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.