Model experiments show that it is possible for us to identify lithology and hydrocarbon conditions in abnormal area in terms of wave field characters and images in different media.
模型试验表明，根据波在不同介质中的传播规律，使我们有可能利用波场图像来区分异常区的岩性和含油气特性。
According to BP neural network theory, dual neural network model for lithology identification was established.
根据BP神经网络原理，建立了岩性识别双重神经网络模型。
Based on seismic lines, hydrocarbon source rock, lithology, thermal stream and test data, a two dimensional forward model of the basin has been made.
以地震主测线为格架，结合烃源岩、岩性、热流、测试分析资料为依据，采用正演法开展二维盆地模拟工作。
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