ABSTRACT An interesting geological objective of quantitative interpretation of magnetic data is to find inverse models which can determine sharp geological interfaces below the surface. The stabilizing function in the Tikhonov parametric functional governs sparseness constraint in the recovered model. This paper introduces a novel stabilizer based on a sigmoid function which can provide non‐smooth models in the inversion of magnetic data efficiently. An inversion algorithm is developed based on the reweighted regularized conjugate gradient to get the solution of the inverse problem using this stabilizing function. The performance of the proposed algorithm is checked on two synthetic data sets and real aeromagnetic data from McFaulds Lake in Ontario, Canada, in comparison with the results of the minimum support stabilizing function. The inverse problem converges to the solution faster when the sigmoid stabilizing function is used instead of the minimum support stabilizing function.

中文翻译：

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用于快速稀疏 3D 磁数据反演的 sigmoid 稳定函数

摘要 磁性数据定量解释的一个有趣的地质目标是找到可以确定地表以下尖锐地质界面的反演模型。Tikhonov 参数函数中的稳定函数控制恢复模型中的稀疏约束。本文介绍了一种基于 sigmoid 函数的新型稳定器，它可以有效地在磁数据反演中提供非平滑模型。基于重新加权的正则化共轭梯度开发了一种反演算法，以使用该稳定函数获得反演问题的解。与最小支撑稳定函数的结果相比，该算法的性能在两个合成数据集和来自加拿大安大略省 McFaulds 湖的真实航磁数据上进行了检查。