Abbreviation (ISO4): Prog Geophy
Editor in chief:
The continents and the oceans are the two members of the earth family. They are all "Earths". The "Earths" cultivate, lived and multiplied on the land and sea, and together maintain social progress, economic prosperity, and the development of science and technology. And continue to create the future. The ocean occupies 70.8% of the total area on this earth, and contains rich and diversified various metal mineral resources. It is a strategic base for the sustainable development of the demand and supply of metal mineral resources in human society. To this end, the main issues discussed in this article are: (1) my country's inland important mineral resources are in short supply, the situation is grim and where to go! (2) Marine mineral resources are abundant, diverse, and have great potential, (3) Submarine metal nodule mineral resources gather, (4) Discovery of many metal sulfide deposits and natural gold in the Indian Ocean, (5) Marine mineral resources in China Exploration and discovery. Obviously, marine mineral resources, exploration, development and utilization are the inevitable trajectory of my country's construction and sustainable development!
Based on the CPC daily maximum temperature dataset from 1979 to 2021, this study identified the summer extreme high temperature events in Northeast Asia, and systematically analyzed the variation characteristics of the number of extreme high temperature days. Combined with NCEP/NCAR reanalysis data and GLDAS soil moisture data, correlation analysis and regression analysis were used to explore the possible influence of soil moisture anomaly in northern Eurasia on the change of extreme high temperature days in Northeast Asia in summer (June to August), and further reveal its potential physical mechanism. The results show that summer extreme high temperature events in Northeast Asia show a significant growth trend, and the high incidence areas are concentrated in northeast China and eastern Inner Mongolia. Further analysis shows that the soil moisture anomaly in the north of Eurasia shows a specific dipole distribution in spring and summer, that is, the soil moisture in the northeast of Europe is dry, and the soil moisture in the north of Lake Baikal and the outer Khingan Mountains is wet, and the land-atmosphere interaction affect atmospheric circulation patterns, contributes to the formation of "positive-negative-positive" zonal wave train structure over Eurasia. The eastward transmission of the wave train transmits the wave energy to the downstream region, contributes to the formation of anticyclonic circulation anomalies and positive geopotential height anomalies over Northeast Asia, which leads to the enhancement of atmospheric subsidence movement in the region, which leads to the surface warming, and finally increases the number of extreme high temperature days in Northeast Asia in summer.
A cast of east-west trending continental slivers, which were composed of the Cimmerian Supercontinent, including the Lhasa continental block, started to rift apart from the northern margin of Gondwana in the late Paleozoic. According to this comprehensive tectonic scenario, several points of view have been proposed on when and from which continent the Lhasa block rifted away from the northern margin of Gondwana over the past decades, however, the issue still remains controversial. To this end, in this study, we aim to provide quantitative constraints on this topic by employing isotope-based geochronological dating and paleomagnetic techniques. Through carrying out an integrated study including zircon U-Pb geochronology, paleomagnetism, petrography, and rock magnetism on the early Middle Permian Luobadui Formation basalts and andesitic basalts developed in and around the northwest part of the Linzhou County of south Xizang (i.e., Tibet), it reveals that the Luobadui Formation volcanics was formed at ca. 272 Ma (i.e., Guadalupian stage of Middle Permian). Based on rock magnetic results carried out by previous scholars and petrographic investigations performed in this study, it shows that the Luobadui Formation volcanic samples experienced low-grade metamorphism along margins of some rock-forming minerals like plagioclase, quartz. Typical accessory minerals like magnetite particles (is also a kind of iron-bearing oxides) distributed in Luobadui Formation volcanic rock samples was also impacted by this low-grade metamorphism. Rock magnetic data sets also suggest that the dominant remanence carriers in the Luobadui Formation volcanic rocks are pseudo-single domain (PSD) magnetite grains in this study. Statistical analysis on filtered characteristic remanent magnetizations from 21 paleomagnetic specimens of the Luobadui Formation volcanic rocks reveals that the Fisherian mean direction and associated parameters over the sampling unit of the Luobadui Formation volcanic rocks are Ds±ΔD=124.2°±8.8°, Is±ΔI=34.5°±7.2°, ks=20.3, α95 s=7.2° after bedding correction. Thus, based on already obtained statistical mean direction over the selected 21 samples of the Middle Permian Luobadui Formation volcanics, the paleomagnetic pole can be computed as λp=16.8°N, φp=325.5°E, K=20.7, A95=7.2°. The paleosecular variation has been adequately averaged out according to paleosecular variation (PSV) evaluation criteria in paleomagnetism for the sampled Luobadui Formation volcanics. Therefore, in combination of positive fold test results for the paleomagnetic data sets with rock magnetic and petrographic results, we believe that our obtained paleomagnetic results are primary origin. It can be calculated (reference site: 30.01°N, 90.99°E) that the Lhasa block was at 19.7°±7.2°S in southern hemisphere at ca. 272 Ma. In other words, the Lhasa block was still in middle-low latitude of southern hemisphere then. Combined with previously published results from the Lhasa block, we intend to think that the Lhasa continental block along with the Cimmerian supercontinent likely rifted away from northern periphery of Gondwana and started its long-lasting northward travel journey in early Permian or even much earlier period. Combined with previously published paleomagnetic and geological results, it shows that the total northward convergence is estimated as 1776±700 km of the Lhasa block travelling from low-middle latitude band of 19.7°±7.2°S at ca. 272 Ma to the equatorial area of 3.7°±3.4°S at ca. 180 Ma. This further indicates that the average motion rate of the Lhasa block was around 1.9 cm/a during the time period of 272~180 Ma. In other words, the Lhasa block likely rifted away from northern margin of Gondwana in Early Permian and immediately started its northward drift and motion journey.
