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TRAINING MACHINE LEARNING SYSTEMS FOR SEISMIC INTERPRETATION

机译:培训机器学习系统,用于地震解释

摘要

A method and apparatus for seismic interpretation including machine learning (ML). A method of training a ML system for seismic interpretation includes: preparing a collection of seismic images as training data; training an interpreter ML model to learn to interpret the training data, wherein: the interpreter ML model comprises a geologic objective function, and the learning is regularized by one or more geologic priors; and training a discriminator ML model to learn the one or more geologic priors from the training data. A method of hydrocarbon management includes: training the ML system for seismic interpretation; obtaining test data comprising a second collection of seismic images; applying the trained ML system to the test data to generate output; and managing hydrocarbons based on the output. A method includes performing an inference on test data with the interpreter and discriminator ML models to generate a feature probability map representative of subsurface features.
机译:一种用于地震解释的方法和装置,包括机器学习(ML)。 培训用于地震解释的ML系统的方法包括:准备地震图像的集合作为训练数据; 训练解释器ML模型以学习解释训练数据,其中:解释器ML模型包括地质目标函数,并且该学习由一个或多个地质前沿进行规范; 并训练鉴别者ML模型,以从训练数据中学习一个或多个地质前沿。 一种碳氢化合物管理的方法包括:培训ML系统进行地震解释; 获取包括第二个地震图像集合的测试数据; 将训练的ML系统应用于测试数据以生成输出; 并基于输出管理碳氢化合物。 一种方法包括用解释器和鉴别器ML模型对测试数据执行推断,以生成代表地下特征的特征概率图。

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