A new approach to predict the formation pressure using multiple regression analysis: Case study from the Sukharev oil field reservoir – Russia

Q1 Chemical Engineering
Inna N. Ponomareva , Dmitriy A. Martyushev , Suresh Kumar Govindarajan
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引用次数: 0

Abstract

Formation pressure is an important indicator of field production potential. Currently, the common practice to estimate reservoir pressure is the hydrodynamic exploration test. This method requires shutting down the well, often for a long time. Such long shutdowns lead to less production from the reservoir and worsen the economics of the field. Here, we present the method for determining the pressure without shutting down the well by using statistical methods for such tasks. In this article, we describe the method of finding the formation pressure by using multidimensional multivariate analysis of the actual reservoir data from the Sukharev field. To build the model, several operational, geological, and reservoir properties at various stages of the field pressure were combined into a model to predict reservoir pressure. Results showed that with this simple statistical method, formation pressure varies in two distinctive stages. In the first stage, the formation pressure is influenced by the reservoir petrophysical parameters, whereas in the second stage, operational parameters were more prominent. Finally, three separate formations in the Sukharev field were examined to predict reservoir pressure, and the results were in very good agreement with the actual measured data. This confirmed that the method was practical and capable of predicting reservoir pressure at any time of the well's lifetime.
多元回归分析预测地层压力的新方法——以俄罗斯苏哈列夫油田为例
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来源期刊
Journal of King Saud University, Engineering Sciences
Journal of King Saud University, Engineering Sciences Chemical Engineering-Fluid Flow and Transfer Processes
CiteScore
12.10
自引率
0.00%
发文量
87
审稿时长
63 days
期刊介绍: Journal of King Saud University - Engineering Sciences (JKSUES) is a peer-reviewed journal published quarterly. It is hosted and published by Elsevier B.V. on behalf of King Saud University. JKSUES is devoted to a wide range of sub-fields in the Engineering Sciences and JKSUES welcome articles of interdisciplinary nature.
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