Mathematical Modelling of EOR Methods

Rao Kotini Tirumala, Singh Aman
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Abstract

The choice of appropriate and affordable procedures to boost oil recovery is usually recognized as one of the main challenges in reservoir development due to the huge demand for crude oil. Reservoir flow simulators are valuable tools for understanding and forecasting fluid flow in complex systems. The goal of this study is to run a mathematical model to evaluate the performance of various oil recovery methods, as well as to validate the model's accuracy with simulated field data. Thereby, the results of this developed model indicate that the model is approximately matched with the simulated field data. Enhanced oil recovery typically refers to chemical, miscible, thermal, and microbial processes. A system of nonlinear partial differential equations composed of Darcy's and mass conservation equations governs the model. The system is then numerically solved using the IMPEC (Implicit Pressure and Explicit Concentration) scheme by a finite difference method. We chose this approach because the experimental approaches are not only time consuming, but also costly. As a result, mathematical models could aid in the understanding of a reservoir and how such processes can be optimized to maximize oil recovery while lowering production costs. This paper provides a brief overview of mathematical modelling of various enhanced oil recovery methods, focusing on developing a generalized framework and describing some of the key challenges and opportunities.
提高采收率方法的数学建模
由于对原油的巨大需求,选择合适且价格合理的方法来提高原油采收率通常被认为是油藏开发的主要挑战之一。油藏流动模拟器是了解和预测复杂系统中流体流动的重要工具。本研究的目的是运行数学模型来评估各种采油方法的性能,并通过模拟现场数据验证模型的准确性。因此,该模型的计算结果表明,该模型与现场模拟数据基本吻合。提高采收率通常指的是化学、混相、热和微生物过程。由达西方程和质量守恒方程组成的非线性偏微分方程组控制模型。然后用有限差分法对系统进行了数值求解,采用了隐式压力和显式浓度格式。我们之所以选择这种方法,是因为实验方法不仅耗时,而且成本高。因此,数学模型可以帮助理解储层,以及如何优化这些过程,以最大限度地提高采收率,同时降低生产成本。本文简要概述了各种提高采收率方法的数学建模,重点是建立一个通用的框架,并描述了一些关键的挑战和机遇。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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