基于FCM模型约束的二维直流电阻率正则化反演

Two-dimensional DC resistivity regularization inversion based on FCM model constraint

本文开展了二维直流电阻率模糊C均值聚类(FCM)约束反演研究.在经典最小结构模型正则化的基础上,将L_(1)范数与L2范数模型约束反演进行了对比,可以看出L_(1)范数反演结果相较L2范数边界更清晰、物性呈块状分布更明显.在此基础上,联合使用FCM模型约束,将精确岩石物性测量值作为参考聚类中心,引导反演物性向聚类中心发展,FCM聚类约束的应用可进一步提高反演的效果.合成数据与实测数据反演的结果表明,基于精确岩石物性引导的FCM模型约束与L_(1)范数最小结构模型联合,可以实现高精度的直流电阻率反演.

This article presents a study on Fuzzy C-Means(FCM)constrained inversion of 2D DC resistivity.Based on the minimum structure model constraint regularized inversion,we compared the L_(1)-norm with L2-norm model constraints.It is observed that the L_(1)-norm inversion yields clearer boundaries and more pronounced block-like distribution of physical properties compared to the L2-norm inversion.Furthermore,by incorporating FCM model constraints,accurate rock property measurements are utilized as reference cluster centers to guide the inversion towards those centers.The application of FCM clustering constraints further enhances the inversion results.Both synthetic and field data inversions demonstrate that the combination of FCM model constraints guided by accurate rock property measurements and L_(1)-norm minimum structure model enables high-precision DC resistivity inversion.