砂泥岩地层概率神经网络岩性反演技术应用研究  

Application of probabilistic neural network in the lithology inversion of sandstone-mudstone strata

作　　者：张绍红[1] 林昌荣[2] 

机构地区：[1]西安石油大学油气资源学院,陕西西安710065 [2]中国石油大学(北京)资源与信息学院,北京102249

出　　处：《西安石油大学学报（自然科学版）》2008年第4期1-4,共4页Journal of Xi’an Shiyou University（Natural Science Edition）

基　　金：国家"973"项目(编号:2007CB209600);西安石油大学科技研究基金项目(编号:2006-80)

摘　　要：概率神经网络是一种基于概率密度函数理论的神经网络,能够广泛地应用于模式识别等领域.针对地震岩性反演预测问题,提出了一种具体的概率神经网络方法,包括网络模型的构造和预测识别步骤等.研究区主要目的层为沙溪庙组沙一段湖滩砂及河道砂体,储层单层厚度小,岩性横向变化较大,利用地震资料进行常规储层预测较困难.为此,根据该区储层的测井响应特征、地震属性特征与地质岩性特征的相关性,利用概率神经网络方法对地震属性数据做变换,从而对地层特征进行预测识别.Probabilistic neural network is based on the theory of probabilistic density function,and it is widely used in many realms,such as patter recognition,etc.A specific method of probabilistic neural network is presented for the lithology inversion of seismic data,in which the construction of the network model and the steps of prediction are included.The target strata in the studied area are the beach sandstone and channel sandstone of Shayi member of Shaximiao formation,and because their reservoir thickness is little and the lateral change of their lithology is great,it is difficult to predict the reservoir lithology based on seismic data by conventional methods.For this reason,According to the correlation among logging responses,seismic attributes and geological lithology characteristics,the probabilistic neural network method is used for transforming the seismic attributes to identify the reservoir lithology information.And a case shows that the technique has a good application result.

关 键 词：岩性识别 概率神经网络 地震属性数据 反演 

分 类 号：TE121.3[石油与天然气工程—油气勘探] P618.130.21[天文地球—矿床学]