Integrated Magnetic and Electrical Geophysical Methods for Detecting Concealed Porphyry Copper Deposits in Sedimentary Basins: A Case Study From the Western Liupanshan Basin, Northwest China

ABSTRACT Exploration for concealed porphyry copper (Cu) deposits in sedimentary basins is challenging. Integrated geophysical exploration methods, combining electrical and magnetic techniques, have proven to be highly effective in the search for concealed metal deposits. This study focuses on the Yueliangshan area within the western Liupanshan Basin, utilising high‐precision (1: 10,000) ground magnetic surveys and induced polarisation sounding for Cu exploration. The goal is to interpret geophysical anomalies to delineate Cu mineralization zones, providing a reliable theoretical basis for subsequent engineering drilling. High‐precision ground magnetic surveys indicate that magnetic anomalies are primarily caused by Proterozoic to Palaeozoic metamorphosed volcanic‐sedimentary rock series and magmatic intrusions. These magnetic sources are distributed along a northwest‐southeast regional structural uplift zone, with the upper interface buried approximately 400 m deep. The magnetic bodies trend southwest and are steeply inclined. The induced polarisation sounding results reveal that sulphide mineralized alteration zones at the margins of concealed granodiorite bodies are responsible for the high polarizability characteristics observed in exploration sections 2 and 8. Compared to geophysical parameters from ground magnetic surveys, high polarizability obtained from induced polarisation measurements are the most effective indicators for identifying porphyry bodies that have undergone mineralized alteration. It is proposed that engineering drilling at the sites of maximum anomalies caused by mineralized alteration offers a high feasibility for discovering Cu deposits. Finally, this study summarises the comprehensive exploration indicators for concealed porphyry Cu deposits in sedimentary basins and proposes a generalised exploration model.