Supercritical geothermal can extract more than ten times the energy of conventional Enhanced Geothermal System (EGS), and become the development direction of new energy. Although China has become the country with the largest direct utilization of medium and low temperature geothermal resources, the level of exploration and development of deep underground high temperature geothermal resources needs to be improved. In this paper, we analyze the research progress of high temperature and high pressure physics experiment, numerical simulation, geophysical exploration and monitoring methods for supercritical geothermal, and the rock-fluid-gas geophysical properties of three-phase medium are summarized and analysis. And we give the typical high temperature geothermal area in China for supercritical geothermal resource exploration potential evaluation preliminary discussions, The potential exploration areas of deep supercritical geothermal resources based on geophysical survey results are predicted to provide support for the commercial utilization of supercritical geothermal resources in China.

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°, k_s=20.3, α_{95 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 λ_p=16.8°N, φ_p=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.

High-precision Earth Orientation Parameter (EOP) forecasting, which encompasses parameters such as Polar Motion (PM), universal time, and length of day, is crucial for facilitating the transformation between terrestrial and celestial reference frames in various applications (e.g., satellite autonomous navigation, deep space exploration, and geodynamic research). However, the mainstream predictive methods (including Least squares, numerical decompositions) have serious limitations, such as tail effect, prior periods and poor estimations of model parameters. To improve the accuracy of EOP forecasting (1~360 days), this paper introduces an integrated model combining Singular Spectrum Analysis (SSA), Prony's method, and Autoregressive (AR) models, demonstrated through the case of PM parameter prediction: Firstly, the SSA is used to separate the principal components (e.g., trend, annual, and Chandler terms) and residual components from the original PM observations. Secondly, combined with the Prony method to model and extrapolate these principal components based on complex exponentials functions; and we combine the widely used AR method to predict their residuals. To verify this combined approach, we conduct multiple prediction experiments based on the IERS EOP 20 C04 data. The experimental results showed that the SSA+Prony+AR model effectively captures the time-varying characteristics and significantly mitigates the tail effects of the PM components. Compared with traditional LS+AR models and IERS Bulletin A forecast products, our proposed model exhibits superior performance in medium to long-term polar motion forecasting, particularly reducing forecast errors by nearly 40% in the X direction. These findings can also provide valuable insights into the forecasting of other EOP parameters.

Faults, as one of the main geological structures, are crucial for analyzing subsurface structures and determining oil and gas enrichment areas. Traditional methods face challenges in the efficiency of seismic data feature extraction and the accuracy of fault identification. This article first outlines the background of seismic fault identification and the limitations of traditional methods, and then explores the application of deep learning methods in this field. In deep learning, fault identification is regarded as an image processing task, usually trained in a supervised learning manner. Data, model, and loss function are the three core elements of supervised deep learning. Data is the foundation for training deep learning models, and the quality, diversity, and representativeness of data are crucial for the training and generalization ability of the model; the model can establish a nonlinear expression of the relationship between input and output, used to learn patterns and rules in the data; the loss function is used to quantify the difference between the model's predictions and the true labels, and a good loss function can guide the model towards more accurate optimization continuously. This paper first introduces the training dataset and methods of data fusion and difference optimization, then discusses the effectiveness of different deep learning models such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Transformer models in seismic fault identification, and finally analyzes the impact of different loss functions. This paper summarizes the current performance, advantages, and challenges of deep learning methods in seismic fault identification and provides an outlook on possible future research directions.

