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Generating pore types and synthetic capillary pressure curves from wireline logs using neural networks
Generating pore types and synthetic capillary pressure curves from wireline logs using neural networks
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机译:使用神经网络从电缆测井曲线生成孔隙类型和合成毛细管压力曲线
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摘要
Methods of directly analyzing wireline well logging data to derive pore types, pore volumes and capillary pressure curves from the wireline logs are disclosed. A trained and validated neural network is applied to wireline log data on porosity, bulk density and shallow, medium and deep conductivity to derive synthetic pore type proportions as a function of depth. These synthetic data are then applied through a derived and validated capillary pressure curve data model to derive pore volume and pressure data as a function of borehole depth.
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