To expand the application of Global Navigation Satellite System Reflectometry (GNSS-R) in the field of ocean monitoring, this paper, based on the CYGNSS wind speed products from 2020 to 2023, combined with the wind speed reference data, makes a systematic assessment of the accuracy of CYGNSS wind speed products and analyses the distribution characteristics of wind energy resources in the tropical and subtropical waters of China. Systematic assessment, and analyses of the distribution characteristics of wind energy resources in China's tropical and subtropical seas. The experimental results show that the extrapolated wind speed accuracy of the CYGNSS wind speed product is improved by about 47% after the correction of sea surface roughness, and it has a good matching accuracy with the reference data, which meets the needs of wind energy assessment. In the study area, wind energy resources are more abundant in the southeastern sea, among which the Taiwan Strait has the highest annual average wind power density, reaching more than 550 W/m2. In the southern part of the South China Sea, wind energy resources are relatively scarce, and the annual average wind power density is lower than 250 W/m2; the wind power density of each sea area has significant seasonal differences, and the distribution of wind energy resources in the East China Sea is relatively stable in all seasons, with the distribution maintained at more than 300 W/m2 all year round, while in the South China Sea there is a more violent seasonal fluctuation, and the difference between the average wind power density of the winter and summer seasons is significant; in terms of the potential for development, the wind power density in shallow waters in the southern part of the Yellow Sea is relatively high. In terms of developing potential, the southern Yellow Sea and other sea areas have high wind energy reserves and technological development capacity in shallow waters, while the northeastern part of the South China Sea and other sea areas show great development potential in deep waters.
Carbon Capture, Utilization, and Storage (CCUS) has emerged as a effective strategy for mitigating atmospheric CO2 emissions. However, the large-scale subsurface injection of CO2 may induce ground surface deformation, potentially compromising the long-term integrity of CO2 storage. To investigate surface displacement patterns in CCUS project areas following CO2 injection, this study employed the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to analyze 45 ascending Sentinel-1A images acquired between January 2022 and August 2024, enabling comprehensive deformation monitoring over a 2.5-year period in a Chinese CCUS geological storage site. Recognizing the impact of tropospheric delay errors on InSAR measurements, we developed an enhanced atmospheric delay correction approach synergizing Global Navigation Satellite System (GNSS) data and ERA5 reanalysis data, specifically optimized for small-scale regional applications. Analysis of the phase-unwrapped interferograms confirms that our GNSS-constrained atmospheric correction approach significantly reduces tropospheric delay artifacts in localized interferometric observations. The derived InSAR deformation field reveals distinct surface displacement patterns in the CO2 injection zone, with measured vertical deformation rates ranging from 0 to 10 mm/a. Deformation time series analysis at monitoring points adjacent to injection wells reveals a consistent response: initial surface uplift immediately following CO2 injection, followed by gradual subsidence after several months. This pattern was confirmed through comparative analysis of InSAR-derived vertical displacements (converted from LOS measurements) and independent GNSS observations. This study demonstrates that the synergistic use of GNSS and InSAR technologies enables precise monitoring of millimeter-scale surface deformation in CCUS operational areas. The GNSS infrastructure serves dual purposes: (1) enhancing InSAR measurement accuracy through tropospheric delay correction, and (2) providing independent validation of InSAR-derived deformation results. These findings underscore the critical importance of integrated geodetic monitoring for ensuring the safety and efficacy of CO2 geological storage operations.
The traditional Gravity-Geologic Method (GGM) is an approach that combines shipborne bathymetric data and marine gravity anomalies data to invert seafloor topography by resolving short-wavelength gravity anomalies using the Bouguer plate formula. To further enhance the accuracy of GGM in seafloor topography inversion, an Improved Gravity-Geologic Method (IGGM) has been developed in this paper. A weighting parameter was introduced into the Bouguer plate formula, and short-wavelength gravity corrections were calculated at control points to refine the long-wavelength gravity field modeling further. A seafloor topography model with a spatial resolution of 1′×1′ was constructed for the reef area near the Nansha Islands (112°E—116°E, 8°N—12°N) using the Improved Gravity-Geologic Method. The accuracy of the model was evaluated using shipborne bathymetric data provided by the National Oceanic and Atmospheric Administration of the United States (NOAA). Results indicate that the IGGM model more accurately reflects fine topographic variations, with the standard deviation of 175.68 m in depth differences from measured data, representing a reduction of 7.01 m, 20.67 m and 19.68 m compared to the GGM model, the SIO V25.1 model and the SRTM15+V2.0 model, respectively. Compared to the GGM model, the IGGM model shows a significant accuracy advantage in complex reef areas with depths ≤1000 m, reducing the standard deviation of depth differences by 10.20 m. This validates the effectiveness of the Improved Gravity-Geologic Method in enhancing inversion accuracy, especially in reef regions, where it more accurately reflects the trend of seafloor topography changes, providing essential support for seafloor topography modeling in these areas.
The Mid-Lithospheric Discontinuities (MLD) are an important interface recently discovered in the continental lithospheric mantle. They are closely related to the formation and tectonic evolution of the continental lithosphere. However, their origin remains unclear and has not reached a consensus. The South China Block has a very complex lithospheric structure. Its internal structure and evolution have long been major issues in geoscience. The mechanism of regional lithospheric thinning in the eastern part is still highly debated. Recent seismological studies have found evidence of MLD in the lithospheric mantle of the central and western South China Block. To further investigate the spatial distribution of MLD within the South China Block, this study uses seismic data recorded by national network stations distributed across the block. The single-station S-wave receiver function stacking technique and the k-means+[KG-*2/5]+clustering analysis method are applied to systematically detect MLD in the South China Block. The results show that MLD in the South China Block is mainly distributed in the Upper Yangtze Block. The depth ranges from 75 to 130 km. Beneath some stations in the Sichuan Basin, two possible MLD signals are observed in the mantle lithosphere. The MLD may have originally formed as the continental Lithosphere-Asthenosphere Boundary (LAB) at shallow depths. The ancient magmatic ocean LAB might have been captured or preserved. As the lithosphere cooled, it migrated to greater depths and now appears as the current LAB. In the eastern part of the South China Block, the lithosphere may have delaminated along the original MLD due to the influence of the subduction and retreat of the ancient Pacific Plate. Later, under thermal erosion and extensional forces, the lithosphere continued to thin. The MLD interface was destroyed. As a result, no MLD is observed in the eastern part of the South China Block. This study provides new insights into the spatial distribution and possible formation mechanisms of MLD in the South China Block. It also contributes to understanding the complex lithospheric evolution of the region.
