Identifying oil-gas layer by minimum distance clustering

This paper introduces the basic principles and steps of identifying oil-gas layers and water layers by minimum distance clustering, and establishes distinguishable model to identify the properties of reservoir fluids by logging curves and reservoir parameters of oil-gas layers, oil-water layers, water layers and dry layers. Interpretation is done to the carboniferous' practical logging data of Tahe in Xinjiang by minimum distance clustering, and the identification results are basically consistent with the actual results. The oil-gas layers are not missed, and good interpretation results are obtained.