Airgun source is an important tool for marine geophysical exploration, the construction of the gun body will be pre-injected into the release of high-pressure air into the water column, resulting in continuous oscillation until the rupture of the bubble, artificially generated energy-controllable seismic sub-wave, acquisition and analysis of sub-wave signals propagated underwater, high-resolution deep-earth exploration, and then complete the important task of oil and gas deposits prospecting and other important tasks. After decades of development, the international theory of airgun seismic source is becoming more and more mature, and a number of airgun seismic source products with excellent performance have been born, but the domestic start in this field is relatively late, and there is still a gap in technology compared with foreign countries, and there is no available domestic airgun seismic source. To address this situation, this paper firstly introduces the development history of airgun vibration source and underwater bubble motion theory, including the types and working principles of the existing mainstream airgun vibration source, introduces in detail the domestic and foreign geological exploration research based on airgun vibration source in recent years, and combines the current situation of airgun vibration source with its limitations, summarizes the current limitations of the development of China's airgun vibration source problems, and the future of the airgun vibration source of marine exploration. It also puts forward the prospect of the difficulties that may be faced in the process of localization of core equipment such as airgun seismic source in the future.

As an important component of Transient Electromagnetic (TEM) prospecting, the performance of a TEM transmitter almost determines the effectiveness of this prospecting method. In order to accurately prospect shallow and even very shallow layers using multi-turn small coils, this paper designs an improved TEM transmitter based on SiC MOSFET. SiC MOSFET is a third-generation semiconductor that offers significant improvements in voltage withstanding, current withstanding, heat dissipation, and response speed compared to widely used Si IGBT. The shut-off time, as a critical parameter of the transmitter, essentially determines the degree of coupling between the primary and secondary field signals. To prevent losing information in even very shallow and relatively shallow layers, the transmitter designed in this paper supports switching transmission between large and small currents. When prospecting in even very shallow or relatively shallow layers, a small current of 1.1 A can be selected, with a shut-off time of only 4 μs. When prospecting in shallow layers, a large current of 16.2 A can be selected, with a shut-off time of 35 μs. To provide transmitting current data use for post-processing, this paper designs a current acquisition system that supports dynamic sampling rate to collect the current waveform in the whole time. When the current waveform is in the rising or falling edge area, the acquisition system automatically selects a high sampling rate of 1.8 MSPS for sampling. When the current waveform is in the steady-state area, the acquisition system automatically selects the lowest sampling rate of 50 KSPS for sampling. Tests show that by sampling with dynamic sampling rate, the acquisition accuracy and data volume can be effectively balanced, thereby ensuring the stability of the storage system. In addition, the transmitter board has a small size of only 255 mm×192 mm, and supports 12 V battery power supply, so it has good portability and can improve field prospecting efficiency to a certain extent.

Well logging identification and quantitative characterization of source rocks are of great significance to hydrocarbon reserves evaluation. There are three types of source rocks in the Jurassic Yangxia Formation of Kuqa Depression: coal measure, dark mudstone and carboniferous mudstone. However, due to the depth of burial (average greater than 4500 m), the source rocks are too mature and affected by deep buried ground stress, the traditional ΔlogR method is difficult to apply. Based on this comprehensive use of geochemical analysis and geophysical logging data, this paper first reveals the geological characteristics of the source rocks of the Jurassic Yangxia Formation, and realizes the qualitative identification of the source rocks of different lithologies through conventional logging crossplot. The results show that the overall maturity of source rocks of Yangxia Formation is high and the quality of source rocks is medium to good. The qualitative identification of source rocks can be realized by the intersection of curves such as GR, AC, DEN, CNC and AC, GR, RT, CNC, DEN curves that are sensitive to the response of the source rock are selected to establish a quantitative prediction model of TOC content by using multi-regression analysis methods and BP artificial intelligence method, and the quantitative evaluation of the single well source rock in the study area is realized. The results are in good agreement with the measured core data. The research results are of guiding significance for comprehensive logging evaluation of deep source rock quality in Kuqa Depression.

