosen b ecause of its relative simplicity as a quick method to validate the calculations of the more involved Brill-Beggs method. However, it is worth no ting that this correlation only estimates the properties of pure gases. Thus, pure methane was assumed in this analys is because natural gas primarily consists of methane. In addition, this simplest form of the virial equation has valid ity at low to moderate pressures where the compressibility factor is lin ear in pressure, which e xplains the increase in disagreement between the compressib ility factors at higher pressures.C-1APPENDIX C: COST AND EMISSION SPREADSHEETS OF THE LDAR ANALYSESThe tables in this appendix provide a summary of the emissions calculations using the subpart VV and VVa emission factors fromtheUniform Standards document, and a summaryof the capital andannual costs of implementing the subpart VV and subpart VVaLDAR programs using cost data fromthe Uniform Standards memorandum.C-2Summary of Cost Effectiveness of the SubpartVV and Subpart VVa LDAR Programs for Well PadsAverageModelPlantCostEffectivenessSummaryforWellPadsw/oRecoveryCreditsModelPlantTotalCapitalInvestmentAnnualLDARCost($/yr)RecoveryCredits($/yr)1AnnualLDARCostw/oRecoveryCredits($/yr)TotalCH4Emissions(Tons/yr)TotalCH4EmissionReductionsCH4CostEffectiveness($/Ton)TotalVOCEmissions(Tons/yr)TotalVOCEmissionReductionsVOCCostEffectiveness($/Ton)TotalHAPEmissions(Tons/yr)TotalHAPEmissionReductionsHAPCostEffectiveness($/Ton)ModelPlant1(Basedon1‐Wellhead)Baseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐0.330‐‐‐‐‐ ‐‐‐‐‐0.0916‐‐‐‐‐ ‐‐‐‐‐0.00345‐‐‐‐‐ ‐‐‐‐‐V/VV$25,704 $32,169 $32,169 0.206 0.123 $260,914 0.0573 0.0343 $938,538 0.00216 0.00129 $24,894,909VVa$25,762 $32,258 $32,258 0.0810 0.249 $129,786 0.0225 0.0691 $466,856 0.000849 0.00260 $12,383,448ModelPlant2(Basedon5Wellheads)Baseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐64.04‐‐‐‐‐ ‐‐‐‐‐17.80‐‐‐‐‐ ‐‐‐‐‐0.671‐‐‐‐‐ ‐‐‐‐‐V/VV$101,100 $55,365 $55,365 39.03 25.01 $2,214 10.85 6.95 $7,964 0.409 0.262 $211,253VVa$102,543 $57,534 $57,534 35.99 28.05 $2,051 10.01 7.80 $7,379 0.377 0.294 $195,736ModelPlant3(Basedon48Wellheads)Baseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐672‐‐‐‐‐ ‐‐‐‐‐187‐‐‐‐‐ ‐‐‐‐‐7.04‐‐‐‐‐ ‐‐‐‐‐V/VV$820,109 $278,139 $278,139 410 262.1 $1,061 114 72.86 $3,818 4.29 2.75 $101,264VVa$835,227 $300,812 $300,812 378 294.0 $1,023 105 81.7 $3,681 3.96 3.08 $97,6371AnnualLDARincludesnorecoverycredits.AverageModelPlantCostEffectivenessSummaryforWellPadsw/RecoveryCreditsModelPlantTotalCapitalInvestmentAnnualLDARCost($/yr)RecoveryCredits($/yr)1AnnualLDARCostw/RecoveryCredits($/yr)TotalCH4Emissions(Tons/yr)TotalCH4EmissionReductionsCH4CostEffectiveness($/Ton)TotalVOCEmissions(Tons/yr)TotalVOCEmissionReductionsVOCCostEffectiveness($/Ton)TotalHAPEmissions(Tons/yr)TotalHAPEmissionReductionsHAPCostEffectiveness($/Ton)ModelPlant1(Basedon1‐Wellhead)Baseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐0.330‐‐‐‐‐ ‐‐‐‐‐0.0916‐‐‐‐‐ ‐‐‐‐‐0.00345‐‐‐‐‐ ‐‐‐‐‐V/VV$25,704 $32,169 $29 $32,141 0.206 0.123 $260,682 0.0573 0.0343 $937,704 0.00216 0.00129 $24,872,791VVa$25,762 $32,258 $58 $32,201 0.0810 0.249 $129,554 0.0225 0.0691 $466,022 0.000849 0.00260 $12,361,331ModelPlant2(Basedon5Wellheads)Baseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐64.04‐‐‐‐‐ ‐‐‐‐‐17.80‐‐‐‐‐ ‐‐‐‐‐0.671‐‐‐‐‐ ‐‐‐‐‐V/VV$101,100 $55,365 $5,797 $49,569 39.03 25.01 $1,982 10.85 6.952 $7,130 0.409 0.2621 $189,135VVa$102,543 $57,534 $6,501 $51,033 35.99 28.05 $1,820 10.01 7.797 $6,545 0.377 0.2939 $173,618ModelPlant3(Basedon48Wellheads)Baseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐672‐‐‐‐‐ ‐‐‐‐‐187‐‐‐‐‐ ‐‐‐‐‐7.04‐‐‐‐‐ ‐‐‐‐‐V/VV$820,109 $278,139 $60,750 $217,388 410 262.1 $830 114 72.86 $2,984 4.29 2.747 $79,146VVa$835,227 $300,812 $68,143 $232,669 378 294.0 $791 105 81.7 $2,847 3.96 3.081 $75,5191Recoverycreditscalculatedassumingthenaturalgas(82.9%methane)fromthemethanereductionhasavalueof$4/Mscf.C-3WellPadEmissionSummaryModelPlant1‐SingleWellheadValves