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A Practical approach for self-potential data acquisition, processing, and visualization

Abstract : We propose a comprehensive methodology for the acquisition and processing of self-potential (SP) data, as well as some keys to the interpretation of the results. The wide applicability of the SP method, and its low cost, make it a popular method for use in a variety of natural environments. Despite its versatility and the fact that various published journal papers describe the method and its applications, we believe that there is an important need for a dedicated, peer-reviewed SP acquisition, processing and visualization/interpretation paper in the scientific literature. We identified a great interest from the scientific community for such a journal paper as a guide for both existing and new practitioners with their SP survey design, data acquisition, robust processing, and initial interpretation steps. A step-by-step methodology is proposed here for SP data acquisition and processing, combined with practical guidance for the interpretation of collected and processed SP data, including a discussion of common errors and typical sources of uncertainty. The presented examples are based on studies in volcanic environments (e.g. hydrothermal systems), however the processing steps and methodology are fully applicable and transferable across disciplines to SP data acquired in any environment, and for a wide variety of applications. After a short overview of the field acquisition method and the low-cost equipment, the reference and closure corrections, their meaning for the SP signal, and their effect on the dataset are detailed and exemplified. The benefits of interpolating SP data in two steps is discussed. Combining map visualization, SP vs distance, and SP vs elevation graphs appears as a highly effective strategy to interpret the signal in terms of hydrogeological and hydrothermal domains, and to highlight structural limits in volcanic contexts as well as in other environments.
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Submitted on : Thursday, June 17, 2021 - 1:21:47 PM
Last modification on : Friday, October 21, 2022 - 3:30:04 PM
Long-term archiving on: : Saturday, September 18, 2021 - 6:31:34 PM


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Stéphanie Barde-Cabusson, Anthony Finizola, Niels Grobbe. A Practical approach for self-potential data acquisition, processing, and visualization. Interpretation, 2021, 9, pp.T123-T143. ⟨10.1190/int-2020-0012.1⟩. ⟨hal-03003692⟩



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