Located in the three tectonic domains of the Pacific plate, the Paleo-Asian Ocean and the Tethys, i.e., the northern part is blocked by the southward thrust of the Qinling orogenic belt and the North China block, the western part is pushed by the eastward flow of the uplift material of the Qinghai-Xizang Plateau, and the eastern part is blocked by the Cathaysian block. The eastern and western parts of the Yangtze block have different evolution characteristics. The western part still preserves a relatively stable quasi-craton block centered on the Sichuan continental core, while the eastern Yangtze has been involved in intracontinental orogeny since the early Paleozoic, and different degrees and styles of tectonic deformation have occurred. In this paper, we try to use the aeromagnetic anomaly to directly invert the magnetization vector, and realize the quantitative estimation of the magnetization intensity and magnetization direction in the Yangtze region. On this basis, the magnetic structure and difference of the Precambrian crystalline basement of the Yangtze Block are studied, and the deep structure and state of the orogenic belt within and around the Yangtze Block are analyzed. It is helpful to reconstruct its Precambrian composition and basic tectonic framework, and provides important support for the dynamic problems such as the tectonic relationship between the Yangtze and Cathaysian blocks and the North China plate and the influence of the eastward movement of the Qinghai-Xizang Plateau on it.Traditional magnetization inversion methods usually ignore the remanence and self-demagnetization effects. However, the actual geological conditions are often very complicated. Especially when there is strong remanence, the magnetization direction of the field source usually deviates greatly from the direction of the geomagnetic field. In this paper, the aeromagnetic data of the Yangtze region are collected, and the Direct Analytical Signal (DAS) is calculated by Hilbert transform. The direct analytical signal mode is used as input to invert the magnetization intensity of the region, and the magnetization intensity obtained by DAS mode inversion is used as a constraint. The penalty function is added to the objective function, and the joint objective function under the equivalent constraint condition is established. The inversion of the three components (Mx, My, Mz) of the magnetization intensity vector is realized, and the magnetization intensity vector structure of the Yangtze region is inverted. The magnetic structure of the Sichuan Basin, the Longmenshan tectonic belt and the surrounding area is analyzed.The following progress and understanding have been made: (1)The magnetization intensity of Longmenshan fault zone is different from that of Songpan-Ganzi block and similar to that of Yangtze block, so it is classified as Yangtze block. The northern Sichuan Basin and Hannan-Micang area have high magnetization, and the deep structure is a stable rhombic crystalline basement rock. There are large-scale NE-trending magnetic bodies in the deep underground of the central Sichuan Basin, which may be related to the Archean to Paleoproterozoic basement and the ancient continental nucleus below. The inversion results and the distribution characteristics of magnetic anomalies show that the main body of the Cambrian basement extends from the northern Sichuan Basin to the Micangshan Hannan coverage area.(2)In the negative magnetic anomaly area on the northern margin of the Sichuan Basin, the magnetization direction is opposite to the geomagnetic field, which may be related to the subduction and tectonic deformation of the Qinling orogenic belt. After the collision between the Yangtze plate and the North China plate in the late Late Triassic, the Qinling Mountains experienced a strong intracontinental orogeny, and the deformation expanded from the Qinling Mountains to the northeast of the Sichuan Basin, which may cause the change of magnetization direction.(3)There is a magnetic inversion phenomenon in the Longmenshan tectonic belt, which may be related to the remanence of the Neoproterozoic intrusive rocks. These intrusive rocks were formed in 830-740 Ma, mainly by the underplating of mantle-derived mafic magma. The magnetic minerals in the rock were reversely magnetized during the geomagnetic polarity reversal, and retained this state during the cooling and hardening process, forming an intrusive rock with remanence. In addition, the special tectonic position on both sides of the Longmenshan fault zone, that is, the strong interaction zone between the eastern margin of the Qinghai-Xizang Plateau and the Yangtze block, as well as the push of the eastward flow of the uplift material of the Qinghai-Xizang Plateau and the resistance of the underground rigid block of the Sichuan Basin, led to strong tectonic deformation and magnetization direction changes.

