| 应用地质和地震反演信息进行三维沉积微相随机建模 |
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| 引用本文： | 吴胜和,刘英,范峥,苏彦春,尹伟,张国明,古莉.应用地质和地震反演信息进行三维沉积微相随机建模[J].古地理学报,2003,5(4):439-449. |
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| 作者姓名： | 吴胜和 刘英 范峥 苏彦春 尹伟 张国明 古莉 |
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| 作者单位： | 1.石油大学 北京102249;2.中海石油研究中心渤海研究院 天津塘沽 300450 |
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| 基金项目： | 国家“十五”重大科技攻关项目(2001BA605A09)的部分研究成果 |
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| 摘 要： | 探讨了综合应用地质及测井约束地震反演信息进行三维沉积微相随机建模的基本原理、思路与方法，并以渤海湾盆地某区块新近系明化镇组河流相储层为例，说明这一研究过程的基本步骤，包括井眼沉积微相解释、测井约束地震反演、波阻抗与地质相的概率关系分析、随机模拟方法选择、地质统计特征分析、三维随机建模、随机模拟预测的多解性评价。研究表明，波阻抗与沉积微相之间具有一定的概率相关关系。综合应用包括地震信息在内的多学科信息进行沉积微相随机建模，可对储层预测的多解性进行有效评价。
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| 关 键 词： | 沉积微相 储层 随机建模 测井约束反演 地震 |
| 文章编号： | 1671-1505(2003)04-0439-11 |
| 修稿时间： | 2003年4月5日 |
3D STOCHASTIC MODELING OF SEDIMENTARY MIC-ROFACIES WITH GEOLOGICAL AND SEISMIC DATA |
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| Wu Shenghe Liu Ying Fan Zheng Su Yanchun Yin Wei Zhang Guoming Gu Li
University of Petroleum,Beijing Bohai Research Institute of CNOOC,Tanggu ,Tianjin.3D STOCHASTIC MODELING OF SEDIMENTARY MIC-ROFACIES WITH GEOLOGICAL AND SEISMIC DATA[J].Journal of Palaeogeography,2003,5(4):439-449. |
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| Authors: | Wu Shenghe Liu Ying Fan Zheng Su Yanchun Yin Wei Zhang Guoming Gu Li
University of Petroleum Beijing Bohai Research Institute of CNOOC Tanggu Tianjin |
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| Institution: | 1.University of Petroleum,Beijing 102249;2.Bohai Research Institute of CNOOC,Tanggu 300450,Tianjin |
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| Abstract: | The basic principle and method of 3D stochastic modeling of sedimentary microfacies are discussed according to geological and acoustic impedance data of well-logging constrained seismic inversion, and a case study according to stochastic modeling of fluvial facies reservoir of the Minghuazhen Formation of Neocene in a certain block of Bohai Bay Basin is used to show the general process of this research. The general process of this study includes sedimentary microfacies interpreting within boreholes, well-logging constrained seismic inversion, probability relation analysis between acoustic impedance and sedimentary microfacies, selecting the method of stochastic modeling, analysis of geological statistical characteristics, 3D stochastic modeling and assessment to multi-solutions of forecasting of stochastic modeling. The results show that there are some correlative probability relations between acoustic impedance and sedimentary microfacies, and the stochastic modeling of sedimentary microfacies can make an effective assessment to multi-solutions of reservoir forecasting by synthetically applying multi-disciplinary information, including seismic data. |
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| Keywords: | sedimentary microfacies reservoir stochastic modeling well-logging constrained inversion seismic |
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