For the thin-layer sand bodies of the delta plain-front in the Weixi Area,the reservoir prediction is carried out using a logging coupled frequency division inversion method.In this method,the BP neural network intelligent algorithm is used to establish the nonlinear mapping relationship between amplitude and frequency(AVF)of logging and seismic data research.The low,medium,and high-frequency information of effective frequency band of natural gamma logging and seismic data sensitive to logging lithology in the study area is also excavated,and the high-resolution reservoir inversion results including full frequency band information are obtained.In the inversion profile,the development characteristics of sand body are clear,the horizontal distribution of thin mudstone interlayers is distinct,and the lateral thickness of channel sand body changes obviously.The error between the predicted thickness of sand body and the logging interpretation thickness is controlled about 1%.Compared with the traditional inversion methods,the logging coupled frequency division inversion method effectively improves the accuracy of thickness calculations of thin sand body.
frequency division inversionnatural gamma loggingBP neural networkreservoir prediction
NETL
NSTL
万方数据
