MACHINE LEARNING BASED PORE BODY TO PORE THROAT SIZE TRANSFORMATION FOR COMPLEX RESERVOIRS

Abstract: a computer-implemented method is provided. the computer-implemented method can include receiving one or more input nmr measurements at a first neural network; transforming the one or more input nmr measurements to a predicted pore throat size distribution or one or more predicted pore throat size parameters; receiving the predicted pore throat size distribution or the one or more predicted pore throat size parameters at a second neural network; transforming the predicted pore throat size distribution or the one or more predicted pore throat size parameters to a predicted nmr tdistribution or one or more predicted nmr tparameters; and applying one or more physics based equations to the predicted nmr tdistribution or the one or more predicted nmr tparameters to forward model the predicted nmr tdistribution or the one or more predicted nmr tparameters to one or more simulated nmr measurements.

Inventor(s): Wei Shao, Songhua Chen, Shouxiang Mark Ma, Gabor Hursan, Abdullah A Alakeely

CPC Classification: G01V3/38 (GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS (means for indicating the location of accidentally buried, e.g. snow-buried, persons ))

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