METHOD FOR PREDICTING SUBSURFACE FEATURES FROM SEISMIC USING DEEP LEARNING DIMENSIONALITY REDUCTION FOR REGRESSION
Abstract:
A method for training a backpropagation-enabled regression process is used for predicting values of an attribute of subsurface data. A multi-dimensional seismic data set with an input dimension of at least two is inputted into a backpropagation-enabled process. A predicted value of the attribute has a prediction dimension of at least 1 and is at least 1 dimension less than the input dimension.
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