1. SPE DISTINGUISHED LECTURER SERIES is funded principally through a grant of the SPE FOUNDATION The Society gratefully acknowledges those companies that support the program by allowing their professionals to participate as Lecturers. And special thanks to The American Institute of Mining, Metallurgical, and Petroleum Engineers (AIME) for their contribution to the program.

2. 2 Integrating Reserves and Resource Assessment with Portfolio Management - A Hybrid Approach John Etherington Petroleum Resource Analysts ( PRA ) International Ltd., Calgary, Canada

3. 3 Are reserves disclosures an isolated and bureaucratic process in your company? Do you need two “sets of books” to run your business? Are your managers (and investors) frustrated with with reserves write-downs?

4. 4 Outline Introduction Management Processes and Tools Designing an Integrated System Summary & Conclusions resource assessments reserves reporting portfolio planning

5. 5 E&P Business Model We are in the hydrocarbon finding, developing and producing business! E&P Life Cycle

6. 6 Managing our Business Inventory Cataloguing & Valuation Bookkeeping Performance Forecasting & Planning General Resource Assessment Resource Tracking & Reporting Portfolio Management Oil & Gas Asset Management Hydrocarbon Resource Management (HRM) Processes and Tools

7. 7 Value Volume consistent assessments Resource Assessment Process Development Projects Discovery Risk Commercial Risk and Risk Discoveries Prospects In-Place Uncertainty Recovery Uncertainty Commercial Uncertainties Uncertainty E stimated U ltimate R ecoverable N et P resent V alue

8. 8 Acquisitions Probable Possible Commercial Sub-commercial Sales and Exploration Discoveries total portfolio debits and credits plus internal “reserves growth” Reserves Disclosures are a subset of the total resource accounting. Resource Accounting System Resource Tracking & Reporting Production Proved Undev Dev Sales

9. 9 Corporate Strategies Project A Project B Scenario 1 Scenario 2 Aggregation Model $ Allocation Model Investment Portfolio Portfolio Management Tools VolumeValue stochastic full reserve & resource “opportunity inventory” quantitative assessments of risk & uncertainty [probabilistic-based] Portfolio Performance X X X X X

10. 10 Designing a HRM System  promote consistent assessment processes  quantify technical uncertainties & commercial risk  synchronize volume and value  accommodate complete project inventory  accept deterministic and/or probabilistic methods We need a single Integrated system  avoid “two sets of books”

11. 11 synchronizing volume, value and ownership at the “entity level” applications Resource Management Data Model Lease (ownership) Project (cash flow) Reservoir (in-place) lease- reservoir - project reservoir - project (recoverable) Portfolio Analysis Reserves Disclosures aggregation lease project reservoir

12. 12 Two Views of Uncertainty Deterministic View Cum Prod 1P 2P 3P EUR Proved Probable Possible Probabilistic View 0% 100% % probability of value or more P90 P50 P10 Proved Probable Possible 1P2P3P EUR cum prod do both! (hybrid) Monte Carlo Simulation X X Discrete Scenarios

13. 13 Standard Resource Classification SPE/WPC/AAPG 2000 Reserves & Resource Classification Technical Uncertainty CONTINGENT RESOURCES RESERVES PRODUCTION PROSPECTIVE RESOURCES UNRECOVERABLE ProbablePossible Low Estimate Best Estimate High Estimate Discovered Sub-commercial Commercial Undiscovered Proved 3P1P2P Project Maturity >P90>P50>P10 provides a “bridge” between deterministic & probabilistic methods Low Estimate Best Estimate High Estimate

14. 14 Quantifying Project Risk Contingent Resources Prospective Resources Reserves Development Risk [Chance of Achieving Production Status within 5 years] Discovery Risk [Chance of Discovering Hydrocarbons] Discovered but not yet commercial due to one or more contingencies Commercial Risk Project Maturity

15. 15 Not Owned “Unidentified” Quantifying Acquisition Risk Owned Identified Not Owned Identified discovery risk development risk Discovered Undiscovered Acquisition Risk fiscal terms Prospective Resources Contingent Resources Reserves Total Risk = acquisition risk x discovery risk x development risk [Chance of Capture]

