For magnetic inversion, recovering the location and boundaries of causative bodies is challenging. In this study, we propose an improved magnetic inversion method based on the L ₁ norm of the model and its gradients (TV ₁ ). Four weights for the L ₁ norm and TV ₁ penalties are introduced in the L ₁ -TV ₁ inversion, and their effects are discussed comprehensively. These weights are crucial for the inversion, controlling the shape, boundaries, and resolution of the resultant model. Based on extensive synthetic model tests, appropriate parameters are given to achieve good inversion performance. Numerical experiments demonstrate that the proposed approach can reproduce a consistent model with the real solution. Finally, we apply this method to the inversion of the actual data in the Yeshan region, east Jiangsu Province, China, and successfully image the underground magnetic structure.

Salt domes are favorable geological structures associated with hydrocarbon reservoirs and critical mineral resources. Currently, imaging salt diapir subsurface structures has received widespread attention. The gravity method has been widely used to interpret salt structures due to the significant density contrast between salts and surrounding sediments. However, complex mass sources at different depths challenge the interpretation of the gravity data over salt domes. In this study, we put forward the mixed L1 and L2 norm regularized inversion of the gravity data observed on the surface to image the 3-D subsurface structure of salt domes. The synthetic tests demonstrate that the mixed norm regularization inversion of gravity data can effectively recover subsurface complex density anomalies similar to salt dome structures. The practical application in the Vinton Salt Dome reveals a shallow high-density caprock and a deep low-density salt core beneath Vinton Dome, greatly enriching the underground structure information of the study area. It demonstrates that the mixed norm regularized inversion is a valuable interpretation technique for detecting and delineating salt structures.

Evaluating the impact of geomagnetic disturbances on power grid infrastructure is critical to mitigate the risk posed by geomagnetically induced currents (GICs). In this paper, the geoelectric field and induced voltage distribution in North China were estimated from the SinoProbe magnetotelluric (MT) impedance data together with the geomagnetic observatory data of six INTERMAGNET stations recorded during the significant geomagnetic storm of 17th March 2015. The measured impedances from 119 SinoProbe MT sites were convolved with geomagnetic observatory data to account for the Earth's complex three‐dimensional electrical resistivity structure. The resultant geoelectric field was then used to model the induced voltage distribution across the regional power transmission network in North China. Due to the large inter‐site distances of the SinoProbe MT program, the derived geoelectric field is mostly homogeneous, except in the Ordos Basin that displays a polarization of the geoelectric field, and with higher magnitudes in the orogenic belts. The estimated geoelectric fields in Taihang‐Lvliang, Yanshan, and Luxi orogenic belts of North China were large (>1 V/km) during the storm, due to high‐resistivity lithosphere resulting in large voltage gradients in the Earth. However, in relation to locations of major power transmission lines, only the central part of North China experienced induced voltages exceeding 100 V.

• We updated the high-resolution lithospheric magnetic field model for China and surrounding regions as CUG_CLMFM3Dv2. • The CUG_CLMFM3Dv2 model mitigates short-wavelength loss in Xinjiang and Tibet and improves high-altitude accuracy in comparison with the first version. • Comparisons show CUG_CLMFM3Dv2 achieves higher resolution and reliability than global spherical harmonic models. • Multi-component grids that include the magnetic gradient tensor at multiple altitudes are forward calculated and provided.