Geophysical inversion under different stabilizers has different descriptions of the target body boundary, especially in complex geological structures. In this paper, we present an extremum boundary inversion algorithm based on different stabilizers for electrical interface recognition. Firstly, we use the smoothest and minimum-support stabilizing functional to study the applicability of adaptive regularization inversion algorithm. Then, an electrical interface recognition method based on different stabilizers is developed by introducing extremum boundary inversion algorithm. The testing shows that the adaptive regularization inversion method does work for different stabilizers and has a low dependence on the initial models. The ratio of the smooth and focusing upper and lower boundaries obtained using the extremum boundary inversion algorithm can clearly demarcate electrical interfaces. We apply the inversion algorithm to the magnetotelluric (MT) data collected from a preselected area of a high-level-waste clay-rock repository site in the Tamusu area. We recognized regional structures with smooth inversion and the local details with focusing inversion and determined the thickness of the target layer combined with the geological and drilling information, which meets the requirement for the site of the high-level waste clay-rock repository.

中文翻译：

---

基于不同稳定剂的大地电磁极值边界反演及其在高放射性废物处置库选址中的应用

不同稳定剂作用下的地球物理反演对目标体边界的描述不同，尤其是在复杂的地质构造中。在本文中，我们提出了一种基于不同稳定器的极值边界反演算法，用于电接口识别。首先，我们使用最平滑和最小支持稳定函数研究自适应正则化反演算法的适用性。然后，通过引入极值边界反演算法，开发了一种基于不同稳定器的电接口识别方法。测试表明，自适应正则化反演方法适用于不同的稳定器，并且对初始模型的依赖性较低。使用极值边界反演算法获得的平滑边界和聚焦边界的上下边界的比率可以清楚地划分电接口。我们将反演算法应用于从Tamusu地区的高级废物粘土岩储存库站点的预选区域收集的大地电磁（MT）数据。我们识别出具有平滑反演的区域结构，并通过集中反演识别了局部细节，并结合地质和钻探信息确定了目标层的厚度，从而满足了对高级废弃黏土岩库的选址要求。