This research employs a combined geophysical approach, utilizing electrical resistivity tomography (ERT) and induced polarization (IP) imaging, to characterize the subsurface architecture and identify copper-bearing zones at the Takhte-Gonbad porphyry copper deposit within the Kerman metallogenic belt, Iran. The acquired field data were inverted using two distinct methodologies: conventional Tikhonov regularization and sparsity-based regularization. The resulting inverse models successfully delineated two principal E-W trending mineralized zones, which are distinguished by coherent low-resistivity and high-chargeability anomalies diagnostic of disseminated sulfide mineralization. These geophysical signatures exhibit a strong spatial correlation with surface-mapped zones of phyllic and argillic alteration and are further validated by borehole assay data confirming local copper grades exceeding 1%. A comparative assessment of the inversion results indicates that sparsity-based regularization produces subsurface models with sharper lithological boundaries and improved delineation of compact, high-contrast ore bodies, making it particularly effective for resolving localized features at the deposit scale. In contrast, Tikhonov regularization yields smoother models that are better suited for representing broader, regional-scale geological structures. Overall, both inversion approaches are capable of resolving the main subsurface features; however, they emphasize different aspects of the subsurface due to their inherent regularization properties. Accordingly, the choice between them should be guided by the geological objectives rather than interpreted as a general superiority of one method over the other.