WELL LOGGING FACIES IDETIFICATION USING SELF-ORGANIZATION NEURAL NETWORK
WEI Lian , XIAO Ci-xun (Chengdu University of Technology, Chengdu 610059, China)
The paper introduces a method to identify well logging facies using self organization neural network, which is a non-supervisor learning algorithm. It extracts information from input data adaptively and now is largely used in various kinds of pattern identifications. In the method, we first extract the depositional environment information parameters from well logging data. Then depositional facies patterns are identified using the self organization neural network. As the method to identify depositional facies is based on depositional genetic factors, it can remove some uncertain factors from well data and is more representative.