| 井控主成分分析技术在储层预测中的应用 |
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| 引用本文： | 高斌,王志坤,付兴深,霍丽丽,段彬,潘以红.井控主成分分析技术在储层预测中的应用[J].沉积学报,2018,36(1):198-205. |
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| 作者姓名： | 高斌 王志坤 付兴深 霍丽丽 段彬 潘以红 |
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| 作者单位： | 1.中国石油冀东油田公司, 河北唐山 063004; |
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| 摘 要： | 南堡凹陷中浅层火成岩类型多、非均质性强，利用单一技术方法难以有效刻画火成岩和砂岩储层的空间分布，制约了中浅层砂岩油气藏的勘探开发。在岩石物理交会分析基础上，利用对岩性响应敏感的纵波阻抗、伽马、泊松比和甜点4类地震属性和PCA主组分降维技术，对玄武岩、蚀变火成岩、砂岩、泥岩四类岩性进行了有效的区分，利用创新的井控综合解释技术获得了最终岩性体数据，达到在复杂岩性背景下准确识别砂岩储层的目的。结果表明，地震预测与实钻情况吻合程度较高，达到87.1%，预测的火成岩与砂岩分布特征与区域地质认识相匹配，为研究区滚动开发和开发调整提供了有力技术支撑。
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| 关 键 词： | 岩性识别 主成分分析(PCA) 砂岩储层 地震属性分析 |
| 收稿时间： | 2017-04-11 |
Application of Well Controlled Principal Component Analysis in Reservoir Prediction |
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| GAO Bin,WANG ZhiKun,FU XingShen,HUO LiLi,DUAN Bin,PAN YiHong.Application of Well Controlled Principal Component Analysis in Reservoir Prediction[J].Acta Sedimentologica Sinica,2018,36(1):198-205. |
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| Authors: | GAO Bin WANG ZhiKun FU XingShen HUO LiLi DUAN Bin PAN YiHong |
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| Institution: | 1.PetroChina Jidong Oilfield Company, Tangshan, Hebei 063004, China;2.LandOcean Energy Services Company Ltd., Beijing 100094, China |
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| Abstract: | The igneous rock of shallow layer developed in NanPu Depression has many types and strong heterogeneity laterally and vertically present,which are difficult to describe the spatial distribution of igneous rocks and sandstone reservoirs. As the identification of the igneous rock distribution is very critical for the confirmation of sandstone gas/oil reservoir development feature,so, multiple technologies integration is urgent need instead of only by single geology and geophysical technology. The prediction of sandstone reservoirs restricts the exploration and development of sand-stone reservoirs in shallow layers. In this study,based on the rock physical property analysis, combined P-wave im-pedance,Gamma,Poisson ratio and Sweet seismic attributes which are sensitive to various lithology and PCA dimen-sion reduction technology,four lithologies which are basalt,altered volcanic rock,sandstone and mudstone have been effectively distinguished. And lithology cube is built by using innovative technology of well constrained interpretation, so that,the identification of sandstone reservoir with high accuracy can be achieved. From the comparison, the final seismic prediction result is consistent with the regional geology distribution feature, and with coefficient of 87.1%matching with well data. The distribution of igneous rocks and sandstones are matched with regional geology. |
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