ConnectorsOpen‐EndedLinesPressureReliefValves Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalVOCEmissionsEmissionreduction Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalHAPEmissionsEmissionreductionUncontrolled 9 37 1 0 0.032 0.037 0.022 0.000 0.092 0.001 0.001 0.001 0.000 0.003V 9 37 1 0 0.019 0.037 0.001 0.000 0.057 0.034 0.001 0.001 0.000 0.000 0.002 0.001VV 9 37 1 0 0.019 0.037 0.001 0.000 0.057 0.034 0.001 0.001 0.000 0.000 0.002 0.001VVa 9 37 1 0 0.008 0.014 0.001 0.000 0.023 0.069 0.000 0.001 0.000 0.000 0.001 0.003ModelPlant2‐FiveWellheadsValves ConnectorsOpen‐EndedLinesPressureReliefValves Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalVOCEmissionsEmissionreduction Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalHAPEmissionsEmissionreductionUncontrolled 235 863 29 10 0.842 0.867 0.644 15.450 17.803 0.032 0.033 0.024 0.582 0.671V 235 863 29 10 0.508 0.867 0.021 9.455 10.851 6.952 1.92E‐02 3.27E‐02 7.75E‐04 3.56E‐01 4.09E‐01 0.262VV 235 863 29 10 0.508 0.867 0.021 9.455 10.851 6.952 1.92E‐02 3.27E‐02 7.75E‐04 3.56E‐01 4.09E‐01 0.262VVa 235 863 29 10 0.201 0.329 0.021 9.455 10.006 7.797 7.57E‐03 1.24E‐02 7.75E‐04 3.56E‐01 3.77E‐01 0.294ModelPlant3Valves ConnectorsOpen‐EndedLinesPressureReliefValves Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalVOCEmissionsEmissionreduction Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalHAPEmissionsEmissionreductionUncontrolled 2,454 9,080 299 105 8.791 9.119 6.641 162.226 186.776 0.331 0.344 0.250 6.116 7.041V 2,454 9,080 299 105 5.308 9.119 0.212 99.282 113.921 72.856 0.200 0.344 0.008 3.743 4.295 2.747VV 2,454 9,080 299 105 5.308 9.119 0.212 99.282 113.921 72.856 0.200 0.344 0.008 3.743 4.295 2.747VVa 2,454 9,080 299 105 2.097 3.463 0.212 99.282 105.055 81.722 0.079 0.131 0.008 3.743 3.961 3.081VOCEmissionFactorsUncontrolled(kg/hr/comp)V_VV(kg/hr/comp)VVa(kg/hr/comp)Valves 0.000371 0.000224 0.0000885Connectors 0.000104 0.000104 0.0000395OEL 0.0023 0.0000734 0.0000734PRV 0.16 0.09792 0.09792EmissionfactorsobtainedfromMemorandumfromCindyHancy,RTItoJodiHoward,EPA,AnalysisofEmissonReductionTechniquesforEquipmentLeaks,December21,2011.[EPA‐HQ‐OAR‐2002‐0037‐0180]MonitoringModelPlantComponentCount VOCEmissions(Tons/yr) HAPEmissions(Tons/yr)MonitoringModelPlantComponentCount VOCEmissions(Tons/yr) HAPEmissions(Tons/yr)MonitoringModelPlantComponentCount VOCEmissions(Tons/yr) HAPEmissions(Tons/yr)C-4WellPadModelPlant2SubpartVTypeofComponentNumberofComponentsInitialMoni toringFeeorUni tCost($/comp)InitialMonitoringCos ts($/yr)(Capital)InitialLDARAdmin.CostsFrequencyofMoni toring(times/yr)SubsequentMonitoringFee($/comp)orCharge(%)AnnualMonitoringCosts($/yr)AnnualMaintenanceCos ts($/yr)InitialLeakFractionIni tialNumberofLeaksSubsequentLeakFrequency(%)AnnualNumberofLeaksPercentRepairedOnLineRepairTime(hours)LaborCharge($/hr)AnnualOnLineLeakRepairCost($/yr)PercentRequiringFurtherRepairRepairTime(hours)LaborCharge($/hr)AnnualOfflineLeakRepairCost($/yr)Moni toringtoVerifyRepair($)AnnualAdmin.Cost($/yr)AnnualMisc.Charges($/yr)Valves(UU)*Gas/vaporservice 235 23.80 5799.69 12 1.50 4230.00 0.0118 2.77 1.18 33.28 75 0.17 66.24 132.74 25 4.00 66.24 2204.20Connectors*Flanges‐gas/vapor 863 1.10 949.30PressureReliefDevices*Disks 10 122.11 1221.10 0 2.00 0.00 25.0048.84*Diskholders,valves,etc. 10 6374.29 63742.90 5.00 3200.002549.72Open‐EndedLines29 140.92 4086.68 5.00 203.00163.47MonitoringDevice1 $10,800 $10,800MonitoringDevice‐Rent0DataCollectionSystem1 $14,500 $14,500Sumofcomponents:1137AnnualAdminstrativeandReports250 92.72$23,180‐Assume300hrperfacInitialPlanningandTraining320 92.72 $29,670‐Assume340hrperfacTOTALS$101,100 $29,670 $4,230 $3,428$132.74 $2,204.20 $23,180 $2,762.03Capi talCosts$101,100AnnualizedCapi talCosts $19,428AnnualExpenses $35,937AnnualFixedCosts($/yr) $45,370AnnualVariableCosts($/yr) $9,995TotalAnnualCosts($/yr) $55,365WellPadModelPlant2Controlled‐SubpartVVaTypeofComponentNumberofComponentsInitialMoni toringFeeorUni tCost($/comp)InitialMonitoringCos ts($/yr)(Capital)InitialLDARAdmin.CostsFrequencyofMoni toring(times/yr)SubsequentMonitoringFee($/comp)orCharge(%)AnnualMonitoringCosts($/yr)AnnualMaintenanceCos