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首页» 过刊浏览» 2020» Vol.5» Issue(1) 39-48     DOI : 10.3969/ j.issn.2096-1693.2020.01.004
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滨里海盆地东缘中区块碳酸盐岩储层渗透率预测研究
赵培强,李长文,沙峰,张莉莉,毛志强,蒋新宇
1 中国石油大学( 北京) 油气资源与探测国家重点实验室,北京 102249 2 中国石油大学( 北京) 地球探测与信息技术北京市重点实验室,北京 102249 3 中国石油集团测井有限公司国际事业部,北京 102206 4 长城钻探工程有限公司国际测井公司,北京 100101
Study of permeability prediction of carbonate reservoirs in the middle block of the eastern margin of the Caspian Basin
ZHAO Peiqiang, LI Changwen, SHA Feng, ZHANG Lili, MAO Zhiqiang, JIANG Xinyu
1 State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing 102249, China 2 Beijing Key Laboratory of Earth Prospecting and Information Technology, China University of Petroleum-Beijing, Beijing 102249, China 3 CNPC Logging International Division, Beijing 102206, China 4 International Logging Company, CNPC Greatwall Drilling Company, Beijing 100101, China

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摘要  滨里海盆地东缘中区块石炭系KT-II碳酸盐岩储层孔隙类型复杂多变,导致利用毛管压力曲线准确预测渗透率困难。本文开展了基于毛管压力曲线的Purcell模型、Swanson参数、Capilliary-parachor参数、R25、R35、R50等6种渗透率预测模型在研究区的适用性分析。在此基础之上,以孔隙度和毛管压力曲线特征参数等7 个敏感性参数作为输入向量,利用基于粒子群参数优化的支持向量机方法预测渗透率。研究表明,传统的渗透率模型应用效果差,Purcell模型虽然优于其它几种模型,其预测值与测量值间的确定系数仅为0.763;支持向量机方法预测的渗透率效果良好,训练样本、测试样本的预测结果与测量值的确定系数分别为0.917 和0.883,且相对误差多小于30%,在一定程度上克服了传统渗透率模型对碳酸盐岩储层适用性差的缺陷,为储层评价提供有效信息。
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关键词 : 碳酸盐岩储层;渗透率预测;毛管压力曲线;支持向量机
Abstract

The pore types of Carboniferous KT-II carbonate reservoirs in the middle block of the eastern margin of the Caspian Basin are complex and variable, which makes it difficult to predict the permeability accurately. In the studied area, application analysis was undertaken of six permeability prediction models based on capillary pressure curves. These were the Purcell model,Swanson parameter, capillary-parachor parameter, R25, R35 and R50. On this basis, seven sensitive parameters including porosity and other parameters obtained from capillary pressure curve are selected as input vectors, and the particle swarm optimization support vector machine (PSO-SVM) method is used to predict permeability. Results show that the traditional permeability models provide unreasonable results. Although the Purcell model is superior to other models, the coefficient of determination between predicted and measured results is only 0.763. The permeability predicted by support vector machine is reliable. The coefficients of determination of predicted results of training samples and test samples with measured values are 0.913 and 0.854,respectively. The proposed method overcomes the shortcomings of the traditional permeability model to carbonate reservoirs to a certain extent, and provides valuable information for formation evaluation.

Key words: carbonate reservoir; permeability prediction; capillary pressure curve; support vector machine
收稿日期: 2020-03-28     
PACS:    
基金资助:中国石油集团测井有限公司项目“乍得、尼日尔复杂油气层测井评价技术研究与应用”(2016D-4502) 资助
通讯作者: maozq@cup.edu.cn
引用本文:   
赵培强, 李长文, 沙峰, 张莉莉, 毛志强, 蒋新宇. 滨里海盆地东缘中区块碳酸盐岩储层渗透率预测研究. 石油科学通报, 2020, 01: 39-48
链接本文:  
ZHAO Peiqiang, LI Changwen, SHA Feng, ZHANG Lili, MAO Zhiqiang, JIANG Xinyu. Study of permeability prediction of carbonate reservoirs in the middle block of the eastern margin of the Caspian Basin. Petroleum Science Bulletin, 2020, 01: 39-48.
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