16. 16 Using Hybrids for Quality Assurance Deterministic Estimated Ultimate Recoverable (EUR) mmbo Probable Proved 1P2P Cumulative Probability of “X” or greater 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 020406080100120140 Probabilistic Intercept at P80 vs >P90 target! There is a “mismatch” in our uncertainty analysis! Check both

17. 17 Deterministic/Probabilistic Integration 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 020406080100120140 Cumulative Probability of “X” or greater Possible Estimated Ultimate Recoverable (EUR) X Proved Probable EV (mean) = 52 = 17 (.95) + 27 (.74) + 56 (.28) Integrate deterministic estimates with probabilistic distribution to derive average confidence factors (CF) CF3 = 0.28 CF1 = 0.95 CF2 = 0.74 17 27 56 1P = 172P = 443P = 100

18. 18 Creating “Pseudo-Distributions” Deterministic Estimated Ultimate Recoverable (EUR) Possible Probable Proved 1P 2P 3P Cumulative Probability of “X” or greater 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 020406080100120140 Possible Probable Proved “Probabilistic” Using default confidence factors (CF): EV (Mean) = Pvd(0.95) + Prob(0.7) + Poss(0.3) X default CF values based on local calibration tests

19. 19 Integrating Regulatory Disclosure Rules e.g. “SEC Proved” reserves n Economic Criteria: n Volume Extent: n Discovery Criteria n Improved Recovery low est best est high est SEC Proved = revised SPE Probable SPE 2P minus SEC Proved SPE/SEC Hybrid more conservative deterministic criteria?

20. 20 Hybrid Assessments – Input/ 1P 2P 3P 1744100 ProvedProbablePossible.95.74.28 275 6 17 162016 Volume Confidence Factor Discounted Volume probabilistic assessment X Mean = 52 deterministic assessment X commercial risk continuous distribution discretized matrix probabilistic &/or deterministic applications Output

21. 21 Initially-In-Place Resource Accounting/Material Balance Remaining “Recoverable” Economic & Committed Unrecoverable 100 40 55 Produced 5 Reserves Contingent Resources Primary Waterflood EOR 20 10 Economic -Not Committed Economic?? -Not Committed mean of distributions sales and non-sales quantities development projects + + = 25

22. 22 Resource Tracking & Reporting New Field Discoveries Probable Possible Proved Undev Dev Reserves C. Resources Acquisitions Property Sales Prospective Resources Production Sales Reconcile changes to maintain material balance

23. 23 100 0 Estimated Ultimate Recoverable (EUR) mmbo P10 P90 Cumulative Probability of “X” or greater Probabilistic vs Arithmetic Aggregation Probabilistic Aggregate Arithmetic Sum (deterministic) X X X X X portfolio analysis reserves disclosures X EV 150 200 P90 = 30 “portfolio effect”

24. 24 Quality Assurance & Quality Control Chief Executive Officer Board of Directors Business Unit Staff “Independent” Reserves Committee Technical Manager External Evaluators Internal Resource Management Group Resource Coordinators

25. 25 Summary Resource management teams ensure corporate-wide assessment consistency and quality. SPE classification provides a standard framework. Modifications quantify commercial risk. “Project” synchronizes volume and value. The key is the data model. Hybrid methods quantify technical uncertainty for resource accounting & portfolio management.

26. 26 reserves disclosures Project Database Conclusions Portfolio Management Resource Tracking And Reporting Hybrid Resources Assessments Hydrocarbon Resource Management System There is only one set of books! Integrated QA/QC

27. 27 You now have a happy manager!

28. 28 Key References SPE Reserve and Resource Definitions and Glossary (www.spe.org)www.spe.org Guidelines for Evaluation of Petroleum Reserves & Resources (SPE 2001) SPE 38803: An Integrated Deterministic/Probabilistic Approach to Reserves Estimation – An Update; L.B. Hunt et al. - 1997 SPE 68573: SPE/WPC/AAPG Resource Definitions as a Basis for Portfolio Management; J.M. Ross - 2001 SPE 71424: Aggregating Reserves and Resources for Portfolio Management; J.R. Etherington et al. - 2001