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Edge detection is a widely popular data processing tool in magnetic and gravity exploration which plays an important role in defining shapes and horizontal locations of underground geological structures such as faults, rock boundaries, and minor lineaments. Conventional edge detectors, which are mostly derived from the total field anomaly, have long been applied in field exploration. However, the development of full gradient tensor measurement, which improves detection resolution and provides greater geophysical detail for researchers, has given greater importance to edge detection for full gradient tensors. We propose the use of multiple combinations of gradient tensor components and their eigenvalues to construct balanced boundary recognition filters, taking full advantage of information from the gradient tensor matrix. Different synthetic tests demonstrated that model boundaries were definitely detected, and our methods demonstrated great robustness to noise and oblique magnetization. Field processing of magnetic and gravity data using our methods also yielded clear lineaments and structure locations. Compared with other edge detectors derived from gradient tensors, boundary detection accuracy was considerably improved and false edges were nearly eliminated.

Sub-ice-shelf bathymetry strongly influences ice shelf stability by guiding melt-inducing water masses and through pinning points that resist the flow of the overriding ice. Collecting sub-ice-shelf bathymetry data using active source seismic surveying or direct observations is accurate but time-consuming and often impractical. Gravity methods provide a pragmatic, but more uncertain, alternative, by which observed variations in Earth's gravitational field are used to estimate the underlying bathymetry. We utilize a new open-source gravity inversion algorithm developed specifically for modeling sub-ice-shelf bathymetry and estimating the spatially variable uncertainty in the results. The inversion is tested on a suite of models created with high-resolution multibeam bathymetry data. These tests enable (1) determination of the best practices for conducting bathymetric inversions, (2) recognition of the limitations of the inversion and uncertainty quantification, and (3) identification of where community efforts should be focused for the future determination of Antarctica's sub-ice-shelf bathymetry. With an airborne gravity survey with 10 km spacing, 3 mGal of errors, a distribution of known bathymetry measurements, and a regional gravity field representative of the average Antarctic ice shelf, we achieve a root mean squared error of the inverted bathymetry of 23 m. We find that estimating and removing the regional component of gravity before the inversion is the largest source of error in the resulting bathymetry model, but this error can be greatly reduced with additional known bathymetry points. We analyzed Antarctic ice shelves and predict that, if high-resolution gravity data were available, gravity inversion could potentially improve bathymetry models for 95 % of them compared to interpolated products like Bedmap2.

The crustal architecture of northern Egypt, characterized by its tectonic complexity, remains poorly understood due to insufficient seismic data, limited coverage, and inaccuracies in prior gravity models. Recent advancements in satellite gravity methods, however, provide new opportunities to resolve crustal thickness variations with greater precision. In this study, we integrate GOCE gravity data, topography, sediment distributions, and seismic receiver functions to construct a high-resolution Moho depth model for the region. Using inverse and forward modeling techniques, we invert Bouguer anomalies from the GOCO06 gravity field and incorporate data from 50 seismic stations to constrain the model. Our results reveal significant variations in Moho depth, ranging from 23 to 38 km, with thinning to 23–29 km along the coastal zone and thickening to 35–38 km eastward toward the Sinai Peninsula and Red Sea. Forward modeling of three 2.5D crustal cross-sections further elucidates key tectonic features, including [specific features, e.g., fault zones, crustal thinning], which provide new constraints on the region’s tectonic evolution. This integrated approach, combining gravity modeling with seismic and geological constraints, offers a robust crustal thickness model that advances our understanding of northern Egypt’s tectonic history and structure. The findings have important implications for seismic hazard assessment and provide a foundation for future seismic data collection in the region.

