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Neural network based well log synthesis with reduced usage of radioisotopic sources

机译:基于神经网络的测井曲线合成,减少了放射性同位素源的使用

摘要

Logging systems and methods are disclosed to reduce usage of radioisotopic sources. Some embodiments comprise collecting at least one output log of a training well bore from measurements with a radioisotopic source; collecting at least one input log of the training well bore from measurements by a non-radioisotopic logging tool; training a neural network to predict the output log from the at least one input log; collecting at least one input log of a development well bore from measurements by the non-radioisotopic logging tool; and processing the at least one input log of the development well bore to synthesize at least one output log of the development well bore. The output logs may include formation density and neutron porosity logs.
机译:公开了测井系统和方法以减少放射性同位素源的使用。一些实施例包括从具有放射性同位素源的测量中收集训练井眼的至少一个输出测井;通过非放射性同位素测井工具的测量收集至少一个训练井眼的输入测井;训练神经网络以从至少一个输入日志中预测输出日志;通过非放射性同位素测井工具的测量收集至少一个开发井眼的输入测井;处理显影井筒的至少一个输入测井曲线,以合成显影井筒的至少一个输出测井曲线。输出测井曲线可以包括地层密度和中子孔隙率测井曲线。

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