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

Abstract

We have developed a comprehensive methodology for the acquisition and processing of self-potential (SP) data, as well as some keys for the interpretation of the results. The wide applicability of the SP method and its low cost make it a popular method to 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 have identified great interest from the scientific community for such a journal paper as a guide for existing and new practitioners with their SP survey design, data acquisition, robust processing, and initial interpretation steps. We have developed a step-by-step methodology for SP data acquisition and processing, combined with practical guidance for the interpretation of collected and processed SP data, including an evaluation of common errors and typical sources of uncertainty. Our 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. We evaluated 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 data set. The benefits of interpolating SP data in two steps are examined. Combining map visualization, SP versus distance, and SP versus elevation graphs appears to be a highly effective strategy to interpret the signal in terms of hydrogeologic and hydrothermal domains and to highlight structural limits in volcanic contexts as well as in other environments.