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本文采用灰色关联度、模糊聚类及人工神经网络方法，预测了塔北雅克拉地区圈闭的含油气性，预测所用多数有氧化还原电位、放射性能谱、地震、高精度重磁、频谱激电等。为了把灰色关联度方法用于面积性资料处理，将灰色曲线关联度推广为灰色曲面关联度。在分析对比上述三种预测方法的应用前提、条件及效果的基础上可以看出，综合运用多种方法、多参数可以减少预测结果的多解性。本文中综合预测的地质效果明显，其中大涝坝远景区已见工业油气流，托库远景区有待验证。
In this paper, we use the methods of gray relational degree, fuzzy clustering and artificial neural network to predict the oil and gas trap of trapping in the Yakula area of Tarim, and predict the most redox potential, radioactivity spectrum, earthquake, high precision gravity and magnetic resonance Electricity and so on. In order to use the gray relational degree method for the area data processing, the degree of gray curve association is extended to the gray surface degree of correlation. On the basis of analyzing and comparing the application preconditions, conditions and effects of the above three prediction methods, it can be seen that using a plurality of methods synthetically, the multiple parameters can reduce the multiplicity of the prediction results. In this paper, the comprehensive prediction of geological effects is obvious, in which the Dalaoba dam has seen industrial oil and gas streams, tortoises prospects to be verified.