Wadi SabhaΒΆ

Airborne and Ground Time-Domain EM results from the Albany Graphite Discovery


This case history has been adapted from the paper “High-resolution velocity modeling by seismic-airborne TEM joint inversion: A new perspective for near-surface characterization”. It follows a comprehensive multi-physics and joint-inversion study of 3D non-seismic data over the wadi Sahba region off the coast of Qatar. The helicopter-borne TEM and MT data used for this study was collected in December, 2014.



We discuss the use of helicopter-borne transient electromagnetic (HTEM) for a high-resolution spatial and vertical characterization of the near surface in a structure-controlled wadi in central Saudi Arabia. In this area, seismic data quality is poor, and seismic imaging suffers from a combination of scattering effects β€” due to swarms of faults reaching the surface β€” and large velocity variations occurring along subvertical boundaries between the wadi sediment infill and the surrounding carbonate plateaus. HTEM was selected from a suite of non-seismic methods for multiparameter velocity-model building to enhance the velocity estimation for the wadi and surrounding areas. HTEM data were modeled by performing spatially constrained 1D resistivity inversion to obtain a high-resolution image of the near surface with sensitivity to a depth of 400–500 m from the surface. Sharp boundaries of the wadi and fine vertical layering, obtained from the HTEM inversion, provide detailed information about the parameter variations in the near surface. A seismic-HTEM joint-inversion approach is developed using a cross-gradient structural operator to constrain the velocity inversion with the higher resolution HTEM data. Joint-inversion results provide sharp velocity reconstruction across the wadi boundaries and increase the dynamic range of the velocity variations when compared to a single-domain tomographic approach in which the HTEM contribution is ignored. Superior imaging results in both time and depth are derived from velocities estimated by the seismic-TEM joint-inversion approach.