Microseismic monitoring is widely used in the analysis of engineering disasters such as mines and tunnels, all of which are based on microseismic source parameters. The calculation of microseismic source spectrum is the basis of source parameter calculation. Once the source spectrum is determined, most of the source parameters can be calculated accordingly. However, research into the calculation process and method of microseismic source spectra is limited. Therefore, we investigated the basic steps and methods of microseismic source spectrum calculation in detail. This includes four main steps: waveform processing and source location; signal spectrum calculation; signal spectrum correction and source spectrum determination. Signal processing involves removing the instrument response, filtering and arrival picking with localisation to provide basic parameters for subsequent calculations. Signal spectrum calculation involves not only common methods such as the discrete Fourier transform, but also the lag-window spectral technique and multi-taper methods. Signal spectrum correction involves geometric spreading, site effects, and attenuation, which are all influenced by multiple and complex factors. Source spectrum determination initially requires the theoretical source spectrum model to be determined, followed by the selection of the objective function and fitting method. This study briefly analyses the impact of these factors on the calculation of the microseismic source spectrum and suggests possible future research directions. These results can be used as a reference for calculating the source spectrum, thereby establishing a foundation for calculating source parameters and ultimately providing theoretical support for standardising and normalising engineering microseismic monitoring and the quantitative warning of engineering disasters.
Multimodal information fusion technology is an emerging field that has flourished in recent years, representing the application of artificial intelligence theories and technologies in information analysis and processing. It plays a crucial role in various domains, such as battlefield situational awareness, industrial robotics, remote medical care, and autonomous driving. With the rapid development of geophysical exploration theories and technologies, particularly with the significant advancements in China's airborne and satellite-based Earth observation technologies in recent years, the massive data generated poses a severe challenge to the traditional analysis models, which are primarily based on human experience. There is an increasing demand to introduce multi-information fusion technology into the field of geosciences, especially in the domain of geophysical exploration data. However, due to the differences in methods, scenarios, and equipment in geophysical observations, the data obtained have varying spatial distribution standards, making subsequent information fusion calculations difficult. Therefore, it is necessary to preprocess the observational data according to a unified standard to ensure that the data have consistent observational density. Currently, both the theory and technology for voxel-based preprocessing of observational data, which is crucial for multi-information fusion, are lacking. In some studies, traditional prediction techniques have been used to perform quasi-three-dimensional (or quasi-voxel-based) data standardization, but the effectiveness of these approaches is still under evaluation. Therefore, this paper reviews the existing data standardization preprocessing methods from the perspective of geophysical multi-information fusion methods. It introduces a semi-airborne electromagnetic observation case to discuss the performance of various existing methods, providing a methodological basis for further developing and refining the geophysical multi-information fusion processing technology system.
Geophysical exploration has a wide range of applications in the fields of energy exploration, environmental monitoring and engineering survey by quantitatively processing the observed field source data for subsurface target detection. However, the geophysical exploration method using a single data has the problems of multiple solutions and low resolution in the inversion process. Therefore, joint inversion by synthesizing multiple geophysical observation data has more significant advantages than single inversion. Electromagnetic exploration and seismic exploration are two kinds of geophysical exploration methods based on different physical mechanisms, which typically differ in spatial resolution and sensitivity to the target. Therefore, the combination of the two can significantly improve the reliability of the inversion results. As an important means for quantitatively interpreting electromagnetic and seismic data, joint electromagnetic and seismic inversion can effectively reduce the multiple solutions of single data inversion and improve the prediction accuracy of formation parameters. This paper firstly summarizes the classification of electromagnetic and seismic joint inversion and its development history, then describes the principle and application examples of joint inversion method, and finally discusses its development opportunities and looks forward to the future research direction.
To address the three-dimensional (3D) forward modeling problem of transient electromagnetic fields for grounded-wire source, this paper explores a finite element forward modeling method that employs a frequency-time transformation and background-scattered field separation strategy. It utilizes the vector finite element theory, and the 3D model is discretized using structured hexahedral mesh. Subsequently, the frequency-domain numerical response is computed using the MUMPS solver. Ultimately, the time-domain transient electromagnetic response is derived via cosine transformation. On this basis, the reliability of the forward algorithm is validated using both a one-dimensional layered model and an open three-dimensional model, and its computational accuracy is assessed. Theoretical examples show that the calculation results of the 3D transient electromagnetic forward modeling proposed in this paper are accurate and can meet the calculation requirements of 3D inversion research.