ts($/yr)InitialLeakFractionIni tialNumberofLeaksSubsequentLeakFrequency(%)AnnualNumberofLeaksPercentRepairedOnLineRepairTime(hours)LaborCharge($/hr)AnnualOnLineLeakRepairCost($/yr)PercentRequiringFurtherRepairRepairTime(hours)LaborCharge($/hr)AnnualOfflineLeakRepairCost($/yr)Moni toringtoVerifyRepair($)AnnualAdmin.Cost($/yr)AnnualMisc.Charges($/yr)Valves(UU)*Gas/vaporservice 235 23.80 6635.21 12 1.50 4230.00 0.0595 13.98 1.91 53.86 75 0.17 66.24 132.74 25 4.00 66.24 3567.82Connectors*Flanges‐gas/vapor 863 1.10 1556.92 0.25 2.50 539.38 0.0170 14.67 0.81 1.75 75 0.17 66.24 2.77 25 2.00 66.24 57.88PressureReliefDevices*Disks 10 122.11 1221.10 0 2.00 0.00 25.0048.84*Diskholders,valves,etc. 10 6374.29 63742.90 5.00 3200.002549.72Open‐EndedLines29 140.92 4086.68 5.00 203.00163.47MonitoringDevice1 $10,800 $10,800MonitoringDevice‐Rent0DataCollectionSystem1 $14,500 $14,500Sumofcomponents:1137AnnualAdminstrativeandReports250 92.72$23,180‐Assume300hrperfacInitialPlanningandTraining320 92.72 $29,670‐Assume340hrperfacTOTALS$102,543 $29,670 $4,769 $3,428$135.51 $3,625.70 $23,180 $2,762.03Capi talCosts$102,543AnnualizedCapi talCosts $19,633AnnualExpenses $37,901AnnualFixedCosts($/yr) $45,575AnnualVariableCosts($/yr) $11,959TotalAnnualCosts($/yr) $57,534C-5Summary of Cost Effectiveness of the Subpart VV andSubpart VVa LDAR Programs for Gathering & BoostingAverageModelPlantCostEffectivenessSummaryforGathering&BoostingStationsw/oRecoveryCreditsModelPlantTotalCapitalInvestmentAnnualLDARCost($/yr)RecoveryCredits($/yr)1AnnualLDARCostw/oRecoveryCredits($/yr)TotalCH4Emissions(Tons/yr)TotalCH4EmissionReductionsCH4CostEffectiveness($/Ton)TotalVOCEmissions(Tons/yr)TotalVOCEmissionReductionsVOCCostEffectiveness($/Ton)TotalHAPEmissions(Tons/yr)TotalHAPEmissionReductionsHAPCostEffectiveness($/Ton)ModelPlant1Baseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐179‐‐‐‐‐ ‐‐‐‐‐49.6‐‐‐‐‐ ‐‐‐‐‐1.87‐‐‐‐‐ ‐‐‐‐‐V/VV$236,278 $94,682 $94,682 109 69.3 $1,367 30.4 19.26 $4,917 1.14 0.7260 $130,416VVa$239,435 $99,500 $99,500 103 75.7 $1,314 28.6 21.05 $4,728 1.08 0.793 $125,403ModelPlant2Baseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐295‐‐‐‐‐ ‐‐‐‐‐82.1‐‐‐‐‐ ‐‐‐‐‐3.10‐‐‐‐‐ ‐‐‐‐‐V/VV$374,334 $135,821 $135,821 181 114.5 $1,186 50.3 31.84 $4,265 1.90 1.201 $113,133VVa$379,571 $143,807 $143,807 170 125.2 $1,148 47.3 34.81 $4,131 1.78 1.312 $109,568ModelPlant3Baseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐412‐‐‐‐‐ ‐‐‐‐‐115‐‐‐‐‐ ‐‐‐‐‐4.32‐‐‐‐‐ ‐‐‐‐‐V/VV$512,390 $176,960 $176,960 252 159.8 $1,107 70 44.43 $3,983 2.65 1.675 $105,642VVa$519,707 $188,114 $188,114 238 174.8 $1,076 66 48.58 $3,872 2.49 1.832 $102,7091AnnualLDARincludesnorecoverycredits.AverageModelPlantCostEffectivenessSummaryforGathering&BoostingStationsw/RecoveryCreditsModelPlantTotalCapitalInvestmentAnnualLDARCost($/yr)RecoveryCredits($/yr)1AnnualLDARCostw/RecoveryCredits($/yr)TotalCH4Emissions(Tons/yr)TotalCH4EmissionReductionsCH4CostEffectiveness($/Ton)TotalVOCEmissions(Tons/yr)TotalVOCEmissionReductionsVOCCostEffectiveness($/Ton)TotalHAPEmissions(Tons/yr)TotalHAPEmissionReductionsHAPCostEffectiveness($/Ton)ModelPlant1Baseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐179‐‐‐‐‐ ‐‐‐‐‐49.6‐‐‐‐‐ ‐‐‐‐‐1.87‐‐‐‐‐ ‐‐‐‐‐V/VV$236,278 $94,682 $16,058 $78,625 109 69.27 $1,135 30.4 19.26 $4,083 1.14 0.7260 $108,298VVa$239,435 $99,500 $17,549 $81,951 103 75.7 $1,082 28.6 21.05 $3,894 1.08 0.793 $103,285ModelPlant2Baseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐295‐‐‐‐‐ ‐‐‐‐‐82.1‐‐‐‐‐ ‐‐‐‐‐3.10‐‐‐‐‐ ‐‐‐‐‐V/VV$374,334 $135,821 $26,554 $109,268 181 114.5 $954 50.3 31.84 $3,431 1.90 1.201 $91,015VVa$379,571 $143,807 $29,030 $114,778 170 125.2 $917 47.3 34.81 $3,297 1.78 1.312 $87,450ModelPlant3Baseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐412‐‐‐‐‐ ‐‐‐‐‐115‐‐‐‐‐ ‐‐‐‐‐4.32‐‐‐‐‐ ‐‐‐‐‐V/VV$512,390 $176,960 $37,050 $139,911 252 159.8 $875 70 44.43 $3,149 2.65 1.675 $83,524VVa$519,707 $188,114 $40,510 $147,605 238 174.8 $845 66 48.58 $3,038 2.49 1.832 $80,5911Recoverycreditscalculatedassumingthenaturalgas(82.9%methane)fromthemethanereductionhasavalueof$4/Mscf.C-6GatheringStationEmissionSummaryModelPlant1Valves ConnectorsOpen‐EndedLinesPressureReliefValves Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalVOCEmissionsEmissionreduction Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalHAPEmissionsEmissionreductionUncontrolled 547 1,723 51 29 1.960 1.730 1.133 44.805 49.628 0.074 0.065 0.043 1.689 1.871V 547 1,723 51 29 1.183 1.730 0.036 27.421 30.370 19.257 0.045 0.065 0.001 1.034 1.145 0.726VV 547 1,723 51 29 1.183 1.730 0.036 27.421 30.370 19.257 0.045 0.065 0.001 1.034 1.145 0.726VVa 547 1,723 51 29 0.467 0.657 0.036 27.421 28.582 21.046 0.018 0.025 0.001 1.034 1.078 0.793ModelPlant2Valves ConnectorsOpen‐EndedLinesPressureReliefValves Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalVOCEmissionsEmissionreduction Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalHAPEmissionsEmissionreductionUncontrolled 906 2,864 83 48 3.246 2.876 1.843 74.160 82.126 0.122 0.108 0.069 2.796 3.096V 906 2,864 83 48 1.960 2.876 0.059 45.386 50.281 31.845 0.074 0.108 0.002 1.711 1.896 1.201VV 906 2,864 83 48 1.960 2.876 0.059 45.386 50.281 31.845 0.074 0.108 0.002 1.711 1.896 1.201VVa 906 2,864 83 48 0.774 1.092 0.059 45.386 47.312 34.814 0.029 0.041 0.002 1.711 1.784 1.312ModelPlant3Valves ConnectorsOpen‐EndedLinesPressureReliefValves Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalVOCEmissionsEmissionreduction Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalHAPEmissionsEmissionreductionUncontrolled 1,265 4,005 115 67 4.532 4.022 2.554 103.516 114.623 0.171 0.152 0.096 3.903 4.321V 1,265 4,005 115 67 2.736 4.022 0.082 63.351 70.191 44.432 0.103 0.152 0.003 2.388 2.646 1.675VV 1,265 4,005 115 67 2.736 4.022 0.082 63.351 70.191 44.432 0.103 0.152 0.003 2.388 2.646 1.675VVa 1,265 4,005 115 67 1.081 1.528 0.082 63.351 66.042 48.582 0.041 0.058 0.003 2.388 2.490 1.832VOCEmissionFactorsUncontrolled(kg/hr/comp)V_VV(kg/hr/comp)VVa(kg/hr/comp)Valves 0.000371 0.000224 0.0000885Connectors 0.000104 0.000104 0.0000395OEL 0.0023 0.0000734 0.0000734PRV 0.16 0.09792 0.09792EmissionfactorsobtainedfromMemorandumfromCindyHancy,RTItoJodiHoward,EPA,AnalysisofEmissonReductionTechniquesforEquipmentLeaks,December21,2011.[EPA‐HQ‐OAR‐2002‐0037‐0180]MonitoringModelPlantComponentCount VOCEmissions(Tons/yr) HAPEmissions(Tons/yr)MonitoringModelPlantComponentCount VOCEmissions(Tons/yr) HAPEmissions(Tons/yr)MonitoringModelPlantComponentCount VOCEmissions(Tons/yr) HAPEmissions(Tons/yr)C-7Gathering&BoostingModelPlant2SubpartVTypeofComponentNumberofComponentsInitialMoni toringFeeorUni tCost($/comp)InitialMonitoringCos ts($/yr)(Capital)InitialLDARAdmin.CostsFrequencyofMoni toring(times/yr)SubsequentMonitoringFee($/comp)orCharge(%)AnnualMonitoringCosts($/yr)AnnualMaintenanceCos ts($/yr)InitialLeakFractionIni tialNumberofLeaksSubsequentLeakFrequency(%)AnnualNumberofLeaksPercentRepairedOnLineRepairTime(hours)LaborCharge($/hr)AnnualOnLineLeakRepairCost($/yr)PercentRequiringFurtherRepairRepairTime(hours)LaborCharge($/hr)AnnualOfflineLeakRepairCost($/yr)Moni toringtoVerifyRepair($)AnnualAdmin.Cost($/yr)AnnualMisc.Charges($/yr)Valves(UU)*Gas/vaporservice 906 23.80 22359.66 12 1.50 16308.00 0.0118 10.69 1.18 128.29 75 0.17 66.24 132.74 25 4.00 66.24 8497.90Connectors*Flanges‐gas/vapor 2864 1.10 3150.40PressureReliefDevices*Disks 48 122.11 5861.28 0 2.00 0.00 120.00234.45*Diskholders,valves,etc. 48 6374.29 305965.92 5.00 15360.0012238.64Open‐EndedLines83 140.92 11696.36 5.00 581.00467.85MonitoringDevice1 $10,800 $10,800MonitoringDevice‐Rent0DataCollectionSystem1 $14,500 $14,500Sumofcomponents:3901AnnualAdminstrativeandReports250 92.72$23,180‐Assume300hrperfacInitialPlanningandTraining320 92.72 $29,670‐Assume340hrperfacTOTALS$374,334 $29,670 $16,308 $16,061$132.74 $8,497.90 $23,180 $12,940.94Capi talCosts$374,334AnnualizedCapi talCosts $58,701AnnualExpenses $77,121AnnualFixedCosts($/yr) $94,822AnnualVariableCosts($/yr) $41,000TotalAnnualCosts($/yr) $135,821Gathering&BoostingModelPlant2Controlled‐SubpartVVaTypeofComponentNumberofComponentsInitialMoni