The principle restoration of Zhang Heng's Seismoscope and the realization of its seismic detection function are crucial for the seismological community to recognize and accept Zhang Heng's Seismoscope as a scientific instrument. Pillar and Copper-instrument are the two most critical information in historical literature records. The Pillar must support the Copper-instrument, and the Copper-instrument must be placed on the top of the Pillar, otherwise it cannot be called Pillar; Understanding this relationship of support and positioning leads to the emergence of the principle model of the Seismoscope. The "secondary structure excitation model of primary-secondary structure resonance system" is proposed as the principle model of the Seismoscope. By utilizing the resonance amplification effect of the primary-secondary structures (at least 5.0 times), and the lever amplification effect of the trigger mechanism (at least 4.0 times), a relative displacement amplification of at least 20 times for most seismic motions is achieved, with some amplifications exceeding 50 times. Theoretically, this enables the effective excitation of Zhang Heng's Seismoscope under microseisms (imperceptible to humans). Coupled with an automatic locking system, the Seismoscope achieves an automatic seismic detection function. The primary structure (Ground-Motion) can be simplified as a "cantilever structure with a large concentrated mass at the top and supported at the bottom on a horizontal elastic foundation." The secondary structure (Wind-Observation) consists of 8 pendulums corresponding to 8 directions. Each pendulum is suspended using a "pin", and the pendulum rod is made of copper, serving as a tension-compression rod. This design ensures that the pendulum's swing direction is essentially perpendicular to the axis direction of the pin, allowing for the detection of seismic motion direction. The seismic motion direction measured by the Seismoscope is the one caused by microseisms that initially excites the secondary structure to undergo a significant displacement relative to the primary structure. If the direction aligns with the earthquake-source direction, it may be possible to measure the earthquake-source direction. Due to the significant differences in stiffness and mass between the primary and secondary structures, they can be separated and calculated separately as small-damping ideal linear elastic single-degree-of-freedom systems. The relative displacement of the secondary structure given by this simplified method is slightly smaller than the precise calculation results of the ANSYS finite element model, with a deviation of no more than 10%, indicating that the simplified method has high accuracy and credibility. The relative displacement amplification coefficient of the secondary structure is the primary indicator for whether the seismograph is easy to be excited. The relative displacement amplification coefficient spectrum of the secondary structure is proposed as the basic technical diagram for designing the Seismoscope. A statistical analysis was conducted on the calculation results of 18 sets of far-field seismic records. If requiring the relative displacement amplification coefficient of the secondary structure to be no less than 5.0, it is preliminarily believed that the optimal natural vibration period of the primary-secondary structures ranges from 2.1 s to 2.6 s. The on-site installation and adjusting process to control the natural vibration period range of the primary-secondary structures of the Seismoscope for achieving resonance effects is provided. Further field tests are required to verify its seismic detection function. The principle restoration and instrument design of Zhang Heng's Seismoscope have been preliminarily achieved. Using modern seismic observation results and structural dynamic analysis technology, the principle model of the Seismoscope proposed in this paper conforms to historical records and can achieve the (micro-)seismic detection function

The reserve and production of oil and gas exploration and development in the global sea areas have been steadily increasing. The growth rate of ultra-deepwater oil and gas production has exceeded that of deepwater, making it a strategic replacement area for global oil and gas resources. Offshore oil and gas are a crucial part of China's oil and gas energy. With the advancement of offshore exploration towards deepwater and ultra-deepwater, it is extremely urgent to improve the technical service guarantee capabilities for exploration and well logging in these areas. Due to the special characteristics of the offshore exploration environment, such as complex structures, diverse lithologies, high temperatures and high pressures, there are special and complex requirements for the functions and performance of well logging instruments, and the technical difficulty is extremely high. Most offshore drillings are cluster wells or multi-branched wells, featuring large deviation angles, large displacements or horizontal wells. This requires well logging instruments to have higher operational efficiency and measurement accuracy. This paper sorts out and summarizes the technical bottlenecks and challenges faced by China's deepwater well logging technology and equipment. Combining with the development status, it puts forward development trends and suggestions, aiming to provide technical support for the exploration and development of China's deepwater oil and gas resources.

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.

