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INFERRING PETROPHYSICAL PROPERTIES OF HYDROCARBON RESERVOIRS USING A NEURAL NETWORK
INFERRING PETROPHYSICAL PROPERTIES OF HYDROCARBON RESERVOIRS USING A NEURAL NETWORK
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机译：利用神经网络推断油气储层的物性
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摘要
Received image data is enhanced to create enhanced image data using image processing to remove artifacts and to retrieve information associated with a desired target output. Image segmentation is performed on useable enhanced image data to created segmented image data by partitioning the enhanced image data into coherent regions with respect to a particular image-based criterion. Useable segmented image data and auxiliary data is pre-processing for input into a neural network as pre-processed data. The pre-processed data is divided into training, validation, and testing data subsets. A neural network architecture is determined to process the pre-processed data and the determined neural network architecture is executed using the pre-processed data. Output of the determined neural network is post-processed as post-processed data. The post-processed data is compared to a known value range associated with the post-processed data to determine if the post-processed data satisfies a desired output result.
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