应用人工智能搜索技术进行三维大地电磁测深反演的探索

3-D magnetotelluric sounding data inversion by artificial intelligence searching technique

江汉石油学院计算机科学系电磁室,荆州 434102

Department of Computer Science, Jianghan Petroleum Institute, Jingzhou 434102

基于人工智能中状态空间的启发式搜索技术, 提出了一种全新的大地电磁测深三维反演新思路。其基本思想是把模型空间量化成有限模型集, 而后按一定的搜索策略选择一个最有希望的模型进行正演计算, 再把正演结果与观测数据比较并计算目标函数, 如果目标函数小于给定值, 则此时的模型即为反演结果, 否则继续搜索、正演、比较, 不断重复此过程, 直到找到一个满意的解估计。作为一种通用的反演新思路, 不但适用于大地电磁测深, 还可以把该反演技术应用到其它各种地球物理反演问题中。

We give in this paper a new train of thought for 3-D magnetotelluric (MT) sounding data inversion. Its basic idea is that the model space is quantified into finite model sets, then select a most prospective model according to a certain searching tactics to perform forward computation, compare the forward results with the observed data and compute the objective function; if the function value is less than a given value, then the model is the inversion result, and if not, continue searching, forward com-putation and comparing repeatedly until a satisfactory solution estimate is found. As a new common in-version idea, it is not only suitable to MT sounding data inversion, but also can be appliable to other geo-physical inversion problems.