油藏监测动态物质平衡法的改进

K. Lawal, O. Okoh, Asekhame U. Yadua, Mathilda I. Ovuru, S. Eyitayo, S. Ramaswamy
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引用次数: 1

摘要

如果有足够的性能和其他数据,物质平衡(MB)是确定储层中初始就位(HCIIP)碳氢化合物的常用方法。该方法的应用至少需要历史累积产量(包括注入)和平均储层压力。然而,要确定历史平均油藏压力需要关井,因此需要推迟生产。动态物质平衡法(DMB)是Mattar和Anderson(2005)对经典物质平衡法的改进。与MB方法不同,直接测量平均储层压力对DMB并不重要。在DMB的基本形式中,实施DMB需要历史产量、井底流动压力和累积产量,从而消除相关的延迟。尽管DMB在某些应用中表现令人满意,但其整体稳健性仍有待充分探索。本文对选定的DMB模型进行了严格的灵敏度检查。根据所获得的见解,突出了它们的相对优势和劣势。为了保持问题的可处理性,对已知HCIIP的不同三维多相均质油藏模型进行了详细的模拟。通过模拟不同的情况,生成相关的性能数据集来评估DMB。对该欠饱和可压缩油藏进行的参数测试包括:(1)恒定与可变产量;(ii)速率滞后;(iii)直井与水平井;(iv)单井与多井;(v)健康井与受损井;(六)皮肤因素可变,具有迟滞性。在测试的参数空间内,仿真结果表明DMB性能(例如HCIIP)对所研究的一些参数和地下实现非常敏感。在此背景下,提出了一些改进和指导方针,以提高DMB作为水库监测技术的能力和性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improvements to the Dynamic Material-Balance Method of Reservoir Surveillance
Given sufficient performance and other data, material balance (MB) is a common method of determining the hydrocarbons initially in-place (HCIIP) in a reservoir. The application of this method requires, as a minimum, historic cumulative production (including injection) and average reservoir pressure. However, determination of historic average reservoir pressures would require shut-in of wells, hence production deferments. As an improvement to the classical MB, the dynamic material balance (DMB) method was developed by Mattar and Anderson (2005). Unlike the MB method, direct measurements of average reservoir pressure are not critical to DMB. In its basic form, the implementation of DMB requires historic production rates, flowing bottomhole pressures and cumulative production, thereby eliminating associated deferments. Although DMB has performed satisfactorily in some applications, its overall robustness remains to be fully explored. This paper conducts rigorous sensitivity checks on selected DMB models. Based on insights gained, their relative strengths and weaknesses are highlighted. To keep the problem tractable, detailed simulations are performed on different three-dimensional (3D) multiphase homogenous reservoir models of known HCIIP. Different cases are simulated, generating relevant performance datasets to evaluate DMB. The parametric tests conducted on this undersaturated compressible oil reservoir include (i) constant vs. variable production rates; (ii) rate hysteresis; (iii) vertical vs. horizontal well; (iv) single vs. multiple wells; (v) healthy vs. damaged well; and (vi) variable skin factors, with hysteresis. Within the parameter space examined, simulation results show that DMB performance (e.g. HCIIP) is sensitive to some of the parameters and subsurface realisations investigated. Against this background, some improvements and guidelines are proposed to enhance the capability and performance of DMB as a technique for reservoir surveillance.
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