The difference in formation wave impedance is one of the important factors affecting the quality of wellbore microseismic monitoring data. Based on Snell's law and the Zoeppritz equation, by studying the influence of wave impedance difference and incident angle on the characteristics of the first arrival wave signals of microseisms, the relationship between the energy of the first arrival waves in wellbore microseismic data, the magnitude of the formation wave impedance difference, and the incident critical angle was revealed and verified through forward modeling. It was concluded that formations with large wave impedance differences have a significant impact on the energy and propagation path of the first arrival waves. Taking Well XX in a coalbed methane field as an example, at Perforation Section 1, some geophones failed to receive the first arrival signals, which affected the three-component rotation positioning of the geophones and the monitoring interpretation. By obtaining the formation velocity information of the target interval from acoustic logging data and combining it with the changes in formation wave impedance, the reasons for the absence of the first arrival waves in the microseismic perforation records of some geophones were analyzed. The deployment depth of the geophones was adjusted in a timely manner to solve the problem that some geophones could not detect the first arrival waves when the wave impedance difference was large and the incident angle was greater than the critical angle. After the depth of the geophones was adjusted upward by 30 meters, good first arrival wave signals were obtained at Perforation Section 2. The positioning results of these signals were used for wellbore microseismic fracturing fracture monitoring. The interpretation results, when comprehensively analyzed with conventional logging and dipole acoustic logging, showed that the microseismic event points were basically consistent in height with the reservoir characteristics and the fracture height indicated by dipole acoustic logging.
The dispersion and attenuation of seismic waves are critical physical properties of hydrate reservoirs, essential for the precise identification and quantitative characterization of hydrate reservoirs. The coupled effects of hydrate saturation and occurrence modes typically exert significant influences on seismic wave velocity dispersion and attenuation characteristics. However, most existing attenuation characterization theories are established based on assumptions of single or limited hydrate morphologies, making it challenging to accurately describe hydrate reservoirs with complex occurrence states. To address this, this study integrates the generalized effective medium model and two-phase media theory to develop an attenuation theoretical model for hydrate reservoirs that simultaneously considers four occurrence modes: contact-cementing, grain-coating, matrix-supporting, and pore-filling. A comparison of P-wave attenuation characteristics modeled using Biot theory (focusing on global fluid flow in porous media) and BISQ theory (Biot-Squirt theory, incorporating both global fluid flow and local squirt mechanisms) under different hydrate morphologies reveals that the attenuation predicted by Biot theory is significantly lower than that of the BISQ model. This discrepancy arises because the BISQ framework accounts for additional energy loss mechanisms, such as microscopic fluid squirt between hydrate-coated grains, which are critical in heterogeneous hydrate-bearing sediments. Based on the BISQ-derived attenuation model, a morphology-constrained attenuation rock physics template is developed, and a crossplot of P-wave velocity, attenuation, and hydrate saturation is constructed to identify hydrate occurrence modes. Furthermore, the developed morphology-constrained attenuation rock physics template is applied to logging data from Sites 1247B and 1250F of the Ocean Drilling Program (ODP) Expedition 204. Field results demonstrate that the constructed crossplot of P-wave velocity and attenuation versus hydrate saturation accurately identifies hydrate occurrence modes, and the attenuation rock physics template aligns well with the distribution characteristics of logging data. These research outcomes provide a new theoretical foundation and technical methodology for utilizing seismic attenuation attributes to identify and evaluate hydrate reservoirs, confirming the capability of attenuation theory to accurately diagnose occurrence states and estimate reservoir physical parameters.
Three-dimensional gravity inversion is the process of obtaining the location, shape, and physical parameters of underground anomalies using gravity anomaly data observed at the surface. In recent years, the rapid development of data-driven methods has led to widespread interest in applying Deep Learning (DL) techniques to gravity inversion problems, yielding certain results. Research based on the U-Net network that employs an Attention Feature Fusion (AFF) mechanism for three-dimensional gravity inversion enhances the vertical resolution of the inversion results. However, the reconstruction effect for deeper models still needs improvement. Building on this, the use of Global Receptive Convolution (GRC) to replace certain standard convolutions aims to ensure that the convolution process meets the conditions of spatial position and channel indexing. This approach integrates global and local features into a pixel-wise representation, further learning the original features to improve the reconstruction resolution of deeper models. The network's inversion results show enhanced vertical resolution, and experimental results from the San Nicolás deposit in Mexico demonstrate that the inversion network can clearly predict the basic location and approximate shape of the sulfur deposit, aligning well with known geological data.
To utilize wave field characteristics for transient electromagnetic data interpretation, enhance the interpretation accuracy of electromagnetic detection, and overcome the limitations of traditional diffusion field interpretation capabilities. This paper proposes a multi-constrained wavefield transformation algorithm based on integral transform relationships between diffusion and wavefields, with its core being the construction of an objective function that integrates diffusion field data characteristics and wavefield frequency features. First, based on the wavefield transformation theory, this study constructs an objective function framework. Within this framework, filtering process constraints and wavefield characteristic constraints are introduced. The filtering constraints mitigate the loss of wavefield resolution caused by traditional smoothing constraints, while the wavefield characteristic constraints further narrow the solution space based on wavefield propagation features. These two constraint terms are integrated into a unified objective function to enhance the accuracy of inverse transformation. Next, for optimizing the objective function, a quasi-Newton algorithm is employed for iterative optimization. During computation, this approach eliminates the need to compute the complex Hessian matrix required in traditional methods, ensuring both efficiency and robustness. Through iterative calculations, a virtual wavefield that satisfies both data constraints and wavefield characteristics is ultimately obtained. Finally, the proposed algorithm is applied to perform wavefield transformation on Transient Electromagnetic (TEM) forward modeling data from layered and complex geological models, validating its effectiveness and stability in practical applications. During the wavefield transformation process, comparative analysis with forward modeling data is conducted to investigate the algorithm's performance under diverse geological models, ensuring broad applicability and accuracy. Numerical experimental results demonstrate that the transformed wavefields retain the propagation characteristics of the wavefield and align closely with the forward modeling results, fully confirming the validity of the inverse transformation algorithm proposed in this study. This study provides a theoretical foundation for interpreting transient electromagnetic quasi-wave equations and holds application value in deep mineral exploration and complex geological structure identification