Gravity exploration, an Earth science method leveraging gravitational field variations due to density differences in geological structures, is a pivotal tool for subterranean investigation due to its cost-effectiveness and efficient data acquisition. This study focuses on potash, a vital agricultural resource, which forms low-density geological deposits manifesting gravitational anomalies. The research delineates favorable regions for potash enrichment within an exploration zone in Laos, utilizing gravity data, geological information, drilling records, and insights into mineralization mechanisms. The study employed analytic continuation, residual anomaly calculation, and vertical derivative analysis to interpret anomalies and identify low-density potash targets. Apparent density calculations revealed significant variations at different depths. Fault identification using integrated methods identified 16 fault lines, predominantly north–south and northeast oriented. Primary potash targets are in the northeastern and northwestern parts, with secondary targets in the central-western and southeast regions. The study acknowledges limitations such as potential field ambiguity, restricted resolution, and scarce geological data. It recommends integrating other geophysical methods, denser exploration grids, and prompt drilling for verification to refine interpretations and improve understanding, laying a solid foundation for future exploration.

The North China Craton is the oldest continental block, and has suffered from large-scale lithospheric thinning and destruction, which in turn led to gold deposits in northern China. The decratonic gold deposits in the North China Craton became the most important gold deposits in China, and geophysical methods are key means to detect and discover gold deposits there. In this paper, based on the geological and petrophysical characteristics of the North China Craton, the geological model of the decratonic gold deposits is transformed into a geophysical model. At present, two methods of geophysical exploration of decratonic gold deposits are in use: rapid and efficient exploration on the scale of the ore concentration area, and large depth exploration on the scale of the deposit area. In detail, the airborne electromagnetic, magnetic and gravity methods are used to detect the shallow (1,500 m) anomaly area on the scale of the ore concentration area. Through the ground-controlled source electromagnetic and ground magnetotelluric methods, explorations for targets at significant depth (5,000 m) are carried out in the mining area. Then, taking the Liaodong ore concentration area as an example, geophysical methods are used to discover two prospecting areas around the Jianshanzi Fault in the Qingchengzi ore concentration area, Baiyun-Xiaotongjiapuzi deep prospecting area, and Qingchengzi deep prospecting area. Next, three prospecting areas are delineated around the Jixingou Fault in the Wulong mining area, Wulong deep prospecting area, Weishagou deep prospecting area, and Chang’an deep prospecting area. The anomalies in the ore concentration area and mining area are revealed by means of three-dimensional exploration methods, thereby providing technical support for the exploration of metal minerals such as decratonic gold deposits.

Herein, the gravity anomalies are a function of horizontal variations in subsurface rock densities; therefore, the interpretation of gravity anomalies is useful in prospecting the provinces that have contrasting geological structures, which contain crypts, minerals, ores, and hydrocarbon deposit. Depth-size relationships due to geological considerations in the region are also necessary. This study attempted to develop a new fast inversion algorithm to prospect the gravity anomaly profiles, like evaluating the depth, the amplitude coefficient, and the shape parameter of target structures for simple geometric bodies. This new inverted model parameters approach mainly used the analytical signal of the gravity anomaly profile data. The efficiency and stability of this method were tested by many cases such as noise-free and noisy synthetic cases, multiple model cases effect, and the effect of choosing the location of the origin. In addition, the validity of this method was examined by raw gravity data from three different locations around the world, Slovakia, Cuba, and India. In all the three examined real gravity data, it was reported that the estimated parameters were consistent in an appositive manner with the actual ones and with those reported by the extent of research. The necessary time to discover this proper elucidation was very short and the assessed parameters demonstrated that the new suggested method was applicable for gravity exploration. The study concludes that this method can be extracted parameters, which have a significant association in terms of geologic and economic characteristics.

Geophysical methods are instrumental in characterizing lithospheric-scale heterogeneity beneath continental rifts and collisional zones. Seismic imaging techniques, in particular have played a significant role in imaging lithospheric discontinuities within the crust as well as its Moho boundary with the underlying sub-continental lithospheric mantle (SCLM). However, in geodynamic settings where there have been significant mafic magmatic underplating, the seismic Moho and the petrological Moho become distinct, making gravity methods more effective to image the compositional variation between the crust and the SCLM. Our work assesses one of the gravity modeling methods that can be applied to image the petrological Moho by introducing a new approach, which is referred to as the spectral analysis with piecewise regression (SAPR). To test the effectiveness of SAPR, we used the World Gravity Model 2012 (WGM 2012) to calculate the depth to the petrological Moho and the depth to the top of the Precambrian crystalline basement beneath the Lake Turkana rift within the East African Rift System in southern Ethiopia and northern Kenya. Subsequently, the results of the Moho depths from the SAPR were compared with previous Moho depth estimates using other gravity methods as well as controlled-source seismic techniques.