The spatial and temporal distribution of the palaeomagnetic data of the South China Block is uneven, which limits our understanding of the paleogeography position of the South China Block in the Early Paleozoic. To search for suitable strata for systematic study of paleomagnetism, this study carries out a combined study including petrography, rock magnetism, and magnetic fabric on the mudstone-siltstone of the Cambrian strata from the Zhenba area in the northwestern edge of the South China. The results show that the magnetic minerals of the strata are mainly composed of titanium-bearing hematite or magnetite and magnetic pyrite, while the magnetic fabric is characterized by depositional-weakly deformed magnetic fabric. It is concluded that most of the Cambrian strata in this area have not been tensely modified by tectonic activities, and it is expected to retain the primary magnetic component acquired during deposits, which makes it possible to obtain reliable paleomagnetic data.

The fluxgate sensor is a kind of important equipment to measure the vector magnetic fields. Its working principle is based on the non-linear properties of soft magnetic material. It is used to detect weak magnetic fields. In this paper, we introduce the basic working principle, structure, and main applications of fluxgate sensor. We also discuss the research development of fluxgate sensor, focus on the progress of fluxgate sensor in miniaturization, intelligence, digitization, as well as reducing noise. Some further research directions are also provided.

The Transient Electromagnetic Method (TEM) is a geophysical exploration technique with significant potential for widespread application. Its good adaptability to various terrains and capability for non-invasive detection have made it a mainstream technology in urban underground space surveys in recent years. To enable effective TEM exploration in spatially constrained areas such as urban underground spaces and tunnels, this paper addresses the issues associated with small loop devices, such as high mutual inductance and complex structural design, by designing a transceiver integrated small coil and a matching buffer circuit. Firstly, this paper models the transceiver integrated coil and analyzes it from three aspects: equivalent resistance, inductance, and capacitance. Solutions to these issues are then proposed. To address the resonance problem in the coil, a buffer circuit is designed. Finally, the performance of the coil and its matching buffer circuit is verified using both high and low transmission currents. Testing indicates that even with a transmission magnetic moment of 28.75 Am², the coil's effective resistance, inductance, and capacitance remain very low, measuring 494 mΩ, 1.03 mH, and 260 pF, respectively. Moreover, the coil demonstrates impressive turn-off times, reaching 38 μs and 5 μs for transmission currents of 14 A and 1.2 A, respectively. When the coil is used in conjunction with the buffer module, the system effectively reduces the interference from the primary field response, thereby enhancing the secondary field information. Additionally, since the designed coil device integrates transmission and reception functions and is small in size, it is highly suitable for exploration in spatially constrained areas, significantly improving portability and exploration efficiency.

Interferometric Synthetic Aperture Radar (InSAR), a highly effective technique for surface deformation monitoring, has been extensively employed in applications such as geological disaster monitoring, mining surface damage. Nevertheless, InSAR is limited by its ability to measure only one-dimensional deformation along the satellite's Line-of-Sight (LOS), which restricts its capacity to capture the full complexity of surface movements. This study focuses on Kilauea Volcano and utilizes three sets of Synthetic Aperture Radar (SAR) data acquired from different orbital directions before and after the volcanic eruption, in conjunction with data from several Global Navigation Satellite System (GNSS) monitoring stations. The two-orbit DInSAR observation method is used to calculate vertical and east-west deformations, whereas the three-orbit DInSAR observation method is employed to calculate vertical, east-west, and north-south deformations. The consistency of the vertical deformation and east-west deformation calculated by both methods is tested via the Intraclass Correlation Coefficient (ICC), and the deformation calculation accuracy is validated by monitoring data from two GNSS stations, KAMO and KTPM. To further discuss the computational accuracy of the two-orbit and three-orbit methods, the Probability Integral Method (PIM) is used in conjunction with SAR spatial parameters to simulate LOS deformations in different directions, allowing for 2D/3D deformation accuracy analysis. The experimental results indicate that: (1) the vertical (ICC=0.986) and east-west (ICC=0.989) deformations calculated by the two and three-orbit DInSAR observation methods are highly consistent, with maximum RMSE differences of 0.021 m and 0.013 m, respectively; (2) the absolute errors of the vertical, east-west, and north-south deformations calculated by the three-orbit method compared with the GNSS monitoring data from the KAMO and KTPM stations are relatively small, at 0.04 m, 0.035 m, 0.009 m, and 0.001 m, 0.023 m, and 0.0002 m, respectively; and (3) the simulation experiment reveals that, in the absence of spatial parameter errors, the three-orbit method can accurately calculate three-dimensional deformations; the error in the subsidence calculation using the two-orbit method is about 3% of the maximum subsidence value, and the error in the east-west horizontal movement is about 5% of the maximum horizontal movement value, indicating that the two-orbit method can provide relatively accurate vertical and east-west surface deformation measurements.

