Owing to complex Neogene channel sands stacking and abrupt change of sedimentary facies in the river-lake transition zone in Bohai,microfacies classification using seismic attributes may be quite uncertain.We propose an improved amplitude-spec-trum-distance K-center clustering method to mitigate the uncertainties.Microfacies calibrated using log data are set as the initial clustering center and constraints of clustering,and amplitude-spectrum distance is used to measure the differences among seismic wave forms for microfacies prediction.In view of the geologic conditions in Field A,Bohai Bay,a 3D geologic model is built with su-perposed channel sands.The model test shows a prediction accuracy of 95％,15％higher than that of the K-mean clustering in the time domain.Six channel styles,i.e.mudstones,single-phase channel edge,single-phase channel body,superposed channel edges,su-perposed channel edge and body,and superposed channel bodies(or multi-phase superposed channels),could be identified,based on which Neogene channels are classified into 10 microfacies.A large reservoir,S,is classified into 6 microfacies:distributary chan-nel,mouth bar,sand sheet,crevasse channel,inter-distributary bay,and natural levee,among which distributary channel and mouth bar are the promising microfacies for production.The case study demonstrates the feasibility of the improved classification method.
waveform classificationamplitude-spectrum distancesuperposed channelssedimentary microfaciesriver-lake transi-tion zoneNeogene in Bohai Sea
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