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.