Prospect Risk and Benchmarking using Wildcat

Report Summary

The Industry has a long track record of generally underestimating the chance of geological success of
exploration prospects and an overestimation of success case volumes, resulting in a significant
proportion of non-commercial discoveries. This is well documented in the literature and supported by
data from Westwood’s Wildcat database and information shared in Rose & Associates Risk
Coordinators network.
Westwood’s Wildcat database includes 220 technical or commercial discoveries made since 2008
where both pre- and post drill resource estimates are available. These data demonstrate that 78% of
discoveries have found less than the pre-drill P50 estimate and 28% have been lower than the pre-drill
P90 (assuming that reported pre-drill volumes represent the P50 case). 45% of frontier discoveries
have found less than the pre-drill P90 estimate. Reported P10/P90 ratios vary between 1.5 and 41.5
with an average of 8.3.

Best practice advocates the use of regular “look back analyses” to understand where systematic errors
in estimation of chance of success or success case volumes may be generated. Look back analyses,
however, require access to a statistically significant number of wells. This can be difficult for
companies with limited exploration programmes and has become exacerbated by the reduction in
global exploration activity following the oil price crash of 2014.

Exploration success rates and discovered volumes typically vary according to the maturity of a play
being explored, with success rates typically increasing and volumes decreasing as a play moves along
the creaming curve. “Base rate” success rates and volumes can provide a benchmark to guide prospect
chance of success and volume estimation whilst not replacing effective technical assurance of
exploration activity.

Access to global prospect analogue databases can provide effective calibration and benchmarking of
volumes ranges and expected success rates by allowing plays to be compared to local or global
analogues taking into account geology and play maturity. The use of play analogue databases can also
mitigate against the cognitive bias that often leads to inaccurate estimation of risk and volume.

1. Summary
2. Introduction
3. Estimation of Chance of Success
   • Examples from Literature
4. Estimation of Success Case Volumes
   • Examples from Literature
   • Examples from Wildcat
     • Prospect Size
     • Play Maturity
     • Trap Type
5. Using Wildcat to Calibrate Chance of Success
6. Using Wildcat to Calibrate Success Case Volumes
   • Example: Gulf of Mexico
   • Example: Barents Sea
7. Discussion
   • Current Best Practice in Risk and Resource Estimation
   • The Importance of Lookback Analysis
   • Impact of Cognitive Bias
   • The Value of Global Databases
8. Conclusions
9. References
10. Disclaimer