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按照油气微渗漏理论，利用ＴＭ数据同已知油气田进行相关分析，优选波段变量组合，进行图像处理，可以获得和建立反映油气水分布主趋势的色调异常影像模式。这些色调异常的形成，除了与油气圈闭相伴的油田水类型及总矿化度有关外，同时还受地貌和地表、地下水排泄条件、第四条沉积、植被等因素影响和干扰。在相同含油气条件下的不同地物具有相同的色调显示，在不同含油气条件下的相同地物却具有不同色调特征，因此，遥感图像上的色调异常必然具有一定的多解性。为了减少单一色调异常的多解性，必须同时利用遥感图像中的线性体和环形构造信息，建立油气圈闭的线性体－环形构造－色调异常影像模式进行油气预测。
According to the microleakage theory of oil and gas, the correlation analysis between TM data and known oil and gas fields, and the combination of band variables, and the image processing are feasible, and the abnormal color tone patterns reflecting the main trend of oil-gas water distribution can be obtained and established. In addition to the type and total salinity of oil and gas associated with oil and gas trap, the formation of these anomalous hues is also affected and disturbed by such factors as landform and groundwater discharge conditions, the fourth sediment and vegetation. In the same oil and gas conditions of different features have the same color display, the same in different oil and gas conditions have different color tone characteristics, therefore, the remote sensing image of the hue must have a certain degree of multi-solution. In order to reduce the multiplicity of monochromatic anomalies, it is necessary to use the linear body and ring structure information in the remote sensing images simultaneously to establish a hydrocarbon-gas cyclic linear body-ring structure-anomalous tone image model for hydrocarbon prediction.