With the deepening of exploration and development of unconventional oil and gas reservoirs, especially pore-fracture reservoirs with both pore and fracture reservoir structures have become a research hotspot. Due to the complexity of geological conditions and the band limit of seismic data, these reservoirs often show hidden characteristics on longitudinal seismic data, and it is very necessary to carry out multi-wave seismic response analysis of pore-fracture reservoirs. In this paper, we combine the anisotropic fluid substitution theory of Gassmann equation and Thomsen anisotropic parameter theory to carry out equivalent HTI medium petrophysical modeling; use 2.5-dimensional staggered-grid finite-difference method to carry out highly efficient elastic fluctuation orthotropic simulation; and analyze the characteristics and sensitivity of the multi-wave AVO and AVAz responses in a variety of geological conditions. The model characterization shows that the PP wave near-deviation amplitude and PS wave far-deviation amplitude are more sensitive to the changes of fracture density and porosity, which can better reflect the changes of the two parameters; the amplitudes of different offset distances have similar characteristics of the changes with water saturation, and there is a sudden change near 90%; the PP wave AVAz characteristics show that the amplitude amplitude amplitude is near-deviation and far-deviation, and the PS wave shows the opposite trend, and all of them are periodic changes, which can indicate the The PS wave AVAz characteristics show an opposite trend in amplitude, and both of them change periodically, which can indicate the fracture orientation; the defining equation of the PS wave tuned thickness is deduced, which complements the characterization of the multi-wave tuned thickness. The significance of the pore-fracture type reservoir response characteristics to the actual data interpretation is summarized, which provides an important reference for understanding the fluctuation response characteristics of complex pore-fracture reservoirs, helps to understand the actual seismic data phenomena of complex pore-fracture reservoirs, and can effectively assist the design of the interpretation scheme to improve the accuracy of the interpretation.
The marine exploration environment is generally regarded as a fluid-solid boundary coupling medium. High-precision imaging of the fluid-solid boundary coupling medium can be achieved by using the decoupled elastic wave field for reverse-time migration. Traditional elastic wave decoupling utilizes the Helmholtz principle, but the separated P-waves and S-waves have phase and amplitude issues, which seriously affect the final imaging quality. This paper starts from the first-order velocity-stress elastic medium wave equation, separates the full elastic wave field into pure P-waves and pure S-waves to construct a new coupling equation, avoiding the phase and amplitude problems and crosstalk artifacts caused by the traditional Helmholtz decomposition; analyzes the displacement and stress continuity conditions at the boundary of the fluid-solid boundary coupling medium, and establishes the acoustic-elastic coupling vector separation equation; compares the numerical simulation results with the acoustic wave equation to verify the effectiveness and accuracy of the proposed acoustic-elastic coupling vector separation equation forward modeling method, and compares the results with the conventional reverse-time migration imaging method in a complex seabed model to verify the reliability of the reverse-time migration imaging results.
Dielectric logging technology is limited by its shallow probe depth, and the influence of mud cake cannot be ignored. By measuring the dielectric spectrum of 25 artificial mud cakes with different electrical properties, the electrical characteristics and dielectric dispersion model of mud cakes are revealed in this paper. The mud cake was prepared by mixing barite, bentonite, kaolin, sodium chloride and water, and the effect of salinity, clay mineral content and clay mineral type on the electrical properties of the mud cake was studied and discussed by using the terminal open-circuit coaxial reflection method. The experimental results show that in the low frequency band, the dielectric constant of mud cake increases with the increase of montmorillonite proportion, the increase with the increase of clay mineral content and salinity, and the relationship with salinity is linear positive, and the relationship with clay mineral content is more complex, showing a quadratic function increase. In the high frequency band, the dielectric constant increases with the increase of clay mineral content, and is less affected by clay mineral type and salinity. The modified Shaly Sand model (SHSD) dielectric dispersion model can effectively describe this law. The results of this study provide basic data and theoretical basis for environmental correction and forward and inverse research of sweep frequency dielectric logging data.
The tight oil resources in the Triassic Yanchang Formation in the Ganquan area of the southern Ordos Basin have great potential. However, the research on rock mechanical parameters and in-situ stress analysis of its tight sandstone reservoirs is relatively lagging. In this paper, small cores with angles of 0° (parallel, H), 45° (oblique intersection) and 90° (perpendicular, V) to the bedding plane were drilled, and X-ray diffraction, scanning electron microscopy and triaxial stress experiments were carried out. The research shows that the minerals in the Chang 8 layer samples are mainly quartz (31.8%), plagioclase (22.6%) and clay (26.6%), with a total content of 81.0%. Scanning electron microscopy shows that there are quartz overgrowth, intergranular and grain-surface clay mineral filling in the core, and there are intergranular residual pores. Under different bedding directions, the Kaiser point stress value, peak load value and compressive strength decrease in turn, while the elastic modulus and Poisson's ratio first decrease and then increase. There is a logarithmic function relationship between the pore volume compressibility coefficient and the effective stress. Through the analysis and prediction of logging data and experimental data, the dynamic elastic modulus is higher than the static one, and the dynamic Poisson's ratio is lower than the static one. The prediction results of compressive strength, tensile strength and in-situ stress are consistent with the experimental results. The research results provide new indicators for the prediction of "sweet spots" in the integration of geology and engineering of tight oil reservoirs in the Chang 8 interval of the Ganquan area. They have important guiding value for the identification of comprehensive sweet spots in tight oil reservoirs in the southern part of the Ordos Basin, the optimization of horizontal well trajectories, the design of fracturing stages and clusters, and the optimization of construction parameters.
