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David Lowry My prospect has a DHI How do I incorporate it in my risk assessment?

Lowry Resources 2017. PESA Lunch Talk 23 February 2017. David Lowry My prospect has a DHI How do I incorporate it in my risk assessment?. Use Powerpoint’s View>Notes Page to see transcript. My prospect has a DHI – how do I incorporate it in my risk assessment?. My prospect:

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David Lowry My prospect has a DHI How do I incorporate it in my risk assessment?

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  1. Lowry Resources 2017 PESA Lunch Talk 23 February 2017 David Lowry My prospect has a DHI How do I incorporate it in my risk assessment? Use Powerpoint’s View>Notes Page to see transcript

  2. My prospect has a DHI – how do I incorporate it in my risk assessment? My prospect: Geological COS 30% DHI; reliability 70% Overall COS? 2-3

  3. Use Bayes’ Theorem My prospect has a DHI – how do I incorporate it in my risk assessment? 2-3

  4. Rev. Thomas Bayes, 1764 An Essay towards solving a problem in the Doctrine of Chances Patron saint of scientists with dodgy data 2-3

  5. Bayes’ Theorem P(A) : initial (prior) estimate of probability perform test P(Fneg) : probability of false negative P(Fpos) : probability of false positive P(revised) : revised probability given a positive test (P(A) – P(A)*P(Fneg)) P(revised) = (P(A) – P(A) *P(Fneg)) + (1–P(A))*P(Fpos) 2-3

  6. 2-3

  7. Medical example I used to belong to a population of caucasian males between ages 60 and 70. Statistics say I have a 3.36% chance of having prostate cancer. Suppose I take a PSA test where there are 12% false positives and 27% false negatives.I test positive, now what is the revised chance that I have cancer? 2-3

  8. Prior risk of prostate cancer 3.36% PSA test Positive PSA: False positives 12% False negatives 27%Revised chance of cancer ????????????? 2-3

  9. Best explained with a matrixConsider population of 10,000 Initial risk 3.36% 2-3

  10. Considerpopulation of 10,000 27% of sick test healthy (false negative) 2-3

  11. Consider population of 10,000 2-3

  12. Consider population of 10,000 12% of healthy test positive for cancer (false positive) 2-3

  13. Consider population of 10,000 2-3

  14. Revised risk 245/1405 = 17% 2-3

  15. Prospect Charge Risk On geological grounds I assess my gas prospect has a 30% COS of charge.The prospect has a DHI;but 30% of the time such a DHI will be generated by something other than hydrocarbons (false +)and 20% of the time gas prospects in the area will not show a DHI (false -)What is the revised COS of charge? 2-3

  16. Consider population of 10,000 similar prospects 2-3

  17. Consider population of 10,000 such prospects 20% of gas prospects don’t show a DHI (false negative) 2-3

  18. Consider population of 10,000 such prospects 30% of water filled prospects show a DHI (false positive) 2-3

  19. Prior COS 3,000 out of 10,000 (30%)Revised COS 2,400 out of 4,500 (53%) 2-3

  20. Risk spreadsheet Structure fault imaging reservoir imaging velocities optimistic interpretation Chargetiming conduits drainage preservation Reservoirsequence developed facies developed quality as modelled no waste zone Sealtop seal lateral seal bottom seal no fault reactivation Sourcetype and richness source rock thickness maturity Lowry Resources Pty Ltd, 2017 2-3

  21. * These elements get a Bayesian update if a DHI is observed Structure fault imaging reservoir imaging velocities optimistic interpretation Charge * timing * conduits * drainage * preservation Reservoirsequence developed facies developed quality as modelled no waste zone Seal* top seal * lateral seal * bottom seal no fault reactivation Source* type and richness * source rock thickness * maturity Lowry Resources Pty Ltd, 2017 2-3

  22. 2-3

  23. If there were no DHI - would it be a false negative? "If this prospect is a gas field, what is the chance of NOT seeing a DHI?“ What would be the chance that this is really a gas field even if I cannot see a DHI?

  24. 2-3

  25. 2-3

  26. * These elements get a Bayesian update if a DHI is observed Structure fault imaging reservoir imaging velocities optimistic interpretation Charge * timing * conduits * drainage * preservation Reservoirsequence developed facies developed quality as modelled no waste zone Seal* top seal * lateral seal * bottom seal no fault reactivation Source* type and richness * source rock thickness * maturity Lowry Resources Pty Ltd, 2017 2-3

  27. Some issues with using Bayes (1) Bayes is great for raising the prospect COS and getting wells drilled If your prospect does not show a DHI when it should - do you have the fortitude to use Bayes to downgrade the prospect? If your prospect has a gas chimney, what does it tell you about fault seal? 2-3

  28. Yardarino 1964 2-3

  29. Some issues with using Bayes (2) “False positive” can have one of two radically different meanings Some purists say that there is no theoretical basis for applying Bayes’ Theorem to the COS of a prospect 2-3

  30. BHP Watson (1998) “ DHIs ... only partly reliable, however, false positive and false negative indications being common. The confidence rating from conventional risking and the DHI risk interact to give a combined value ....” 2-3

  31. 1999 1999 2-3

  32. Press release 2003 “Statoil has selected GeoX for company-wide implementation. GeoX uses Bayesian statistical analysis of seismic anomalies to determine the likelihood of success before drilling.” 2-3

  33. Rose & AssociatesThe Seismic Amplitude Analysis Module (SAAM) .....A consortium of companies, active since 2001, has contributed literally thousands of hours to the design and testing of SAAM ...... SAAM facilitates the systematic and uniform grading of amplitude anomalies. http://www.roseassoc.com/software-oil-gas-prospect-play-portfolio/seismic-amplitude-analysis-module/ 2-3

  34. Rose & AssociatesRoden et al (2010) Threshold effects on prospect risking AAPG Search and Discovery Article #110120 Sansal (2014)“The third calibration option is “Binary Bayesian Conditioning”, which is an experimental approach” 2-3

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