Deterministic/Probabilistic Hybrid Assessments of Resources

John R. Etherington
Managing Director, PRA International Ltd, Calgary, AB, Canada

Many authors advise that the answer to consistency in reserves disclosures is the adoption of fixed confidence targets based on fully probabilistic analyses. While the probabilistic method is commonly used in exploration, it has not gained industry-wide application in post-discovery analyses leading to reserves reporting where deterministic methods still dominate.

Evaluators accept that application of Monte Carlo simulation to reservoir parameters in volumetric analyses provides a more comprehensive view of the uncertainty profile of in-place hydrocarbons. However, the reliability of extending the models to incorporate recovery under variable development scenarios to generate realistic production profiles and cash flow schedules is less well accepted. Moreover, as fields mature, performance-based analyses (decline curves, material balance) are more often utilized for production forecasts; probabilistic methods are not commonly applied to these types of assessments.

Reserves evaluators are often faced with the requirement to document deterministic estimates not only for regulatory reporting but also for final design of development programs (well locations, production facilities, etc). An additional complication in the probabilistic method is to clearly reconcile annual changes in the allocation to reserves categories.

Given these practicalities, many companies choose to utilize combinations of assessment methods. Confidence is increased by comparing deterministic scenario results with a full distribution derived from a probabilistic analysis. Other companies go further and use various integration processes to associate confidence levels with scenario estimates; project results can then be utilized in portfolio optimization applications. When rigorously applied, such hybrid solutions incorporate the advantages of both resource assessment methods.

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