When numerically simulating the elastic wave field in anisotropic media using the rotated staggered grid finite difference method, numerical dispersion phenomena usually occur. To solve this problem, a time-domain high-order difference coefficient calculation model based on the coupling of Taylor expansion and sampling approximation method is proposed, and an improved space-time domain high-order rotating staggered grid scheme is constructed. To verify the performance of the modified algorithm, the improved algorithm is compared with the general staggered grid and other rotated staggered grids, and the dispersion degree and stability of each algorithm are analyzed. Through the results of numerical experiments, it is found that the algorithm improved by the optimization strategy of the difference operator coefficients based on the Taylor expansion and the sampling approximation method can significantly suppress the dispersion of the elastic wave field in isotropic media, VTI/TTI anisotropic media, and the modified BP model.
The Bongor Basin in Chad is located in the western extension zone of the Central African Rift System. Its Cretaceous P reservoir, as the main production layer, has complex lithology and significant heterogeneity, and the oil reservoir resistivity values vary greatly, making saturation evaluation difficult. Based on data from lithology, physical properties, rock electrical experiments, and nuclear magnetic experiments, this study focuses on the Baobab and Daniela blocks in the Bongor Basin of Chad. The study analyzes the complex wettability characteristics of the P reservoir in the Bongor Basin and proposes a saturation calculation model that combines rock wettability with electrical resistivity. Research has shown that the P group sand bodies can be divided into four sets from top to bottom. The first set is composed of thin sandstone layers containing mud, witharesistivity of less than 20 Ω·m, using a mud sandstone saturation model; The second set is partially thick sandstone with a resistivity of less than 100 Ω·m, suitable for hydrophilic models; The third set has an abnormally high resistivity reservoir with a resistivity of 300~1000 Ω·m, which is explained by an oil affinity model; The resistivity of the second set of partial sand bodies and the fourth set of sand bodies is between 100 and 300 Ω·m, suitable for the mixed wetting model. This method achieves accurate calculation of saturation of complex wettability reservoirs in the Bongor Basin of Chad, providing key technical support for efficient exploration and development in the basin in the future.
The JN area is located in the lithogenic syncline of the high and steep fold belt in east Sichuan Basin, The exploration potential of oil and gas resources is great, the first 3D seismic acquisition was carried out in 2007, due to the lack of pertinence of the early 3D acquisition scheme, There are some problems, such as small azimuth, low folds, large rolling line distance and serious acquisition footprints, it is difficult to meet the demand of exploration and development of target layer after repeated reprocessing of acquired data, in recent years, the observation system scheme of several blocks in the adjacent area have been optimized, the imaging effect of the data has been improved significantly, which strongly supports the exploration and evaluation of the target layer. In view of the acquisition difficulties of exploration and development in this work area, combined with the optimization design experience of observation system in neighboring areas, this paper demonstrates the key parameters of the observation system through the observation system design technology based on three-dimensional complex geological model, and puts forward an observation system scheme with small bin, wide azimuth and high fold that meets the exploration and development needs in this area. The feasibility of the observation system is demonstrated by comparing the amplitude and the coherence attribute of different object images, which provides theoretical guidance and basis for the optimization design of the 3D secondary acquisition high-precision seismic observation system in JN area.
A comprehensive statics technique for converted wave data was adopted effectively to solve the problems of low signal-to-noise ratio, serious statics and imaging difficulties in fracturedcarbonate reservoir in the study survey of southern Sichuan Basin. Thisstatics technique combinedthe surfave wave dispersion curves in version, common-detection-point stackingand cross-correlating method and nonlinear global optimization method for residual statics together.The converted wave prestack time migration technique for VTI anisotropic medium was appliedto solve the complex imaging problem, which wasbased on the establishment of migration velocity models and anisotropic parameter models for both PP and converted wave data.The processing results showed that the imaging quality of converted wave data with low signal to noise ratiowas improvedeffectively, with the diffraction energy beingfocused, the far offset imaging gathers being flattenedand the target layersbeing migrated accurately.The final two migration profiles of PP wave and converted wave data correlated with each other clearly with the consistent corresponding features, and the target layer is clearly imigrated, which built a good foundation for gas and water identification and fractured carbonate reservoir detection in the target formaton.
Manual fault interpretation is time-consuming and the experience of the interpreters tends to increase the uncertainty of the fault interpretation. With the development of computers and artificial intelligence, varieties of algorithms based on convolutional neural networks are more widely used in fault recognition. In order to further improve the accuracy of fault identification, a multi attribute convolutional neural network is proposed to identify faults. First, the residual block is introduced to replace the convolutional block in 3D UNet to simplify the learning goal and reduce the difficulty of training. Then the dilated convolution module and multi-layer deep supervision mechanism are introduced to take advantage of multi-scale information more effectively and further improve the accuracy of fault recognition. Finally, the four-channel network is constructed with multiple seismic attributes to learn various response characteristics of faults. The synthetic model test and the application of real seismic data show that this method can effectively identify the fault location, reduce the missed and wrong identification of small faults, and significantly improve the accuracy of fault identification.
Seismic inversion, a critical method for inferring subsurface petrophysical parameters (acoustic impedance) from seismic data, plays a vital role in hydrocarbon exploration and geological research. However, conventional seismic inversion methods heavily rely on low-frequency background models, exhibit sensitivity to noise interference, and suffer from low computational efficiency, making them inadequate for high-precision inversion under complex geological conditions.In recent years, Convolutional Neural Networks (CNN) have been widely adopted in seismic impedance inversion due to their strong nonlinear modeling capabilities and end-to-end learning approaches, enabling effective mapping of seismic data to impedance values. Nevertheless, deep CNN architecture still face challenges such as gradient vanishing, gradient explosion, and overfitting, which compromise the stability and accuracy of inversion results. To address these limitations, this study proposes a ResUNet-based inversion approach by integrating residual blocks into a UNet framework, thereby mitigating gradient vanishing and information loss issues while enhancing inversion accuracy and stability. Synthetic seismic data generated through forward modeling were used to train the ResUNet model, and real seismic data were subsequently input into the trained network to derive impedance inversion results. However, the intelligent inversion outputs may exhibit discrete artifacts and "spiking" phenomena near complex geological features (fault), impairing the smoothness and continuity of the results. To optimize the inversion outputs, a post-processing smoothing technique was further introduced to suppress anomalies and improve stability. Theoretical model testing and real-data validation demonstrate that the ResUNet combined with smoothing effectively enhances the precision and stability of seismic acoustic impedance inversion, offering a feasible novel method for intelligent seismic inversion applications.
