An Open-Source ERT Data Inversion Tool for the Assessment of Sinkhole Hazards Related to Shallow Underground Workings

Abstract

Post-mining areas affected by historical shallow mining are often exposed to sinkhole hazards associated with abandoned underground workings. Reliable identification of such structures is essential for geotechnical assessment and land redevelopment. Among the available non-invasive investigation techniques, electrical resistivity tomography (ERT) is widely used for detecting shallow subsurface voids. However, interpretation of ERT measurements requires inversion processing performed using specialized software, which is frequently commercial and associated with considerable licensing costs.

This paper presents a standalone software application developed for the processing and inversion of ERT data. The software is based on the open-source pyGIMLi framework and enables ERT data analysis without requiring a dedicated Python environment or programming knowledge. The implemented workflow includes data import, quality assessment, outlier detection, inversion, and visualization of resistivity models.

The applicability of the software is demonstrated using a case study from the Upper Silesian Coal Basin (Poland), where ERT surveys were conducted to investigate shallow underground workings associated with sinkhole hazards. The obtained inversion results enabled the identification of resistivity anomalies corresponding to known underground structures. A comparison with results generated using the commercial RES2DINV package demonstrated a high degree of agreement, confirming the practical reliability of the proposed solution. The presented approach offers a cost-effective alternative for geophysical investigations conducted in mining and post-mining areas and may be useful for engineers and researchers involved in geohazard assessment and land reclamation.