toringFeeorUni tCost($/comp)InitialMonitoringCos ts($/yr)(Capital)InitialLDARAdmin.CostsFrequencyofMoni toring(times/yr)SubsequentMonitoringFee($/comp)orCharge(%)AnnualMonitoringCosts($/yr)AnnualMaintenanceCos ts($/yr)InitialLeakFractionIni tialNumberofLeaksSubsequentLeakFrequency(%)AnnualNumberofLeaksPercentRepairedOnLineRepairTime(hours)LaborCharge($/hr)AnnualOnLineLeakRepairCost($/yr)PercentRequiringFurtherRepairRepairTime(hours)LaborCharge($/hr)AnnualOfflineLeakRepairCost($/yr)Moni toringtoVerifyRepair($)AnnualAdmin.Cost($/yr)AnnualMisc.Charges($/yr)Valves(UU)*Gas/vaporservice 906 23.80 25580.84 12 1.50 16308.00 0.0595 53.91 1.91 207.66 75 0.17 66.24 132.74 25 4.00 66.24 13755.08Connectors*Flanges‐gas/vapor 2864 1.10 5166.89 0.25 2.50 1790.00 0.0170 48.69 0.81 5.80 75 0.17 66.24 2.77 25 2.00 66.24 192.08PressureReliefDevices*Disks 48 122.11 5861.28 0 2.00 0.00 120.00234.45*Diskholders,valves,etc. 48 6374.29 305965.92 5.00 15360.0012238.64Open‐EndedLines83 140.92 11696.36 5.00 581.00467.85MonitoringDevice1 $10,800 $10,800MonitoringDevice‐Rent0DataCollectionSystem1 $14,500 $14,500Sumofcomponents:3901AnnualAdminstrativeandReports250 92.72$23,180‐Assume300hrperfacInitialPlanningandTraining320 92.72 $29,670‐Assume340hrperfacTOTALS$379,571 $29,670 $18,098 $16,061$135.51 $13,947.16 $23,180 $12,940.94Capi talCosts$379,571AnnualizedCapi talCosts $59,445AnnualExpenses $84,363AnnualFixedCosts($/yr) $95,566AnnualVariableCosts($/yr) $48,242TotalAnnualCosts($/yr) $143,807C-8Summary of the Incremental Cost Effectiveness of the Subpart VVa LDAR Programs for Processing PlantsProcessingPlantCostEffectivenessSummaryLDARProgramsLDARProgramTotalCapitalInvestmentAnnualLDARCost($/yr)RecoveryCredits($/yr)1AnnualLDARCostw/oRecoveryCredits($/yr)TotalCH4EmissionReductionsCH4CostEffectiveness($/Ton)TotalVOCEmissionReductionsVOCCostEffectiveness($/Ton)TotalHAPEmissionReductionsHAPCostEffectiveness($/Ton)SubpartVVa$8,041 $12,261 $12,261 16.4 $748 4.56 $2,691 0.172 $71,374LDARProgramTotalCapitalInvestmentAnnualLDARCost($/yr)RecoveryCredits($/yr)1AnnualLDARCostw/RecoveryCredits($/yr)TotalCH4EmissionReductionsCH4CostEffectiveness($/Ton)TotalVOCEmissionReductionsVOCCostEffectiveness($/Ton)TotalHAPEmissionReductionsHAPCostEffectiveness($/Ton)SubpartVVa$8,041 $12,261 $3,800 $8,462 16.4 $516 4.56 $1,857 0.172 $49,2561Recoverycreditscalculatedassumingthenaturalgas(82.9%methane)fromthemethanereductionhasavalueof$4/Mscf.CostEffectivenessw/oRecoveryCreditsCostEffectivenessw/RecoveryCreditsC-9NaturalGasProcessingPlantEmissionSummaryValves ConnectorsOpen‐EndedLinesPressureReliefValves Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalCH4Emissions Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalVOCEmissions Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalHAPEmissionsVV 1,392 4,392 134 29 10.8 15.9 0.3 98.6 125.7 3.01 4.41 0.095 27.42 34.9 0.114 0.166 0.004 1.03 1.32VVa 1,392 4,392 134 29 4.3 6.0 0.3 98.6 109.3 1.19 1.68 0.095 27.42 30.4 0.045 0.063 0.004 1.03 1.15VOCEmissionFactorsVV(kg/hr/comp)VVa(kg/hr/comp)Valves 0.000224 0.0000885Connectors 0.000104 0.0000395OEL 0.0000734 0.0000734PRV 0.09792 0.09792MonitoringModelPlantComponentCount MethaneEmissions(Tons/yr) VOCEmissions(Tons/yr) HAPEmissions(Tons/yr)C-10ProcessingModelPlantBaseline‐SubpartVVTypeofComponentNumberofComponentsInitialMoni toringFeeorUni tCost($/comp)InitialMonitoringCos ts($/yr)(Capital)InitialLDARAdmin.CostsFrequencyofMoni toring(times/yr)SubsequentMonitoringFee($/comp)orCharge(%)AnnualMonitoringCosts($/yr)AnnualMaintenanceCos ts($/yr)InitialLeakFractionIni tialNumberofLeaksSubsequentLeakFrequency(%)AnnualNumberofLeaksPercentRepairedOnLineRepairTime(hours)LaborCharge($/hr)AnnualOnLineLeakRepairCost($/yr)PercentRequiringFurtherRepairRepairTime(hours)LaborCharge($/hr)AnnualOfflineLeakRepairCost($/yr)Moni toringtoVerifyRepair($)AnnualAdmin.Cost($/yr)AnnualMisc.Charges($/yr)Valves(UU)*Gas/vaporservice 1,392 23.80 34353.91 12 1.50 25056.00 0.0118 16.43 1.18 197.11 75 0.17 66.24 132.74 25 4.00 66.24 