Study on Oil-gas Reservoir Rule Extraction and Automatic Identification Based on Rough Set

摘要

A rough set based method for oil-gas reservoir rule extraction and automatic identification through petroleum logging data is provided in this paper. Based on the traditional way of rough set data mining, this method makes adjustments to the mining procedure and optimizes the reduction, discretization, and rule generation steps respectively via Sweep Forward Neighborhood Fast Algorithm, Fuzzy Clustering FCM Algorithm, and CAAI Decision Tree Algorithm, allowing itself more applicable to the issue of oil-gas reservoir rule extraction through petroleum logging data. Afterwards, the automatic identification of oil-gas reservoir is enabled by a case-based reasoning method. This paper analyzes the applicability of rough set method and case reasoning to petroleum logging data, and verifies algorithms' feasibility through an actual set of petroleum logging data.