河流-三角洲储层沉积微相的模糊识别Fuzzy diagnosis of sedimentary microfacies in fluvial delta res-ervoir
董焕忠
Dong Huan-zhong ( No. 3 Oil Production Company of Daqing Oilfield Company Ltd. ;
摘要(Abstract)：
针对河流-三角洲储层沉积微相划分问题,提出了一种基于加权模糊推理神经网络的判别方法。该模型可同时处理油田沉积微相研究中的定性专家经验和反映油层沉积微相变化的定量数据。根据取心井分析资料和专家解释结果确定区块沉积微相类型,建立标准模式库,判别待识别小层的沉积微相类型。同时可较好解决过渡性沉积微相在识别中存在的多解性问题。通过对大庆油田萨北开发区23口井的实际资料处理,其符合率达到84.1％。
Focusing on the classification of sedimentary microfacies in fluvial delta reservoir, one diagnosis based on weighted fuzzy neural network is proposed. The qualitative expert experience of sedimentary microfacies research and the quantitative data about the change of sedimentary microfacies in oil layers can be processed at the same time. The sedimentary microfacies model of the area can be determined according to coring well data and the interpretation results of experts, and then the standard model base can be established to determine the sedimentary microfacies types of candidate subzones. Multi results problems exiting in the identification of transitional sedimentary microfacies can be resolved simultaneously. This method is applied to the data of 23 wells in Sabei of Daqing oilfield, and the coincidence rate can reach 84. I % .
关键词(KeyWords)：
沉积微相;测井曲线;模糊神经网络;模式识别
sedimentary microfacies; logging curve; fuzzy neural network; pattern recognition
基金项目(Foundation): 该文为国家自然科学基金资助项目P60373102的部分内容。
作者(Authors):
董焕忠
Dong Huan-zhong ( No. 3 Oil Production Company of Daqing Oilfield Company Ltd. ;