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The AAPG/Datapages Combined Publications Database

AAPG Special Volumes

Abstract


Pub. Id: A028 (1984)

First Page: 15

Last Page: 26

Book Title: M 35: Petroleum Geochemistry and Basin Evaluation

Article/Chapter: Worldwide Geological Experience as a Systematic Basis for Prospect Appraisal

Subject Group: Geochemistry, Generation, Migration

Spec. Pub. Type: Memoir

Pub. Year: 1984

Author(s): D. Sluijk, M. H. Nederlof

Abstract:

To evaluate the uncertain hydrocarbon potential of single exploration prospects, use is made of a computer model to simulate the processes of hydrocarbon generation, expulsion and migration (leading to "hydrocarbon charge"), trapping and retention, and finally recovery.

Simulation of the charge and retention processes is based on the results of various "calibration studies". Such studies imply the statistical analysis of extensive data sets, which represent worldwide exploration experience. The statistically highly significant results of these studies are built into the simulation model.

For the estimation of the probability of charge, worldwide prior probabilities are updated in two steps: firstly, on the basis of prior observations of charge in the area of the prospect; and secondly, on the basis of the generation and migration parameters specific to the prospect in question. The latter update is made in line with the results of the statistical analysis of the charge calibration file, which is a representative collection of numerous case histories. This learning set also forms the basis for the estimation of the charge volumes.

In the simulation of the complex process of trapping and retention, the sealing capacity plays a role. Based on the analytical results of another calibration file, the seal properties as described by the appraiser can be used to estimate the retention potential of the seal (i.e., the maximum differential pressure, or hydrocarbon column, the seal can withstand).

The conceptual models followed in the calibration studies mentioned above are deliberately simple, so that the parameters needed for the description of the model can be readily estimated during actual prospect appraisal. This simplicity, and the implicit incompleteness of the models, contributes to uncertainties in the resulting formulas. The residual errors, however, are taken into consideration when the formulas are applied in the simulation model, the less significant parameters receiving less weight in the end result.

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