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作 者:史浩 刘小波[2] 林利明 王振国 郭俊超 Shi Hao;Liu Xiaobo;Lin Liming;Wang Zhenguo;Guo Junchao(China United Coalbed Methane Co.,LTD,Beijing 100015;Northeast Petroleum University,Daqing 163318)
机构地区:[1]中联煤层气有限责任公司,北京100015 [2]东北石油大学,黑龙江大庆163318
出 处:《石化技术》2024年第5期273-275,共3页Petrochemical Industry Technology
基 金:中海石油中国有限公司重大科技专项“中联公司上产60亿方关键技术研究”(编号:CNOOC-KJ 135 ZDXM 40);中联煤层气有限责任公司自主立项科研项目“神府区块木瓜区煤系地层致密气储层高精度识别及关键技术研究”联合支持。
摘 要:鄂尔多斯盆地东缘神府木瓜区上古生界属于典型的致密砂岩气藏,储层甜点受岩性、物性多重因素控制。下石盒子组盒8段为辫状河沉积,砂岩与泥岩波阻抗差异小,因此常规波阻抗反演方法和地震属性难以达到有效储层预测。通过神经网络技术,对下石盒子组致密砂岩储层进行预测,应用效果较好,为该技术的推广应用提供了依据。The Upper Paleozoic in the Shenfu Mugua area of the eastern margin of the Ordos Basin belongs to a typical tight sandstone gas reservoir,and the sweet spots of the reservoir are controlled by multiple factors such as lithology and physical properties.The He8 section of the Lower Shihezi Formation is a braided river deposit,with small differences in wave impedance between sandstone and mudstone.Therefore,conventional wave impedance inversion methods and seismic attributes are difficult to achieve effective reservoir prediction.The neural network technology was used to predict the tight sandstone reservoir of the Lower Shihezi Formation,and the application effect was good,providing a basis for the promotion and application of this technology.
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