A comprehensive Python tool for predicting mining-induced subsidence

Accurate prediction of surface deformations from longwall mining is vital for effective subsidence management and infrastructure protection. This paper introduces the Python-based Subsidence Prediction for Underground Mining (PySPUM) framework, developed from the Surface Deformation Prediction System (SDPS). The SDPS uses the Influence Function Method, allowing for consideration of different mining geometries, multi-seam mining operations, and calculation of horizontal strains and related deformations. Validation was conducted using survey data from a Australian longwall operation in Bown Basin. Results indicated that a 30% average hard rock content is suitable for Bowen Basin operations, with potential applications to other mining projects. The PySPUM framework was also employed in a separate project to evaluate subsidence impacts near a Run-of-Mine (ROM) dam, enhancing management and mitigation strategies for large-scale longwall mining operations.