Gonghe Basin is the most critical distribution area of hot dry rock (HDR) geothermal resources in China. Geophysical results (resistivity, velocity, density, etc.) provide an indirect way to image the spatial distribution to understand its genesis, which has a multisolution problem. However, heat flow and thermal conductivity are the most direct and reliable evidence to reveal the distribution of geothermal resources. The conventional thermal conductivity and heat flow obtained based on geologic surveys and rock samples are highly accurate, but it is challenging to characterize the regional distribution characteristics. In this paper, we develop the heat transfer adaptive finite-element equation parameter inversion workflow to invert the thermal parameters and analyze the geothermal formation mechanisms in the Gonghe Basin. First, the synthetic model test verifies that our inversion process has reliable accuracy and strong antinoise ability. For the Gonghe Basin HDR geothermal example, we use high-precision aeromagnetic data to estimate the Curie depth using the improved Parker-Oldenburg method. Then, the regional conductivity thermal and temperature field can be established according to the empirical formula as the initial input model for the inversion procedure. In addition, we collect the temperature data of six HDR geothermal wells across the Gonghe-Guide Basin as a priori constraint information. Combined with the inverted thermal parameters (thermal conductivity, geothermal gradient, and heat flow), geologic structure, and geophysical result, we infer that the high thermal conductivity layer at a depth of 5–10 km provides the main deep heat source channel and the shallow low thermal conductivity fine sandstone layer of Neogene provides good caprock protection for forming a high-temperature geothermal reservoir.

The lunar regolith penetrating array radar (LRPR) carried by Chang’E-5 (CE-5) has explored the subsurface regolith structure of the moon and guided the drill sampling procedures. To evaluate LRPR performance in subsurface imaging and physical-parameter estimation, we apply multiscale full-waveform inversion (FWI) with total variation (TV) regularization to the synthetic CE-5 LRPR data. The time-domain multiscale inversion strategy gives a low-frequency update for the deep region and increases the frequency range for updating the shallow area. The TV regularization reduces the image noise and improves the inversion accuracy of local structures. To mimic the actual scenario, we use an LRPR source wavelet obtained from the LRPR instrument prototype for our FWI test. The LRPR source wavelets include the effect of the antenna radiation patterns and signal scattering from the metallic lander. We test the proposed FWI scheme on two heterogeneous models of the lunar regolith and demonstrate that the scheme effectively reduces the signal scattering from the metallic lander and provides a reliable way to image the lunar regolith structures. These images can be used to estimate the regolith physical parameters.

Grotto rock structure detection is precondition of the grotto protection and restoration. As a stable and non-destructive geophysical method, electrical resistivity tomography (ERT) is extensively used to detect the geological structure of the grottoes. However, the traditional ERT measurement scheme is challenging to satisfy the requirements of high accuracy and high resolution in the cliff region. Therefore, we propose a new borehole-to-surface-to-cliff ERT (BSC-ERT) scheme for grotto detection. The sensitivity patterns of five ERT schemes using three configurations (A-MN array, AB-MN array, and AM-BN array) are tested to show the detection capability of different configurations. Two numerical experiments show that the combination of borehole-to-surface ERT (BS-ERT) and surface-to-cliff ERT (SC-ERT) schemes using AM-BN array have better imaging effects and a more reasonable detection range, which is recommended to be implemented for future work. In addition, the numerical experiment also proves that the symmetric effect generated in the AM-BN array in BS-ERT scheme can be suppressed with the combination of the SC-ERT scheme.

The spatial distribution of rock fractures during water injection in hot dry rock (HDR) geothermal is essential information for evaluating geothermal well fracturing. The rock fractures produce anisotropic electrical characteristics, which may facilitate geophysical methods for monitoring fracture distribution. This paper studies the anisotropic magnetotelluric (MT) response in water injection fracturing based on the finite difference method (FEM). It uses the residual phase tensor (PT) method to calculate the characteristics of fracture strike and dip angle. The feasibility analysis of the technique under a different angle and resistivity conditions in geothermal reservoir investigation is discussed in detail. The results demonstrate that the MT can explain the characteristics of anisotropic resistivity structure changes from the water injection fracturing of HDR at the 5 km depth. The time-lapse MT monitoring method can provide a reliable scientific basis for fracture distribution direction and spreading characteristics.

The Yinchuan Basin harbors significant geothermal resource potential and could be a clean energy source critical for transitioning to a low-carbon economy. However, the current research primarily focuses on the exploration and development of geothermal water in the sedimentary basins, with limited studies on the deep geothermal formation mechanisms and regional geothermal types. Although geophysical methods provide insights into the types and formation mechanisms of deep geothermal resources in the basin, there is still a lack of a connection between quantitative understanding and direct evidence. A series of algorithms based on thermal parameter characteristics can directly extract underground thermal features from raw geophysical signal data, offering a powerful tool for characterizing the structure and aggregation patterns of deep thermal sources. Therefore, this study employed a Bayesian thermal parameter inversion method based on interface information to obtain the spatial distribution of thermal conductivity, surface heat flow, and mantle heat parameters in the Ningxia Basin study area. Additionally, correlation analysis and global sensitivity analysis were conducted to further interpret the predicted results. A comprehensive analysis of the geophysical inversion results showed that the deep thermal anomalies in the basin are primarily controlled by fault activities and the lithospheres’ thermal structure, while shallow high-heat flow anomalies are closely related to convective circulation within faults and heat transfer from deep thermal sources. The established geothermal genesis mechanism and model of the Yinchuan Basin provide crucial support for sustainable regional geothermal development planning and the utilization of deep geothermal resources, contributing to energy security and emission reduction goals.