What Is the Chance for Success?

As exploration professionals, half our job involves estimating various geotechnical parameters that characterize our prospects and plays. Most of us, however, have had little or no training in effective estimating methods.

In [PFItemLinkShortcode|id:20634|type:standard|anchorText:Last month's column|cssClass:asshref|title:read more|PFItemLinkShortcode] we reviewed six ways to improve our estimates of the variable factors - uncertain parameters such as productive area, average net pay, HC-recovery factor, recoverable reserves, flow rates and project costs.

This month we’ll discuss effective methods for estimating existence factors - our confidence (= probability) that key geologic requirements such as HC-charge, reservoir and closure have been satisfied in the subsurface by Mother Nature.

The general industry convention is to estimate the variable factors as probabilistic ranges, whereas the existence factors are estimated as unique decimal fractions, whose product represents the chance that a reservoired, detectable (i.e. flowable) accumulation is indeed present at depth.

Most experienced evaluators agree that better results are obtained by assessing the different geologic attributes separately, rather than estimating only the prospect chance of geologic success. Naturally, this assumes that the individual geologic attributes are statistically independent - that the presence of reservoir rock is not influenced by the existence (or absence) of HC-source rock or closure.

For single-objective prospects, this usually isn’t a problem - but for multizone prospects, it does have to be considered. For now, let’s keep it simple.

The reason why we need to estimate the geological chance of success and failure (= Pg and Pf), of course, is that they are key items in calculation of Expected Present Value (EPV) of the venture, i.e., its chance-weighted present monetary value. (Often we recognize that geological success may not be commercial success, so to arrive at the chance that the well will be completed, reduce Pg proportional to how much of the prospect reserves distribution is greater than the commercial threshold.)

Here are eight tested tips to help you make better estimates of your prospect’s chance of geological success:

• Be sure you have a geological model for the prospect in mind before you start, well supported by maps and cross-sections.
• Having a proposed drilling location on the map will help you focus on the problem.
• Review the prospect with the most knowledgeable professionals - the prospect team.
• Consider all evidence objectively and rigorously, taking into account quality and quantity of data. Maintain a courteous, professional tone throughout your deliberations - you don’t want to suppress any pertinent data or ideas. Remember, the objective is not to sell the prospect, it is to evaluate it honestly.
• Use a probability scale (Figure 1) to help geoscientists and engineers sense and express their individual subjective confidence in the existence of the various geologic attributes.



Figure 1. Subjective expressions of confidence.

• For each chance-factor, ask, “What can hurt us here?” As a reality check, try to estimate the chance of failure (i.e., non-existence), rather than existence.
• Remember that geologic chance of success has nothing to do with economics - it’s only an estimate of the chance that Mother Nature has caused a flowable reservoir accumulation of oil and/or gas to be present.
• Before the group finalizes its consensus probability for each chance factor, ask each member to independently write down his/her estimate - then record them for the group.
• Discuss “outlier” estimates - many of these reflect either important unique knowledge, or incorrect or incomplete knowledge that may be modified. If anyone then wishes to revise his/her estimate, enter it, and then average the estimates.
• Remember that changing a chance-factor from 0.3 to 0.4 has a much bigger impact on Pg than a change from 0.8 to 0.9, so spend more time on the lower chance factors (= critical risks).
• Remember that estimating is not exact - beware of false precision.
• For each geologic chance-factor, compare other prospect chance-factors - i.e., “Are you as confident of Reservoir as you were of Closure?”
• Compare estimated probabilities against previous estimates for counterpart prospects. Are estimates consistent, considering data quality and quantity, and known geological characteristics of the trend?
• Faithfully keep track of your estimates and compare them against actual outcomes.

Are you usually anticipating critical risk correctly? What were the actual success-rates of different risk-classes of your prospects?

Learn from your experiences!