13056.38Connectors*Flanges‐gas/vapor 4392 1.10 4831.20PressureReliefDevices*Disks 29 122.11 3541.19 0 2.00 0.00 72.50141.65*Diskholders,valves,etc. 29 6374.29 184854.41 5.00 9280.007394.18Open‐EndedLines134 140.92 18883.28 5.00 938.00755.33MonitoringDevice1 $10,800 $10,800MonitoringDevice‐Rent0DataCollectionSystem1 $14,500 $14,500Sumofcomponents:5947AnnualAdminstrativeandReports250 92.72$23,180‐Assume300hrperfacInitialPlanningandTraining320 92.72 $29,670‐Assume340hrperfacTOTALS$271,764 $29,670 $25,056 $10,291$132.74 $13,056.38 $23,180 $8,291.16Capi talCosts$271,764AnnualizedCapi talCosts $43,899AnnualExpenses $80,007AnnualFixedCosts($/yr) $75,370AnnualVariableCosts($/yr) $48,536TotalAnnualCosts($/yr) $123,906ProcessingModelPlantControlled‐SubpartVVaTypeofComponentNumberofComponentsInitialMoni toringFeeorUni tCost($/comp)InitialMonitoringCos ts($/yr)(Capital)InitialLDARAdmin.CostsFrequencyofMoni toring(times/yr)SubsequentMonitoringFee($/comp)orCharge(%)AnnualMonitoringCosts($/yr)AnnualMaintenanceCos ts($/yr)InitialLeakFractionIni tialNumberofLeaksSubsequentLeakFrequency(%)AnnualNumberofLeaksPercentRepairedOnLineRepairTime(hours)LaborCharge($/hr)AnnualOnLineLeakRepairCost($/yr)PercentRequiringFurtherRepairRepairTime(hours)LaborCharge($/hr)AnnualOfflineLeakRepairCost($/yr)Moni toringtoVerifyRepair($)AnnualAdmin.Cost($/yr)AnnualMisc.Charges($/yr)Valves(UU)*Gas/vaporservice 1,392 23.80 39303.02 12 1.50 25056.00 0.0595 82.82 1.91 319.05 75 0.17 66.24 132.74 25 4.00 66.24 21133.63Connectors*Flanges‐gas/vapor 4392 1.10 7923.53 0.25 2.50 2745.00 0.0170 74.66 0.81 8.89 75 0.17 66.24 2.77 25 2.00 66.24 294.56PressureReliefDevices*Disks 29 122.11 3541.19 0 2.00 0.00 72.50141.65*Diskholders,valves,etc. 29 6374.29 184854.41 5.00 9280.007394.18Open‐EndedLines134 140.92 18883.28 5.00 938.00755.33MonitoringDevice1 $10,800 $10,800MonitoringDevice‐Rent0DataCollectionSystem1 $14,500 $14,500Sumofcomponents:5947AnnualAdminstrativeandReports250 92.72$23,180‐Assume300hrperfacInitialPlanningandTraining320 92.72 $29,670‐Assume340hrperfacTOTALS$279,805 $29,670 $27,801 $10,291$135.51 $21,428.20 $23,180 $8,291.16Capi talCosts$279,805AnnualizedCapi talCosts $45,041AnnualExpenses $91,126AnnualFixedCosts($/yr) $76,512AnnualVariableCosts($/yr) $59,655TotalAnnualCosts($/yr) $136,168C-11Summary of Cost Effectiveness of the Subpart VV and Subpart VVa LDAR Programs for Transmission and StorageAverageModelPlantCostEffectivenessSummaryforTransmission&StorageFacilitiesw/oRecoveryCreditsModelPlantTotalCapitalInvestmentAnnualLDARCost($/yr)RecoveryCredits($/yr)1AnnualLDARCostw/RecoveryCredits($/yr)TotalCH4Emissions(Tons/yr)TotalCH4EmissionReductionsCH4CostEffectiveness($/Ton)TotalVOCEmissions(Tons/yr)TotalVOCEmissionReductionsVOCCostEffectiveness($/Ton)TotalHAPEmissions(Tons/yr)TotalHAPEmissionReductionsHAPCostEffectiveness($/Ton)ModelPlantTransmissionBaseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐75.7‐‐‐‐‐ ‐‐‐‐‐2.09‐‐‐‐‐ ‐‐‐‐‐0.0622‐‐‐‐‐ ‐‐‐‐‐V/VV$151,669 $78,728 N/A N/A 50.3 25.4 $3,103 1.39 0.702 $112,127 0.0413 0.0209 $3,775,122VVa$156,332 $85,601 N/A N/A 21.5 54.1 $1,581 0.596 1.50 $57,144 0.0177 0.0445 $1,923,920ModelPlantStorageBaseline‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐ ‐‐‐‐‐401‐‐‐‐‐ ‐‐‐‐‐11.1‐‐‐‐‐ ‐‐‐‐‐0.330‐‐‐‐‐ ‐‐‐‐‐V/VV$571,841 $206,513 N/A N/A 127 274 $753 3.51 7.59 $27,201 0.104 0.226 $915,799VVa$582,574 $222,970 N/A N/A 62.8 338 $659 1.74 9.36 $23,819 0.0516 0.278 $801,9541Recoverycreditscalculatedassumingthenaturalgas(82.9%methane)fromthemethanereductionhasavalueof$4/Mscf.C-12TransmissionandStorageEmissionSummaryModelPlant1‐TransmissionValves ConnectorsOpen‐EndedLinesPressureReliefValves Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalCH4Emissions Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalVOCEmissionsEmissionreduction Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalHAPEmissionsEmissionreductionUncontrolled 704 3,068 7 15 34.92 25.80 9.61 5.32 75.66 0.966 0.714 0.266 0.147 2.09‐‐0.0287 0.0212 0.0079 0.0044 0.06‐‐V 704 3,068 7 15 21.09 25.80 0.14 3.26 50.29 0.584 0.714 