Abstract: Reducing Exploration Risk by Improving Pre-Drill Estimates

David F. Nicklin, C. R. K. Moore, R. A. Noble, K. Touysinhthiphonexay

ARCO for many years has applied an analytical approach to estimation of the range of reserves that might be discovered by an exploratory success. Log normal distributions of average net pay, productive area and recovery factor traditionally have been defined, and the mean and variance of the resulting reserves distribution have been calculated by straightforward multiplication. This approach works well in mature areas where geologic control is good and an exploration team has considerable experience. As an example, the method has been a powerful predictor of discovered reserves in recent years in ARCO's Offshore Northwest Java contract area in Indonesia.

This analytical approach has been less satisfactory in rank wildcat settings. Since the quality of the predictions can only be measured in successful wells, the method is difficult to apply when only a very few exploratory tries result in discovered hydrocarbons. Not enough fundamental geological and geophysical parameters are defined to test predictive accuracy when wells are dry. Geologists also have had philosophical difficulty with a system that does not separately evaluate the two independent variables of trap capacity and charge availability.

In order to improve estimation of potential reserves in wildcat plays. ARCO has recently developed a new approach that quantifies the petroleum charge to a trap. The volume of hydrocarbons generated and expelled from a source rock, and conveyed to a trap is calculated from input parameters like source lithology and thickness, kerogen type and richness, maturation level, areal extent of the source rock, and migration loss per unit area of fetch. Estimated reservoir conditions in the trap are used to combine the oil and gas in the hydrocarbon charge with an appropriate gas-oil ratio. The new approach is embodied in a software system called PROSPEX. To quantify the uncertainty in the charge calculation, PROSPEX takes full advantage of the efficient Monte Carlo package now available on de ktop computers.

It is too early to know how much improvement in the accuracy of reserves predictions will result from the introduction of PROSPEX. As has been true for ARCO's traditional approach, the reliability of the new approach depends on continuous comparison between actual results and predictions at the prospect and program levels. Both careful recording of geological and geophysical predictions and rigorous attention to post-mortems as positive learning experiences are important to successfully using any evaluation system to reduce exploration risk.

AAPG Search and Discovery Article #90986©1994 AAPG Annual Convention, Denver, Colorado, June 12-15, 1994