Ground-penetrating radar (GPR) is an efficient and nondestructive geophysical method with great potential for detecting soil water content at the farmland scale. However, a key challenge in soil detection is obtaining soil water content rapidly and in real-time. In recent years, deep learning methods have become more widespread in the earth sciences, making it possible to use them for soil water content inversion from GPR data. In this paper, we propose a neural network framework GPRSW based on deep learning of GPR data. GPRSW is an end-to-end network that directly inverts volumetric soil water content (VSWC) through single-channel GPR data. Synthetic experiments show that GPRSW accurately identifies different VSWC boundaries in the model in time depth. The predicted VSWC and model fit well within 40 ns, with a maximum error after 40 ns of less than 0.10 cm³ × cm⁻³. To validate our method, we conducted GPR measurements at the experimental field of the Academy of Agricultural Sciences in Gongzhuling City, Jilin Province and applied GPRSW to VSWC measurements. The results show that predicted values of GPRSW match with field soil samples and are consistent with the overall trend of the TDR soil probe samples, with a maximum difference not exceeding 0.03 cm³ × cm⁻³. Therefore, our study shows that GPRSW has the potential to be applied to obtain soil water content from GPR data on farmland.

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 S-transform is a fundamental time–frequency (T-F) domain analysis method in ground penetrating radar (GPR) data processing and can be used for identifying targets, denoising, extracting thin layers, and high-resolution imaging. However, the S-transform spectrum experiences energy leakage near the instantaneous frequency. This phenomenon causes frequency components to erroneously spread over a wider range, impacting the accuracy and precision of GPR data processing. Synchrosqueezing is an effective method to prevent spectrum leakage. In this work, we introduce the synchrosqueezing generalized phase-shifting S-transform (SS-GPST). Initially, it resolves the compatibility issue between the S-transform and the synchrosqueezing strategy through phase-shifting. Subsequently, the SS-GPST accomplishes spectral energy focusing and resolution enhancement via a generalized parameter and synchrosqueezing. A synthetic signal test shows that the SS-GPST excels over other methods at focusing degree, spectral resolution, and signal reconstruction accuracy and speed. In actual GPR tunnel detection data processing, we assess the adaptability of the SS-GPST from three aspects: spectral energy distribution, thin layer identification, and data denoising. The results indicate: (1) compared to other methods, the SS-GPST accurately expresses spectral components with a strong focusing degree and fewer interference components; (2) high-frequency slices of the SS-GPST accurately detect the top and bottom interfaces of a 3.0–3.5 cm reinforcement protection layer; and (3) due to fewer interference components in the SS-GPST spectrum, reconstructing GPR profiles through the SS-GPST inverse transform is an efficient denoising technique. The SS-GPST demonstrates adaptability to different data processing purposes, offers high-resolution T-F spectra, and shows potential to supersede the S-transform.

The Gonghe Basin is one of the most important regions for the exploration and development of hot dry rock geothermal resources in China. However, there is still some controversy about the main heat source of hot dry rock geothermal resources in the Gonghe Basin. Combined with previous research results including three-dimensional magnetotelluric imaging and linear inversion of Rayleigh wave group and phase velocity result, we obtained a high-resolution underground spatial density distribution model of the Gonghe Basin based on satellite gravity data by using 3-D gravity focusing inversion method. According to the results, there are widely distributed low density anomalies relative to surrounding rock in the middle crust of the study area. The low-density layer is speculated to be a low-velocity, high-conductivity partial melting layer in the crust of the Gonghe Basin. The inversion result confirms for the first time the existence of a partial melt layer from the gravity point of view, and this high temperature melt layer may be the main heat source of the hot dry rock geothermal resources in the Gonghe Basin. It can provide a new basis for further research on the genesis of the hot dry rock geothermal system in the Gonghe Basin.

Muon detection technology is an innovative type of geophysical exploration method that uses the penetrating ability of cosmic ray muons to detect and image the internal density structure of targets, offering the advantage of non-destructive detection. However, the applied research on muon detection technology is still in its initial stage, with research gaps existing in aspects such as the selection of optimal field observation parameters for muon detection instruments and muon inversion theory. To improve observation efficiency, this paper studies how to select optimal observation parameters in muon detection technology and proposes a method for selecting optimal observation parameters based on FreeCAD modeling and the energy attenuation formula of muon rays after penetrating matter. Additionally, a density-length product calculation method based on the muon survival rate formula is established, using the muon survival rate formula to reflect muon flux attenuation and thereby perform density inversion of objects. For the first time, muon imaging technology is applied to the detection of the No. 2 Mausoleum of the XiXia Imperial Tombs, verifying that muon imaging technology can effectively identify density anomalies inside the mausoleum tower, providing key data support for the structural analysis and protection of the XiXia Imperial Tombs. This paper systematically studies muon observation and inversion theories, laying a foundation for relevant researchers conducting muon detection work in the future.

Among so many fault basins around Ordos presenting good geothermal background, Yinchuan Plain is the key development and protection area of the Ecological and Economic Belt along the Yellow River in Ningxia and Yinchuan Metropolitan Area. The study of geothermal resources in this region is of great significance to the sustainable economic development of Yinchuan Plain. Most scholars suggested that Yinchuan Plain geothermal resources are low-to-medium temperature geothermal resources and have high value in terms of development and utilization due to their large reserves, good water quality conditions, and wide distribution. However, there is much controversy over the geothermal mechanism of this region. As an effective means to study geothermal mechanism, geophysical methods can be used to study regional basement uplift and structural distribution characteristics. Based on the discussion of regional geothermal geology background, this paper studies the distribution rules of Moho and Curie depths in the region by applying different geophysical data. The results show that the western margin of Yinchuan Plain is obviously uplifted. As inferred from the epicentral distribution of Yinchuan Plain section, there is a significant difference of the seismic bottom interface on the east and west sides of the Yellow River fault in Yinchuan Plain. The three-dimensional gravity inversion confirms basement uplift in this region. By referring to results obtained by the inversion of gravity and magnetic data and deep seismic exploration, the paper presents a comprehensive analysis of the regional geothermal geology conditions and proposes a geothermal conceptual model of Yinchuan Plain. The heat source comes from the earth heat flow and migrates to the thermal reservoir through the fault or fissure convection. The deep-large active faults provide a channel for deep heat flow to the shallow part, and the thermal fluid accumulates in the uplift area to form the high geothermal anomaly area. There should be two large-scale geological activities in the geotropics around Ordos. One is the basement uplift of the basins around Ordos platform, which provide the heat source. The other is the uplift of Ordos, which places the surrounding basin in an extensional environment and provides a channel for the heat source upwelling.