改进的均衡滤波器在位场数据边界识别中的应用

边界识别是进行位场数据解释时一项必不可少的任务.现有的边界识别滤波器存在识别边界发散和深部地质体边界模糊的缺点.本文提出增强型均衡滤波器,可有效地改善上述缺点.该滤波器是利用不同阶导数之间的组合来进行地质体边界的识别,并在运算中引入一种计算高阶垂直导数的稳定算法.通过理论模型试验证明增强型均衡滤波器能使浅部与深部地质体的边界同时清晰地显示,且相对于其它边界识别滤波器能更加准确和清晰地识别出地质体的边界.最后将增强型均衡滤波器应用于实测位场数据的解释,根据其识别结果可容易地划分出断裂的水平位置及不同地层之间的界线,并能发现更多的细节信息.

Application of improved balancing filters to edge identification of potential field data

Edge identification is an indispensable task in the interpretation of potential field data. The existing methods have the disadvantages that the recognized edges are diffuse and the edges of the deeper sources are blurred. We presented enhanced balancing filters that can effectively overcome the disadvantages existing in the previous filters. The improved filters use the various combinations of different order derivatives to recognize the source edges, and we introduced a stable algorithm of the high-order vertical derivatives. The enhanced balancing filters are demonstrated on synthetic potential field data, which can display the edges of the shallow and deep bodies simultaneously, and can display the edges of the sources more precisely and clearly compared to the other filters. At last, we applied the enhanced balancing filters to measured potential field data, which can divide the horizontal locations of the faults and the boundaries of different strata easily based on the results, and can discover more subtle details.