BP神经网络识别塔北低阻油气层

THE APPLICATION OF BP NEURAL NETWORK TO RECOGNITION OF THE TABEI LOW RESISTIVITY OIL AND GAS LAYERS

简要介绍了塔北低阻油气层岩性剖面、低阻油气层地球物理测井曲线特征 ,分析了塔北地区低阻油气储层成因 ,重点论述BP人工神经网络识别油气层、油水同层、水层和干层的方法原理。识别实例表明 ,BP人工神经网络识别低阻油 (气 )、水层的结果与实际相符 。

This paper describes in brief the lithologic profiles and the geophysical logging curves of the low resistivity oil and gas layers in Tabei area, analyzes the origin of the low resistivity oil and gas reservoirs in that area, and deals emphatically with the principle of applying the neural network to recognizing oil and gas layers, oil-water layers, water layers and dry layers. The recognition of low resistivity oil (gas) layers and water layers is consistent with the real conditions, thus obviously improving the interpretation precision of logging data.