Fixed window joint Euler deconvolution for depth estimation of magnetic and gravity data in the Shavaz region

This study presents an advanced joint Euler deconvolution algorithm for the integrated analysis of magnetic and gravity data, which employs an adaptive fixed window size to enhance subsurface depth estimation in the Shavaz region. By simultaneously solving Euler's equations for both potential fields, the proposed method effectively mitigates the limitations of traditional independent Euler depth estimation analyses, offering improved accuracy in determining the geometry and depth of mineralized bodies and structural discontinuities. Validation through synthetic modeling confirms the accuracy of the algorithm, while its application to field data from the Shavaz region, supported by known geological structures and drilling results, demonstrates its robustness and practical reliability in revealing the spatial distribution of iron mineralization.The adaptive windowing strategy, in conjunction with comprehensive preprocessing, enhances the delineation of anomaly boundaries and the precision of depth solutions. This integrated geophysical methodology provides a robust and efficient tool for mineral exploration within geologically complex terrains, thereby significantly diminishing both interpretational ambiguity and exploration risk.