An M_S6.2 earthquake struck Jishishan County, Gansu Province, China, on December 18, 2023, leading to a tremendous sand boil and causing more than 150 deaths. As the trigger of the sand boils, the ground shaking during the earthquake attracts extensive concerns. In this study, ground motions of the Jishishan earthquake were reproduced by using a stochastic finite-fault modeling approach and compared with observations. To maintain the far-field received energy independent of subfault size, two improvements were made to the source spectral model. The comparison shows that: Simulated ground motions agree well with observations in terms of the waveform, peak, and duration of the acceleration time histories at reported stations. The response spectra of the observed time series are in general well reproduced by the simulation except for the remarkably large amplitude at certain periods that may result from a site response. Both the simulated and observed PGA are higher than the predictions of the empirical model but remain close to +1 standard deviation. The contour map of the simulated PGA and PGV shows a similar pattern to the observation except for the slight underestimation near the northeast and northwest corners of the study area. The maximum intensity derived from the simulated PGA is degree Ⅺ, which is also consistent with the reported shaking intensity.

Artificial intelligence technology is one of the most important development directions of detailed reservoir description in the future. Detailed reservoir description provides a high-quality platform and foundation for the development and application of artificial intelligence technology. Artificial intelligence also provides a powerful tool and way for the development and progress of fine reservoir description from digitization to intelligence. The research status, advantages and disadvantages of artificial intelligence technology application in fine reservoir description at home and abroad are compared.The application of artificial intelligence technology almost covers all aspects of detailed reservoir description, mainly including fine stratigraphic division and comparison based on analogy learning, fine interpretation of volcanic reservoir structure based on ant colony algorithm, sedimentary microfacies and reservoir configuration division and identification of expert system, fine logging secondary interpretation based on artificial neural network, fine reservoir evaluation based on grey system theory, training image establishment and multi-point geostatistical modeling based on machine learning, knowledge discovery and data mining reservoir flow unit research, fine reservoir description result management platform based on knowledge system, etc. Finally, 10 problems existing in the application of artificial intelligence technology in fine reservoir description and 10 development directions in the future are pointed out.

Reservoir pore structure has an important influence on seepage capacity and oil production capacity. Mercury injection experiment is an important method to study reservoir pore structure, but it cannot be carried out in large quantities due to factors such as limited number of cores, high experiment cost and mercury toxicity. Through the analysis of the mercury injection experiment data, it is found that a series of mercury injection pressure is generally a fixed distribution, and the adjacent mercury injection saturation has a good correlation. As long as a mercury injection saturation of a depth point is predicted, and the entire pseudo capillary pressure curve can be predicted for that depth. XGBoost is adopted to predict the mercury saturation, and then the pore throat radius spectrum is obtained. The rock surface relaxation rate is determined by overlapping the pore-throat radius spectrum of the mercury injection experiment and the T₂ spectrum of the NMR experiment, and the two cut-off values for distinguishing small, medium and large pores on the T₂ spectrum are converted into the two cut-off values of the pore-throat radius spectrum. Using two cut-off values to divide the pore throat radius spectrum into three parts, the pore structure index R_{c_index} is proposed. This parameter has a good correlation with the oil layer production measured by the cable formation tester. It is concluded that the pore structure index R_{c_index} predicted by conventional logging curves can continuously predict reservoir production and guide follow-up measures such as test layers selection.

