摘要
根据研究区的沉积特征和测井曲线模式 ,在取心井的单井相划分的基础上 ,建立各微相的样本库 ;然后根据取心井的测井资料 ,运用统计学结合计算机编程 ,统计各个样本井段上储层参数分布特征 ,建立不同微相上各参数分布模式 ;最后根据各微相上参数分布模式建立判别方程 ,利用其判别其他测井井段的沉积微相类型 .这种方法通过计算机编程将已知沉积微相的认识模式化去认识未知目标沉积微相 .在大港枣南油田研究中 ,综合运用泥质含量、单砂体厚度、砂体含泥量等参数 ,快速而准确地判别了 32 1口井 13个小层沉积微相 .实践证明 ,多参数综合方法融合了传统方法和统计学方法识别沉积微相的优点 。
A method for identifying the sedimentary facies is proposed. It can be described as follows: first, the single well sedimentary facies of core-wells are divided according to the depositional features and the logging curve pattern in the studied area. On the basis of the division, the sample databases of sedimentary facies are built up. Next, the important reservoir parameters used for identifying sedimentary facies are checked out, and the distribution patterns of the reservoir parameters of different sedimentary facies are obtained using statistic method according to the sample databases. Finally, a multi-parameter identifying equation is established from all the parameter distribution patterns of different sedimentary facies, and it can be used to identify the depositional facies of other well intervals. The multi-parameter identifying sedimentary facies method has the advantages of both the traditional methods and the statistical methods. It uses the recognition model established by the features of the known sedimentary facies for identifying unknown sedimentary facies. As an example, this method is applied in Zaonan oilfield, Dagang. Shale content, the thickness of single sand body and the shale content in the sandstone are selected as the reservoir parameters. The depositional facies of 13 layers of 321 wells are quick and accurately identified.
出处
《西安石油大学学报（自然科学版）》
CAS
2004年第6期10-14,22,共6页
Journal of Xi’an Shiyou University（Natural Science Edition）
基金
国家重点基础研究 (973)项目 (2 0 0 2CB4 12 70 2 )资助
