PREDICTION OF SAND BODIES IN DEEP-WATER CHANNEL TURBIDITE RESERVOIR WITH SEISMIC ATTRIBUTES

Deep-water channel sand bodies are good reservoir for oil and gas accumulation. However, the prediction of such a reservoir is difficult since usually no sufficient wells are available offshore. Following the geological characteristics of deep-water channels, this paper constructed some models for different types of channels and proposed some sand body superposition patterns at the well point using forward model analysis, the seismic response characteristics and sensitive seismic attributes as tools. Cluster analysis and probabilistic neural network (PNN) prediction are carried out based on sensitive seismic attributes. The X reservoir in West Africa is selected as a case for application, and the coincidence rate of the prediction results reached as high as 87.5%, which is efficient enough to predict the sand body distribution pattern for oil and gas exploration. Combined with the integrated study of seismic sedimentology, it is concluded that the sand bodies in the target layer are mainly distributed in the middle of the channel but few in both ends under the control of the sedimentary environment and the change in flow regime in the curved part of channel.