Development of a new empirical correlation for predicting formation volume factor of reservoir oil using artificial intelligence
https://doi.org/10.21285/2686-9993-2021-44-4-408-416
Abstract
It is known that oil in reservoir conditions is characterized by the content of a certain amount of dissolved gas. As reservoir pressure decreases this gas is released from oil significantly changing its physical properties, primarily its density and viscosity. In addition, the oil volume also reduces, sometimes by 50–60 %. In this regard, when calculating reserves, it is necessary to justify the reduction amount of the reservoir oil volume when oil is extracted to the surface. For this purpose, the concept of formation volume factor of reservoir oil has been introduced. The formation volume factor of oil is considered one of the main characterizing parameters of crude oil. It is also required for modeling and predicting the characteristics of an oil reservoir. The purpose of the present work is to develop a new empirical correlation for predicting the formation volume factor of reservoir oil using artificial intelligence methods based on MATLAB software, such as: an artificial neural network, an adaptive neuro-fuzzy inference system, and a support vector machine. The article presents a new empirical correlation extracted from the artificial neural network based on 503 experimental data points for oils from the Eastern Siberia field, which was able to predict the formation volume factor of oil with the correlation coefficient of 0.969 and average absolute error of less than 1 %. The conducted study shows that the prediction accuracy of the desired parameter in the developed artificial intelligence model exceeds the accuracy of study results obtained by conventional statistical methods. Moreover, the model can be useful in the prospect of process optimization in field planning and development.
About the Authors
E. V. Shakirova
Irkutsk National Research Technical University
Russian Federation
Competing Interests:
Russian Federation
Elvira V. Shakirova, Cand. Sci. (Polit.), Associate Professor, Associate Professor of the Department of Oil and Gas Engineering, Institute of Subsoil Use
Irkutsk
Competing Interests:
The authors declare no conflicts of interests.
A. A. Aleksandrov
University of Tyumen
Russian Federation
Competing Interests:
Russian Federation
Aleksandr A. Aleksandrov, Student, Polytechnic School
Tyumen
Competing Interests:
The authors declare no conflicts of interests.
M. V. Semykin
Irkutsk National Research Technical University
Russian Federation
Competing Interests:
Russian Federation
Mikhail V. Semykin, Student, Institute of Subsoil Use
Irkutsk
Competing Interests:
The authors declare no conflicts of interests.
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Review
For citations:
Shakirova E.V., Aleksandrov A.A., Semykin M.V. Development of a new empirical correlation for predicting formation volume factor of reservoir oil using artificial intelligence. Earth sciences and subsoil use. 2021;44(4):408-416. (In Russ.) https://doi.org/10.21285/2686-9993-2021-44-4-408-416
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