0.004 0.090 1.39 0.0173 0.0212 0.0001 0.0027 0.04VV 704 3,068 7 15 21.09 25.80 0.14 3.26 50.29 0.584 0.714 0.004 0.090 1.39 0.70 0.0173 0.0212 0.0001 0.0027 0.04 0.02VVa 704 3,068 7 15 8.33 9.80 0.14 3.26 21.53 0.231 0.271 0.004 0.090 0.60 1.50 0.0068 0.0081 0.0001 0.0027 0.02 0.04ModelPlant1‐StorageValves ConnectorsOpen‐EndedLinesPressureReliefValves Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalCH4Emissions Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalVOCEmissionsEmissionreduction Valves ConnectorsOpen‐EndedLinesPressureReliefValvesTotalHAPEmissionsEmissionreductionUncontrolled 1,898 5,660 367 68 94.15 47.60 235.18 24.12 401.05 2.606 1.317 6.508 0.668 11.10 0.0774 0.0391 0.1933 0.0198 0.33V 1,898 5,660 367 68 56.85 47.60 7.51 14.76 126.72 1.573 1.317 0.208 0.409 3.51 0.0467 0.0391 0.0062 0.0121 0.10VV 1,898 5,660 367 68 56.85 47.60 7.51 14.76 126.72 1.573 1.317 0.208 0.409 3.51 7.59 0.0467 0.0391 0.0062 0.0121 0.10 0.23VVa 1,898 5,660 367 68 22.46 18.08 7.51 14.76 62.81 0.622 0.500 0.208 0.409 1.74 9.36 0.0185 0.0149 0.0062 0.0121 0.05 0.28MethaneEmissionFactors‐Transmission&StorageUncontrolled(ton/yr/comp)V_VV(ton/yr/comp)VVa(ton/yr/comp) V_VV VVaValves 0.0496 0.0300 0.0118 39.6% 76.1%Connectors 0.0084 0.0084 0.0032 0.0% 62.0%OEL 0.6408 0.0205 0.0205 96.8% 96.8%PRV 0.3547 0.2171 0.2171 38.8% 38.8%CalculatedfromTable4‐17andTable4‐24ofMethaneEmissionsfromtheNaturalGasIndustry,Volume8:EquipmentLeaksTheemissionfactorsforV_VVandVvawereestimatedusingtheemissionreductionsthatwereobtainedforthevariouscomponentsfromtheUniformStandardsdata.MemorandumfromCindyHancy,RTItoJodiHoward,EPA,AnalysisofEmissonReductionTechniquesforEquipmentLeaks,December21,2011.[EPA‐HQ‐OAR‐2002‐0037‐0180]WeightRatiosforEstimatingEmissionsTransmission&StorageVOC:Methane 0.027674689HAP:Methane 0.000821985MonitoringModelPlantComponentCount MethaneEmissions(Tons/yr) VOCEmissions(Tons/yr) HAPEmissions(Tons/yr)MonitoringModelPlantComponentCount MethaneEmissions(Tons/yr) VOCEmissions(Tons/yr) HAPEmissions(Tons/yr)C-13TransmissionModelPlantSubpartVTypeofComponentNumberofComponentsInitialMoni toringFeeorUni tCost($/comp)InitialMonitoringCos ts($/yr)(Capital)InitialLDARAdmin.CostsFrequencyofMoni toring(times/yr)SubsequentMonitoringFee($/comp)orCharge(%)AnnualMonitoringCosts($/yr)AnnualMaintenanceCos ts($/yr)InitialLeakFractionIni tialNumberofLeaksSubsequentLeakFrequency(%)AnnualNumberofLeaksPercentRepairedOnLineRepairTime(hours)LaborCharge($/hr)AnnualOnLineLeakRepairCost($/yr)PercentRequiringFurtherRepairRepairTime(hours)LaborCharge($/hr)AnnualOfflineLeakRepairCost($/yr)Moni toringtoVerifyRepair($)AnnualAdmin.Cost($/yr)AnnualMisc.Charges($/yr)Valves(UU)*Gas/vaporservice 704 23.80 17374.39 12 1.50 12672.00 0.0118 8.31 1.18 99.69 75 0.17 66.24 132.74 25 4.00 66.24 6603.23Connectors*Flanges‐gas/vapor 3068 1.10 3374.80PressureReliefDevices*Disks 15 122.11 1831.65 0 2.00 0.00 37.5073.27*Diskholders,valves,etc. 15 6374.29 95614.35 5.00 4800.003824.57Open‐EndedLines58 140.92 8173.36 5.00 406.00326.93MonitoringDevice1 $10,800 $10,800MonitoringDevice‐Rent0DataCollectionSystem1 $14,500 $14,500Sumofcomponents:3845AnnualAdminstrativeandReports250 92.72$23,180‐Assume300hrperfacInitialPlanningandTraining320 92.72 $29,670‐Assume340hrperfacTOTALS$151,669 $29,670 $12,672 $5,244$132.74 $6,603.23 $23,180 $4,224.77Capi talCosts$151,669AnnualizedCapi talCosts $26,671AnnualExpenses $52,056AnnualFixedCosts($/yr) $54,076AnnualVariableCosts($/yr) $24,651TotalAnnualCosts($/yr) $78,728TransmissionModelPlantControlled‐SubpartVVaTypeofComponentNumberofComponentsInitialMoni toringFeeorUni tCost($/comp)InitialMonitoringCos ts($/yr)(Capital)InitialLDARAdmin.CostsFrequencyofMoni toring(times/yr)SubsequentMonitoringFee($/comp)orCharge(%)AnnualMonitoringCosts($/yr)AnnualMaintenanceCos ts($/yr)InitialLeakFractionIni tialNumberofLeaksSubsequentLeakFrequency(%)AnnualNumberofLeaksPercentRepairedOnLineRepairTime(hours)LaborCharge($/hr)AnnualOnLineLeakRepairCost($/yr)PercentRequiringFurtherRepairRepairTime(hours)LaborCharge($/hr)AnnualOfflineLeakRepairCost($/yr)Moni