Local gravity and magnetic anomalies are employed to identify potential hydrocarbon reservoirs in the Middle Kura Depression (MKD) within the South Caspian basin in Azerbaijan. The MKD basin in Azerbaijan including the Yevlakh-Agjabedi trough covers a large part of the Kura intermountain basin between the Greater and Lesser Caucasus. In the study region, several local gravity and magnetic anomalies are discovered related to oil and gas deposits in the sedimentary depression whose thickness is 12–14 km. Gravity minima and maxima expressed by different wavelength anomalies are indicative of density variations within the basin. Local gravity minima with an intensity of 0.3–0.4 mGal identified in the study areas are related to the oil–gas deposits. While the local positive magnetic anomalies are associated with the volcanic formations, local negative magnetic anomalies appear over the productive parts of the buried structure within the sedimentary complex. Intense local magnetic minima anomalies with an intensity of 20–30 nT are evidence of oil and gas accumulations. The limitations of traditional methods for interpreting gravity and magnetic data to locate oil and gas fields have led to the use of gravity field gradients. This alternative approach has proven advantageous, as it confirms the results of gravity exploration and is useful for directly searching for hydrocarbons.

Background Fault analysis is a central aspect of gravity exploration,providing vital insights into subsurface geology for resource exploration andmanagement. This study introduces a novel inversion technique tailored for theinterpretation of gravitational responses stemming from subsurface faults.Leveraging techniques like local wavenumber (LWN) and imaging indicator, the methodextracts pertinent insights. Central to the methodology is the computation ofthe rank indicator (β) through the comparison of local wavenumbers betweenobserved and estimated gravitational fields. Results Identifying the maximum rank indicator (β max ) is crucialas it signifies the optimal true target parameters. Rigorous validation isperformed across two synthetic scenarios encompassing noisy, and multi-faultanomalies, Moreover, practical deployment on two distinct real datasets from geologicalhazards and hydrocarbon exploration endeavors in Egypt and USA underscores itseffectiveness. Conclusion The method demonstrates versatility across diverse contexts, highprecision, and a notable ability to operate without requiring prior knowledgeof the source shape. These capabilities are further validated against boreholedata and existing literature. This study introduces a novel inversion technique tailored for the interpretation of gravitational responses stemming from subsurface faults. Leveraging techniques like local wavenumber (LWN) and imaging indicator, the method extracts pertinent insights. Central to the methodology is the computation of the rank indicator (β) through the comparison of local wavenumbers between observed and estimated gravitational fields. Identifying the maximum rank indicator (β max ) is crucial as it signifies the optimal true target parameters. Rigorous validation is performed across two synthetic scenarios encompassing noisy, and multi-fault anomalies, affirming the approach's efficacy. Moreover, practical deployment on two distinct real datasets from geological hazards and hydrocarbon exploration endeavors in Egypt and USA underscores its effectiveness, versatility across diverse contexts, precision, and notable ability to operate sans prior knowledge of source shape, validated against borehole data and existing literature.

The gravity inversion is to restore genetic density distribution of the underground target to be explored for explaining the internal structure and distribution of the Earth. In this paper, we propose a new 3D gravity inversion method based on 3D U-Net++. Compared with two-dimensional gravity inversion, three-dimensional (3D) gravity inversion can more precisely describe the density distribution of underground space. However, conventional 3D gravity inversion method input is two-dimensional, the input and output of the network proposed in our method are three-dimensional. In the training stage, we design a large number of diversified simulation model-data pairs by using the random walk method to improve the generalization ability of the network. In the test phase, we verify the network performance by using the model-data pairs generated by the simulation. To further illustrate the effectiveness of the algorithm, we apply the method to the inversion of the San Nicolas mining area, and the inversion results are basically consistent with the borehole measurement results. Moreover, the results of the 3D U-Net++ inversion and the 3D U-Net inversion are compared. The density models of the 3D U-Net++ inversion have higher resolution, more concentrated inversion results, and a clearer boundary of the density model.