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基于等效渗流角模型的顺北油田线性流地层渗透率确定方法
断块油气田
2022年 29卷 第2期
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Title
The permeability determining method for linear flow reservoirs in Shunbei oil field based on the equivalent seepage angle model
单位
中国石化西北油田分公司完井测试管理中心,新疆 轮台 841600
西南石油大学油气藏地质及开发工程国家重点实验室,四川 成都 610599
Organization
Well Completion and Test Management Center, Northwest Oilfield Company, SINOPEC, Luntai 841600, China
State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610599, China
摘要
断溶体油藏中的流动存在明显的地层线性流特征,传统的试井解释采取复合径向流模型得到的渗透率难以反映线性流的渗透率特征。针对此问题,文中从渗流角的角度,建立了可以等效反映断溶体油藏形状对渗透率影响的方法,通过数值模型,反演得到了不同形状条件下的油藏渗流角。研究发现,线性流的等效渗流角与油井对应的泄流区域长宽比的反余切值相关。当油藏的长宽比小于10∶8.5时,地层流动以径向流为主,而当长宽比大于10∶3.0时,油藏的主控流态转变为线性流。当地层处于线性流阶段时,采用常规试井得到的等效径向流渗透率会明显低于储层的渗透率。
Abstract
There is an obvious formation linear flow process in fault-karst reservoirs. The permeability obtained by traditional well-testing interpretation using compound radial flow model is difficult to reflect the permeability characteristics of linear flow. In order to solve this problem, this paper establishes a method from the perspective of seepage angle, which can reflect the influence of fault-karst reservoir shape on permeability calculation equivalently. Through the numerical model, the reservoir seepage angle under different shape conditions is inversed. It is found that the equivalent seepage angle of linear flow is related to the inverse cotangent value of the length width ratio of the discharge area corresponding to the oil well. When the aspect ratio of the reservoir is less than 10.0∶8.5, the formation flow is dominated by radial flow. While the aspect ratio is greater than 10∶3.0, the main flow pattern of the reservoir changes to linear flow. As the formation is in the stage of linear flow, the equivalent radial flow permeability obtained by conventional well testing will obviously underestimate the permeability value of the reservoir.
关键词:
断溶体油藏;
线性流;
等效渗流角;
试井分析;
数值模型;
Keywords:
fault-karst reservoir;
linear flow;
equivalent seepage angle;
well testing;
numerical model;
DOI
10.6056/dkyqt202202019