| 非常规气藏储层改造体积评价方法研究 |
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| 引用本文： | 罗睿乔.非常规气藏储层改造体积评价方法研究[J].中州煤炭,2022,0(2):220-226. |
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| 作者姓名： | 罗睿乔 |
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| 作者单位： | （中海石油（中国）有限公司 深圳分公司，广东 深圳 518000） |
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| 摘 要： | 为精确描述非常规气藏压裂后的复杂流动特征及定量评价储层改造体积（SRV），利用自主研发的缝网重构算法“破裂树生长法”建立压后缝网模型，并以此为基础提出了使用拟稳态流动时特定的压力等值线来确定SRV范围的定量评价方法，最后以长宁201井区为例进行了矿场实例分析。该方法根据微地震监测点的位置，重构出微裂缝网的连通关系。在复杂微裂缝网的基础上建立离散裂缝地质模型并进行生产数值模拟，根据数值模拟结果的压力分布精确划定SRV的范围。利用该方法计算出长宁201井区的SRV体积为0.052 1 km3，以该缝网模型的数值模拟产量预测结果符合实际生产规律，方法实用性较好。
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| 关 键 词： | 微地震 裂缝重构 SRV 离散裂缝模型 产能预测 |
Research on evaluation method of stimulated reservoir volume of unconventional gas reservoirs |
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| Luo Ruiqiao. Research on evaluation method of stimulated reservoir volume of unconventional gas reservoirs[J].Zhongzhou Coal,2022,0(2):220-226. |
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| Authors: | Luo Ruiqiao |
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| Affiliation: | （CNOOC China Limited，Shenzhen Branch，Shenzhen 518000，China） |
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| Abstract: | In order to accurately describe the complex flow characteristics of unconventional gas reservoir after fracturing and quantitatively evaluate the reservoir reconstruction volume (SRV),the fracture network model after fracturing is established by using the self developed fracture network reconstruction algorithm "fracture tree growth method",and on this basis,a quantitative evaluation method to determine the SRV range by using the specific pressure isoline during quasi steady state flow is proposed.Finally,taking Changning 201 well area as an example,a mine example is analyzed.According to the location of microseismic monitoring points,the connectivity of micro fracture network is reconstructed.Based on the complex micro fracture network,the discrete fracture geological model is established and the production numerical simulation is carried out.The range of SRV is accurately defined according to the pressure distribution of the numerical simulation results.Using this method,the SRV volume of Changning 201 well block is calculated to be 0.052 1 km3.The numerical simulation production prediction results of the fracture network model accord with the actual production law,and the method is practical. |
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| Keywords: | ,micro-seismic, fracture network reconstruction, SRV, discrete fracture model, prediction forecast |
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