Release:2018, Vol. 4. №4
About the authors:Olga A. Yadryshnikova, Section Head, Tyumen Petroleum Research Center; firstname.lastname@example.org
In the oil and gas industry, a large amount of heterogeneous geological and geophysical information is necessary to assess hydrocarbon reserves. There are high risks of incorrect assessment of hydrocarbon reserves in the absence or inaccurate information.
In this article, the authors estimate oil and gas reserves in the cases, when there is insufficient data, especially at the stage of exploration of deposits. Therefore, the methods of probabilistic and fuzzy implementations are of particular interest since deterministic estimation does not provide knowledge about the calculation error. An adequate assessment of the estimated parameters in difficult conditions, unconventional, and complex built-up promising hydrocarbon reserves is required. The modern technology “Digital Kern” is considered promising. A comprehensive approach to solving problems using all kinds of data on complex oil and gas facilities is required.
The authors have used probabilistic methods, methods of the theory of fuzzy sets and fuzzy logic, as well as methods of pattern recognition. This article presents a set of programs that uses an integrated approach and implements both a model for calculating reserves and determining the estimated parameters using new modern intelligent computing technologies for processing information in assessing hydrocarbon reserves under uncertainty. They include:
This software complex is intended to improve the quality in the assessment of hydrocarbon reserves, improve the reliability of determining the estimated petrophysical parameters in the absence or absence of data.