应用神经网络技术预测碳酸盐岩储层孔隙度  

Forecasting the Porosity of Carbonate Reservoir by Neural Net Technique,

作　　者：肖慈珣[1] 罗继红[1] 肖梅[1] 蔡永香[1] 

机构地区：[1]成都理工学院,四川省成都市十里店610059

出　　处：《天然气工业》1993年第6期31-34,35,共5页Natural Gas Industry

摘　　要：本文引入神经网络技术,用以研究碳酸盐岩测井信息与岩心分析孔隙度的关系,并由此预测储层孔隙度。通过在贵州赤水地区取心井的实际应用,在数据的统计规律较差的情况下,获得了令人满意的结果。The relation between carbonate rock logging information and core analysis porosity is studied by neural net technique to forecast reservoir porosity in this paper. Through practising at the well coring in Chishui area, Guizhou, the satisfactory result is obtained in the condition of wanting statistics regula- tion.

关 键 词：神经网络 测井 碳酸盐岩 储集层 

分 类 号：P618.13[天文地球—矿床学]