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针对利用重磁资料增强地质体边界在图像中的视觉效果和提高地质解译的准确性问题,提出应用改进的小子域滤波方法对重力异常及重力梯度张量数据进行增强处理。根据滑动窗口子域平均选择原理,探讨了改进的小子域滤波方法在位场异常数据含有高斯白噪声时,不同窗口大小对地质体边界的识别效果及其在具有不同边界延伸方向地质体中的应用效果。模型试验结果表明,利用改进的小子域滤波对重力梯度张量数据进行增强处理,得到的地质体边界形态失真更小,且受滤波窗口大小、噪声以及地质体边界方向的影响较小;对深部场源体,通过增大滤波窗口的方式,可以较好地反映深部场源体的边界。结合黑龙江省虎林盆地重力异常以及计算的重力梯度张量的处理实例表明改进的小子域滤波法较传统的小子域滤波法增强了对断裂水平位置信息的识别。
In order to improve the visual effect of geologic body boundary in the image and to improve the accuracy of geological interpretation by using the data of gravity and magnetism, an improved small subdomain filter method is proposed to enhance the gravity anomaly and gravity gradient tensor data. According to the principle of average selection of sub-domains in sliding window, the effect of different window sizes on the identification of geological body boundary and its influence on geologic bodies with different boundary extension directions are discussed in the case of abnormal field data containing Gaussian white noise Application effect. The results of model tests show that the enhancement of gravity gradient tensor data using the improved small subdomain filter results in less morphological boundary morphological distortion and is less affected by the size of the filtering window, noise and the direction of the boundary of the geological body. Field source body, by increasing the filter window, can better reflect the deep field source body boundaries. Combined with the gravity anomalies in the Hulin basin in Heilongjiang province and the calculation examples of the gravity gradient tensor, it is shown that the improved small subdomain filter method enhances the recognition of fault horizontal position information compared with the traditional small subdomain filter method.