In both natural and industrial settings, the issue of underwater gas leakage has received increasing attention. This encompasses leaks resulting from ocean engineering endeavors as well as those that occur naturally. Such leaks have emerged as a major challenge for the protection of marine environments. To accurately obtain information from these emergencies and implement prompt responses, experts across various disciplines have been suggesting and investigating novel, dependable methods for detecting underwater gas leaks over the last few decades. Building upon thorough and detailed research of existing technologies, this article examines carrier detection and marine environmental detection, systematically evaluates the current leading technologies for detecting seabed gas leaks. Furthermore, the article offers a detailed analysis of the various challenges currently faced by gas leak detection and anticipates future development trends, with the aim of providing reference and insights for research and practice in related areas.
Submarine mud volcanoes are uplifted landforms formed by the escape of submarine fluids. Studying their evolution process is of great significance for the exploration of marine oil and gas resources, the protection of marine biodiversity, and the prevention of marine geological disasters. Based on the existing research, this paper systematically reviews and summarizes the identification characteristics of submarine mud volcanoes under different acoustic detection methods using submarine acoustic instruments and platforms. It also summarizes the morphological features, causes, and evolution stages of submarine mud volcanoes, and analyzes and discusses the progress of quantitative research on the morphology of submarine mud volcanoes. The investigation results show that theacoustic data obtained by combining multiple acoustic methods can not only be used to obtain the morphological and profile characteristics of submarine mud volcanoes, but also serve as supporting data for quantitative research on the morphology of submarine mud volcanoes. Due to the low detection resolution and narrow detection range, the submarine mud volcanoes identified in China at present are mainly large and medium-scale and dome-shaped. Small-scale and complex-shaped submarine mud volcanoes are difficult to identify. The morphological parameters of submarine mud volcanoes are mainly water depth, diameter and slope. There is less research on other parameters such as the slope of the two wings and the depth of the depression. It is suggested to continuously improve the detection technology to enhance the detection resolution, and to use multiple carrier platforms to expand the detection range of the seabed to obtain higher-resolution and more abundant seabed topographic and geomorphic data. At the same time, on the basis of the existing detection technology and detection resolution, the quantitative research on the morphology of submarine mud volcanoes should be deepened to obtain rich morphological quantitative parameters and achieve precise quantitative research. Automatic identification methods such as deep learning should be introduced to realize the automatic identification of submarine mud volcanoes and improve the efficiency of identifying submarine mud volcanoes.
Distributed Acoustic Sensing (DAS) technology leverages the linear response of Rayleigh backscattered light in optical fibers to external acoustic fields, enabling distributed sensing and collection of vibrations. This technology has seen extensive application in seismic exploration. However, conventional straight optical fibers exhibit sensitivity primarily along the fiber axis, limiting their effectiveness in detecting vertically incident seismic waves, thus constraining their use in surface seismic surveys. To address this limitation, a Helically Wound Cable-Based Distributed Acoustic Sensing (HWC-DAS) technique has been proposed. In this approach, the fiber is helically wrapped around a deformable elastic medium, improving directional sensitivity and enhancing its ability to detect vertically incident reflections, significantly boosting sensitivity. Nevertheless, systematic comparisons between HWC-DAS and traditional seismic geophones remain sparse, and the differences in their sensitivity, Signal-to-Noise Ratio (SNR), and frequency-dependent responses are not yet clearly understood. To fill this knowledge gap, we conducted controlled laboratory experiments, including shaking table and vibration-sensing tests, to systematically compare the performance of HWC-DAS with conventional seismic geophones. Results from shaking table experiments indicate that HWC-DAS exhibits vibration response capabilities comparable to those of geophones across various frequency bands. Furthermore, vibration-sensing tests demonstrated that HWC-DAS achieves higher sensitivity and improved SNR compared to single-point geophones. Our study validates the effectiveness and feasibility of HWC-DAS for seismic exploration through laboratory experimentation, laying foundational groundwork for its practical deployment in industry.
Aiming at the problem of invisible diseases of tower foundation concrete in power transmission and transformation projects caused by improper operation and related environmental factors during construction, this paper proposes a GPR image recognition method for hidden diseases of tower foundation in power transmission and transformation projects based on improved Faster R-CNN. Firstly, the traditional Faster R-CNN model is optimized, and RseNet-50 is used as the feature extraction backbone network, combined with the attention mechanism (SE module). By adding the SE module to different levels of the network and placing the SE module in different positions for comparative experiments, the optimal position in the model is judged, so that the model can reduce the redundant calculation burden on the basis of extracting the key information in the feature map. Secondly, the soft-NMS algorithm is used to improve the detection ability of closely connected targets. Finally, based on the measured data of the rigid straight column foundation, the simulation is carried out by gprMax, and the GPR image is processed by the generative adversarial network to expand the data set and enhance the learning ability of the model. The experimental results show that the average accuracy of the optimized model is 84.49%, and the F-Score is 77.58%. Compared with the traditional Faster-RCNN target detection model, the recognition accuracy is improved by 6.37% on the basis of the same data set.
