Porosity and Porevolume Prediction in a Gas Storage Reservoir

F-12 POROSITY AND POREVOLUME PREDICTION IN A GAS STORAGE RESERVOIR Introduction The aim of any reservoir characterization study is to describe the properties of the reservoir in the appropriate detail. The result is a prediction model of the physical and geological properties of the subsurface. To reach this goal we must integrate spatially distributed seismic data measured in two way time and local informations from wells measured in units of depth. To handle these data of different character and scale a neural network training approach was selected to provide various attribute maps without well (unsupervised) and with well control (supervised)