The document discusses using data analysis to improve compliance and identify potential errors in measurement and reporting. It provides examples of analyzing vent and production data from single well and multi-well sites to identify outliers. Another example analyzes receipt and production data from multi-well sites. The analysis can identify facilities with high vent-to-production or receipt-to-production ratios that may indicate errors. This helps improve data reliability and address non-compliance before it becomes an issue.

1. Measurement & Reporting Data Analysis for
Compliance
Canadian Digital Oilfields Conference – May 18, 2022

2. Agenda
• Introduction
• The case for compliance
• Why data matters to compliance
• Compliance, data and the bottom line
• Practical considerations w/ data analysis
• Identifying potential error sources before they become non-
compliance issues
• Discovering potential error sources through data analysis
• Conclusion

3. Getting Useful Results from Volumetric Data Analysis
Consider:
• What if you can’t tell whether publicly reported Vent or Trucked
volumes are realistic?
• You can’t manage what you can’t measure.
• There is a direct correlation between the accuracy of reported data
and its value.

4. Compliance Indicators through Data Analysis
Industry has a need for accuracy necessitates quick, useful assessment
techniques
• Analysis of relevant data pinpoints measurement and reporting
improvement opportunities
• Information displayed with visual indicators, i.e. bubble maps,
reveals outlier data excursions for facilities where regulatory limits
have been exceeded for:
• Reporting vent volume estimates
• Trucked oil receipt volumes into proration batteries

5. Improving Data Reliability with Compliance Checks
• Analysis of relevant data pinpoints top uncertainties
• e.g. Corporate daily data,
public data
• Is your data trustworthy?
• Production reporting must
be accurate; otherwise,
non-compliance must be
addressed with Regulator

6. Improving Data Reliability with Compliance Checks
• e.g. Corporate daily data,
public data
• Is your data trustworthy?
• Production reporting must
be accurate; otherwise,
non-compliance must be
addressed with Regulator
• Analysis of relevant data pinpoints top uncertainties
• e.g. Tank venting, excessive
trucked production into
proration batteries
• Unaddressed field measurement
uncertainties impact public data
• Data analysis can be used to
validate reliability of data, identify
improvement opportunities

7. Business Benefits from Identifying Data Uncertainties
• Measurement uncertainties degrade the business value of production
data
• Accurate measurement assures reliable results

8. Business Benefits from Identifying Data Uncertainties
• Measurement uncertainty degrades business value of production data
• Accurate measurement assures reliable results
• Volumetrics
• Custody transfer
• Prorations
• Emissions
• GHG Reduction

9. Business Benefits from Identifying Data Uncertainties
• Volumetrics
• Custody transfer
• Prorations
• Emissions
• GHG Reduction
• Measurement uncertainty degrades business value of production data
• Accurate measurement assures reliable results
• Alberta Emissions Offset Registry
• Alberta Emission Performance
Credits
• Risk Assessments
• AER Remote Sensing Reports
• Clean Carbon Status
• Emissions Factor Assessment
• FERC Requirements

10. End-User Data Analysis Applications
• ESG projects to reduce methane and GHG emissions
• Environmental impact of GHG emissions reduction
• Achieving Performance Standards for emissions reduction by 2030
• Carbon credit transactions
• Commercial opportunities with sustainable production methods

11. Practical Considerations with Data Analysis
• Valuable insights result by qualifying volumetric data
• Consider the following examples:
• A single unrepresentative gas-in-solution factor may contribute
up to thousands of erroneous reported vent volume estimates
• Capital spending commitments, i.e. for VRUs are significant to
resolve non-compliance events
• Truck-in meter stations cost upwards of $250-$400K, in some
fields equivalent to drilling a well

12. Application of Data Analysis to Public Data
• Data Analysis Case #1: Vent and Production Data
• Data Analysis Case #2: Receipt and Production Data

