Prediction of Reservoir Compressibility Using Subsurface Cores, Well Logs, and Seismic Data by Neural Network
Jafar VALI,
Farnusch HajiZadeh
Abstract:In this study, three-dimensional pore volume compressibility of a carbonate reservoir was predicted. The primary data of the model were petrophysical parameters, measured compressibility factor on core samples, conventional well logs, and three-dimensional seismic attributes. Neural network algorithms were employed to propagate the compressibility data along the well axis and to predict the distribution of compressibility within three-dimensional seismic acquisition area. A probabilistic neural network algorit… Show more
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