In shallow geological exploration, drilling and geophysical prospecting are two distinct technical methods that play different roles in the acquisition of geological and geophysical data. With the continuous advancement of modern science and technology, the direction is towards green, intelligent, and precise exploration. Integrating drilling and geophysical prospecting technologies can achieve the acquisition of multiple information parameters, such as the structure and physical properties of rock and soil layers, in a single borehole. This integration provides a foundation for the construction of transparent geological models and the precise identification of underground space information. This paper combines the current state of research and development on integrated drilling and geophysical prospecting technologies and equipment to analyze future development trends of intelligent integrated drilling and geophysical prospecting technologies and equipment for shallow layers. It posits that the current period is crucial for the transition from traditional exploration to green and intelligent exploration. By integrating artificial intelligence, big data, and intelligent transmission technologies, and improving traditional drilling processes, the advantages of combined drilling and geophysical prospecting technologies can be effectively leveraged. This can enhance the level of automated and intelligent exploration of shallow geological conditions, providing new technical support for geological disaster prevention, complex condition engineering exploration, and construction. The technical research and engineering practice significance are substantial. Additionally, the paper offers insights and understandings based on drilling-while-prospecting methods, technologies, equipment, and engineering practices to provide a reference for the future development of precise and intelligent geological exploration.
In marine exploration, velocity modeling of complex deep-water salt is an extremely challenging task. On the one hand, complex salt structures exist in a unique environment where seawater coexists with elastic media; on the other hand, the strong amplitude converted waves generated by high-velocity complex salt can affect the accuracy of traditional acoustic velocity modeling. Therefore, it is essential to fully consider these critical factors in order to carry out P- and S-wave velocity waveform inversion modeling for such special structures. Addressing the challenges faced in velocity modeling of complex deep-water salt using towed streamer data, this paper employs a method of boundary coupling between acoustic and elastic wave equations to construct an acoustic-elastic coupled equation (AECE). This equation is more suitable for simulating the propagation process of seismic waves in the overlying seawater elastic media. Through numerical simulations of a three-layered model, we have verified the feasibility of using towed streamer data for S-wave velocity inversion. Subsequently, we derived the waveform inversion gradient operator applicable to the acoustic-elastic coupled equation and established a method for P- and S-wave velocity waveform inversion of complex salt based on towed streamer data. Finally, we validated the applicability and accuracy of this new method through inversion tests conducted on a complex salt media model constructed based on actual overseas geological conditions, as well as through inversion trials using towed streamer data.
Accurate observation system information is the foundation of high-precision seismic data processing. Due to the inability to use conventional GPS positioning for OBN receiver points, specialized technical means are usually required to determine the coordinates of the receiver points. Common secondary positioning methods for receiver points include least squares method, approximate tetrahedron method, search method, fitting surface method, equivalent velocity method, vector synthesis method, etc. However, they are all based on direct wave travel time for positioning. Shallow water OBN data only has direct waves within a small offset distance, making those methods difficult to apply. Another commonly used secondary positioning method is refracted wave secondary positioning, which has low positioning accuracy due to its inability to handle speed gradients, interface bending, and other situations. In response to the problem of inaccurate positioning of receiver points in shallow water environments, this paper proposes a positioning method based on first arrival travel time fitting. Firstly, the first arrival time is accurately picked up from the common receiver point gather. Then, a polynomial is used to fit the relationship curve between the first arrival time and offset. The coordinates of the receiver points are adjusted by the difference between the actual picked travel time and the corresponding value on the curve, and multiple iterations are carried out until convergence. Finally, based on the water depth values measured in the survey, the corresponding Z coordinates can be obtained by projecting the X and Y coordinates of the receiver points, thus obtaining accurate three-dimensional coordinates of the receiver points. The method proposed in this article has been applied to both simulated and actual OBN data, achieving ideal results.
Deep Learning (DL)-based Ground Penetrating Radar (GPR) target recognition methods have been widely applied in geological exploration and infrastructure inspection. However, existing approaches face three main limitations: (1) Most GPR systems operate in single-polarization mode, leading to incomplete acquisition of target scattering information; (2) Traditional deep learning methods risk misclassification when handling B-scan images with similar hyperbolic features from different targets; (3) Direct input of 2D B-scan images into convolutional neural networks incurs high computational overhead. To address these challenges, this paper proposes a multi-polarimetric decomposition fusion method for GPR target recognition based on a lightweight MobileNetV3 network. The proposed method first acquires full-polarimetric GPR data (HH, VH, and VV polarizations) of subsurface targets. Subsequently, H-Alpha decomposition, Freeman decomposition, and Pauli decomposition are performed to extract eight polarimetric parameters characterizing the targets. These parameters are fused into an eight-dimensional feature matrix, which is then fed into a modified MobileNetV3 network integrated with a Squeeze-and-Excitation (SE) attention module for target identification. To verify the effectiveness of the method, four typical targets were classified in the experiments, and the results indicate that using the eight-dimensional feature matrix as the network input can enhance the target classification accuracy. The target classification accuracy can be further improved by incorporating the SE module into the network. Furthermore, compared to conventional ResNet18 and VGG16 networks, the improved MobileNetV3 achieves the highest recognition accuracy (98.75%) while significantly reducing parameter number and model size. The experimental results demonstrate that using an eight-dimensional feature matrix that includes target polarization information as the network input not only provides richer target information but also effectively reduces the redundant information of the input network. This improvement enhances the target classification accuracy while decreasing the matrix size of the input network. Additionally, the lightweight backbone network based on MobileNetV3, integrated with the SE attention mechanism, enhances critical feature extraction capabilities and strengthens discriminative power for target classification. The paper effectively addresses the challenges of insufficient feature discrimination and high computational load in GPR target classification.
ISSN 1004-2903 (Print)
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