13. Potential Error Sources - Example #1
Gas/Oil
Ratio
Stock
Tank Oil
Gravity
GIS Factor
kPa(g) o
C m
3
/STm
3 o
API m3 gas/m3 STO per kPa(g)
January A 487 15.0 20.3 43.9 0.04172
February A 380 15.0 10.0 40.0 0.02626
January B 1349 15.0 57.5 47.9 0.04260
February B 1798 15.0 34.9 47.4 0.01940
January C 1303 15.0 50.2 47.8 0.03853
February C 1587 15.0 14.2 47.4 0.00895
Date and
Location
Flash
Conditions
• Tank vapor estimates not determined using reliable data and factors
can go undetected, contributing to uncertainties for climate change
reporting

14. Potential Error Sources - Example #2
• Measurement error incurred by unmetered trucked-in oil to a
proration battery is absorbed in flow-lined well volumes
Source: Directive 17, Fig 5.10

15. Staying Ahead of Regulatory Tank Venting Limits
• Hefty reductions in AER Directive-060 Overall Vent Gas Limits call for
accurate volumes to design reliable vapor containment solutions with
portable and permanent Vapor Reduction Unit (VRU) systems.
Site (OVG) Vent Limit/month
(E3m3)
Daily Site (OVG) Vent Limit
(E3m3/day)
Before 2020 24 0.8
After January 1, 2020
- Only includes DVG and Non-routine
- Excludes pneumatics, glycol dehys,
compressor seals
15 0.5
After 2021-12-31
- New sites cannot exceed 3 E3m3/month
3 0.1

16. Data Analysis Case #1: Vent and Production Data
• Compare VENT & PRODuction trends for:
1. Single Well Batteries (Type 311)
a. VENT / PROD ratio by facility
b. VENT / PROD ratio by well formation
2. Multi-well Proration Batteries (Type 322)
a. VENT / PROD ratio by facility

17. Data Analysis Case #1: Vent and Production Data cont…
1. Single Well Batteries (Type 311)
a. VENT / PROD ratio by facility
b. VENT / PROD ratio by well formation
Context:
• Where VENT / PROD is used as gas-to-oil ratio (GOR)
• GOR is expected to be 0.007 e3m3 gas / m3 oil

18. Data Analysis Case #1: Vent and Production Data cont…
1. Single Well Batteries (Type 311)
a. VENT / PROD ratio by facility
where VENT / PROD ratio > 0.069
Fig 1. Histogram of VENT/PROD Ratio > 0.069 Fig 2. Geospatial Bubble Map

19. Data Analysis Case #1: Vent and Production Data cont…
1. Single Well Batteries (Type 311)
a. VENT / PROD ratio by facility
where VENT / PROD ratio > 0.69
Fig 3. Histogram of VENT/PROD Ratio > 0.69 Fig 4. Geospatial Bubble Map

20. Data Analysis Case #1: Vent and Production Data cont…
1. Single Well Batteries (Type 311)
b. VENT / PROD ratio by well formation
Fig 5. List of GOR means by Formation Fig 6. Geospatial Bubble Map

21. Data Analysis Case #1: Vent and Production Data cont…
2. Multi-well Proration Batteries (Type 322)
a. VENT / PROD ratio by facility
where VENT / PROD ratio > 0.069
Fig 7. Histogram of VENT/PROD Ratio > 0.069 Fig 8. Geospatial Bubble Map

22. Data Analysis Case #2: Receipt and Production Data
• Compare RECeipt and PRODuction trends for:
• Multi-well Proration Batteries (Type 322)
where REC/PROD > 1 and PROD > 1,000 m3/month
Fig 9. Example of Proration Factor and REC/PROD Ratio vs. 2021 Month

23. Data Analysis Case #2: Receipt and Production Data cont…
• Geospatial representation where bubble
colour and size represent operator and
comparative REC/PROD ratio respectively
Fig 10. Histogram of REC/PROD Ratio Fig 11. Geospatial Bubble Map

24. Conclusions
Both digital data solutions offer useful methods for both producers and
regulators to identify accuracy improvement opportunities.