--> Abstract: Reserves Prediction in Exploration - the Trap We Have Got Ourselves Into and How to Deal with It; #90063 (2007)

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Reserves Prediction in Exploration - the Trap We Have Got Ourselves Into and How to Deal with It

 

Quirk, Dave1, Rick Ruthrauff2 (1) Maersk Oil, Copenhagen K, Denmark (2) Hess Corporation, Houston, TX

 

Existing data from wells allow for the confident prediction of many things in exploration. For example, within mature plays, geological risk in a new prospect differs little from historical success in the same play. Reservoir properties such as porosity and net thickness belong to simple normal or lognormal distributions from which it is straightforward to calculate cumulative probabilities. Yet exploration programs rarely deliver what they predict. In an increasingly probabilistic world using apparently reasonable ranges of parameters, why are prospect reserves usually biased to the upside? Despite all the technology and data we now have, even getting consistency in reserves assessments seems unachievable.

 

The problem lies with the parameter having the greatest influence on reserves estimates in an undrilled prospect – trap size. Unfortunately, a realistic distribution for trap size cannot be built because there are no direct samples of the bounding surfaces. In other words, cumulative probabilities associated with gross rock volume or area-net are not predictable, putting into question the way probabilistic methodologies are currently used in exploration.

 

Fortunately, there is a solution but it involves partially sidestepping the trap size issue and locking on to two things most interpreters can agree on – the culmination and last closing contour. With this basic information, and a standard way of inputting reservoir information, we have devised a reliable method of calculating the size and chance of finding upside reserves (what exploration is really about) and then, by extrapolation, it becomes easy to fully account for the downside (half of all discoveries).

 

AAPG Search and Discover Article #90063©2007 AAPG Annual Convention, Long Beach, California