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OwnerRonald R. Bushinventor
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A neural network based system, method, and process for the automated delineation of spatially dependent objects is disclosed. The method is applicable to objects such as hydrocarbon accumulations, aeromagnetic profiles, astronomical clusters, weather clusters, objects from radar, sonar, seismic and infrared returns, etc. One of the novelties in the present invention is that the method can be utilized whether or not known data is available to provide traditional training sets. The output consists of a classification of the input data into clearly delineated accumulations, clusters, objects, etc. that have various types and properties. A preferred but non-exclusive application of the present invention is the automated delineation of hydrocarbon accumulations and sub-regions within the accumulations with various properties, in an oil and gas field, prior to the commencement of drilling operations.
A method for the automated delineation of hydrocarbon accumulations from seismic data gathered in an oil and/or gas field comprising the steps of:
A method of delineating hydrocarbon accumulations from seismic data gathered in an area comprising the steps of:
A method of delineating mineral accumulations from data relating to a given area comprising the steps of:
A method of delineating spatially dependent characteristics in a given area from data relating to the given area comprising the steps of:
A method of determining the accuracy of predictions made on a given set of data using neural networks comprising the steps of:
A method of producing hydrocarbon products from an oil and/or gas field comprising the steps of:
Dependencies are inferred from the claim text.