Co-operative inversion of geoelectrical data sets acquired from different electrode arrays

D. T. Kieu, T. Truong
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引用次数: 1

Abstract

Summary Direct current resistivity (DCR) method is one of the most commonly applied geophysical exploration methods. The development of data acquisition techniques enables the acquisition of multiple data sets of various electrode arrays with a little extra measurement time in comparison with the time that needs to install the system. Accordingly, the data processor is required to utilise as much as possible useful information to build a more reliable geoelectrical model. This study aims to test using the co-operative inversion process to the multiple data sets of various electrode configurations. We use a synthetic model with the most common electrode arrays: Wenner-Schlumberger (WS), Dipole-Dipole (DD), Pole-Dipole (PD) and Pole-Pole to investigate the possibility of the co-operative inversion schemes. The results show that the co-operative inversion of the combined data sets is better than the inversion of the individual ones. The order of inversion for each data set can produce different results. Fuzzy c-means constraint may assist the inversion to produce better results.
不同电极阵列地电数据集的协同反演
直流电阻率法是目前应用最广泛的物探方法之一。与安装系统所需的时间相比,数据采集技术的发展使采集各种电极阵列的多个数据集具有一点额外的测量时间。因此,数据处理器需要利用尽可能多的有用信息来建立更可靠的地电模型。本研究旨在对不同电极配置的多个数据集进行协同反演过程的测试。我们使用最常见的电极阵列:温纳-斯伦贝谢(WS)、偶极-偶极(DD)、极-偶极(PD)和极-极(Pole-Pole)的合成模型来研究协同反演方案的可能性。结果表明,组合数据集的协同反演效果优于单个数据集的反演效果。每个数据集的反演顺序可以产生不同的结果。模糊c均值约束可以帮助反演得到更好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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