toringtoVerifyRepair($)AnnualAdmin.Cost($/yr)AnnualMisc.Charges($/yr)Valves(UU)*Gas/vaporservice 704 23.80 19877.39 12 1.50 12672.00 0.0595 41.89 1.91 161.36 75 0.17 66.24 132.74 25 4.00 66.24 10688.27Connectors*Flanges‐gas/vapor 3068 1.10 5534.92 0.25 2.50 1917.50 0.0170 52.16 0.81 6.21 75 0.17 66.24 2.77 25 2.00 66.24 205.76PressureReliefDevices*Disks 15 122.11 1831.65 0 2.00 0.00 37.5073.27*Diskholders,valves,etc. 15 6374.29 95614.35 5.00 4800.003824.57Open‐EndedLines58 140.92 8173.36 5.00 406.00326.93MonitoringDevice1 $10,800 $10,800MonitoringDevice‐Rent0DataCollectionSystem1 $14,500 $14,500Sumofcomponents:3845AnnualAdminstrativeandReports250 92.72$23,180‐Assume300hrperfacInitialPlanningandTraining320 92.72 $29,670‐Assume340hrperfacTOTALS$156,332 $29,670 $14,590 $5,244$135.51 $10,894.04 $23,180 $4,224.77Capi talCosts$156,332AnnualizedCapi talCosts $27,334AnnualExpenses $58,267AnnualFixedCosts($/yr) $54,738AnnualVariableCosts($/yr) $30,863TotalAnnualCosts($/yr) $85,601C-14StorageModelPlantSubpartVTypeofComponentNumberofComponentsInitialMoni toringFeeorUni tCost($/comp)InitialMonitoringCos ts($/yr)(Capital)InitialLDARAdmin.CostsFrequencyofMoni toring(times/yr)SubsequentMonitoringFee($/comp)orCharge(%)AnnualMonitoringCosts($/yr)AnnualMaintenanceCos ts($/yr)InitialLeakFractionIni tialNumberofLeaksSubsequentLeakFrequency(%)AnnualNumberofLeaksPercentRepairedOnLineRepairTime(hours)LaborCharge($/hr)AnnualOnLineLeakRepairCost($/yr)PercentRequiringFurtherRepairRepairTime(hours)LaborCharge($/hr)AnnualOfflineLeakRepairCost($/yr)Moni toringtoVerifyRepair($)AnnualAdmin.Cost($/yr)AnnualMisc.Charges($/yr)Valves(UU)*Gas/vaporservice 1,898 23.80 46841.75 12 1.50 34164.00 0.0118 22.40 1.18 268.76 75 0.17 66.24 132.74 25 4.00 66.24 17802.45Connectors*Flanges‐gas/vapor 5660 1.10 6226.00PressureReliefDevices*Disks 68 122.11 8303.48 0 2.00 0.00 170.00332.14*Diskholders,valves,etc. 68 6374.29 433451.72 5.00 21760.0017338.07Open‐EndedLines367 140.92 51717.64 5.00 2569.002068.71MonitoringDevice1 $10,800 $10,800MonitoringDevice‐Rent0DataCollectionSystem1 $14,500 $14,500Sumofcomponents:7993AnnualAdminstrativeandReports250 92.72$23,180‐Assume300hrperfacInitialPlanningandTraining320 92.72 $29,670‐Assume340hrperfacTOTALS$571,841 $29,670 $34,164 $24,499$132.74 $17,802.45 $23,180 $19,738.91Capi talCosts$571,841AnnualizedCapi talCosts $86,996AnnualExpenses $119,517AnnualFixedCosts($/yr) $129,915AnnualVariableCosts($/yr) $76,598TotalAnnualCosts($/yr) $206,513StorageModelPlantControlled‐SubpartVVaTypeofComponentNumberofComponentsInitialMoni toringFeeorUni tCost($/comp)InitialMonitoringCos ts($/yr)(Capital)InitialLDARAdmin.CostsFrequencyofMoni toring(times/yr)SubsequentMonitoringFee($/comp)orCharge(%)AnnualMonitoringCosts($/yr)AnnualMaintenanceCos ts($/yr)InitialLeakFractionIni tialNumberofLeaksSubsequentLeakFrequency(%)AnnualNumberofLeaksPercentRepairedOnLineRepairTime(hours)LaborCharge($/hr)AnnualOnLineLeakRepairCost($/yr)PercentRequiringFurtherRepairRepairTime(hours)LaborCharge($/hr)AnnualOfflineLeakRepairCost($/yr)Moni toringtoVerifyRepair($)AnnualAdmin.Cost($/yr)AnnualMisc.Charges($/yr)Valves(UU)*Gas/vaporservice 1,898 23.80 53589.89 12 1.50 34164.00 0.0595 112.93 1.91 435.02 75 0.17 66.24 132.74 25 4.00 66.24 28815.83Connectors*Flanges‐gas/vapor 5660 1.10 10211.10 0.25 2.50 3537.50 0.0170 96.22 0.81 11.46 75 0.17 66.24 2.77 25 2.00 66.24 379.60PressureReliefDevices*Disks 68 122.11 8303.48 0 2.00 0.00 170.00332.14*Diskholders,valves,etc. 68 6374.29 433451.72 5.00 21760.0017338.07Open‐EndedLines367 140.92 51717.64 5.00 2569.002068.71MonitoringDevice1 $10,800 $10,800MonitoringDevice‐Rent0DataCollectionSystem1 $14,500 $14,500Sumofcomponents:7993AnnualAdminstrativeandReports250 92.72$23,180‐Assume300hrperfacInitialPlanningandTraining320 92.72 $29,670‐Assume340hrperfacTOTALS$582,574 $29,670 $37,702 $24,499$135.51 $29,195.44 $23,180 $19,738.91Capi talCosts$582,574AnnualizedCapi talCosts $88,520AnnualExpenses $134,450AnnualFixedCosts($/yr) $131,439AnnualVariableCosts($/yr) $91,531TotalAnnualCosts($/yr) $222,970