With its powerful feature extraction ability, deep learning has shown great potential in various fields and provides new ideas for solving various complex problems. Deep learning models often require a large amount of labeled data for training, but in practice, limited logging data are obtained due to cost, resulting in insufficient training samples. Therefore, this paper proposes a CNN-BiLSTM based semi-supervised learning method for seismic wave impedance inversion. The interpolation resampling technique is used to augment the wave impedance, and then a semi-supervised learning strategy is introduced to train the augmented data, and the unlabeled data information is used to improve the generalization ability and performance of the model. The Marmusi-2 model test shows that it can achieve better inversion results with only a small amount of data augmentation, which verifies the effectiveness of the method in the case of small samples.

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.

Ground Penetrating Radar (GPR) is widely used in the fine detection of shallow structures such as urban road disease detection and archaeology, etc. Small-scale underground geological bodies such as cavities and cracks are usually the most concerned detection objects. In general, the energy of hyperbolic diffracted waves generated by small-scale underground geological bodies in the measured GPR profile is weaker than the linear reflected waves generated by the subsurface layered interface, and is easily mixed or masked by the reflected waves with stronger energy, which seriously interferes with the accurate identification and interpretation of small-scale targets. To this end, this paper proposes a multiple singular spectrum analysis method based on k-means clustering algorithm to separate the reflected and diffracted waves in the GPR profile. Then, the k-means clustering algorithm is used to cluster the all singular spectrum, and the singular values in the singular spectrum are divided into k classes according to the similarity, and the several types of singular values representing the reflected wave and the noise are set to zero, and some of the singular values representing the diffracted wave are retained to reconstruct the GPR diffraction wave field. Numerical experiments show that the multiple singular spectrum analysis method based on k-means clustering algorithm can efficiently separate the reflected wave from the diffracted wave. Compared with the reverse time migration of the unseparated GPR data, the imaging resolution of the small-scale geological body is higher and easier to be identified in the separated diffraction wave reverse time migration, which provides a feasible and effective method for the high-precision interpretation of small-scale targets.

The portable frequency domain electromagnetic detection instrument has been widely used in the field of urban near-surface exploration because of its high sensitivity, strong anti-interference ability, simple operation and high measurement efficiency. Due to the smaller scale of urban geological exploration targets, three-dimensional inversion is more advantageous than one-dimensional or two-dimensional inversion in terms of data interpretation accuracy. In order to study the effectiveness of the portable frequency domain electromagnetic detection instrument in urban shallow surface exploration and the superiority of 3D inversion, this paper conducts 3D inversion of GEM-2 measured data from a test site in Shanghai, and compares the results with the traditional 1D inversion results. The excavation results show the correctness of the 3D inversion algorithm proposed in this paper and the feasibility and superiority of its application in urban underground space detection.

The high-frequency mass variations of the atmosphere and oceans have significant impacts on the inversion of time-variable Earth gravity fields using GRACE. This paper comprehensively compares and analyzes the atmospheric and oceanic components, as well as their combination, of the AOD1B RL06 and RL07 products released by GFZ using methods including spectral domain analysis, comparison of low-order terms, spatial analysis, principal component analysis, and inversion of time-variable gravity field models. The results show that the differences between the two sets of products in the spectral domain are relatively small, with the main differences being reflected in the oceanic component. However, the comparison results in the spatial domain indicate significant differences in the equivalent water heights of the oceanic component, reaching the decimeter level. The differences between the 60th order time-variable gravity field models inverted based on RL06 and RL07 are relatively small, with differences in the spectral domain mainly concentrated in medium to high orders. The RMS differences of the KBRR residuals after validation for both sets of time-variable models are less than 3.912 nm/s (correlation coefficient: 0.999). However, the KBRR residuals computed based on RL07 products are generally smaller, demonstrating the slight advantage of RL07 in the inversion of time-variable Earth gravity field models.

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.

In response to the current situation where the acquisition of electrical spectrum parameters of rock and ore mainly relies on indoor observation of samples, and there are few experiments on obtaining electrical spectrum parameters of outcrops in the field, a self-developed measurement device was used to conduct field observation experiments. The device is designed with two switchable signal transmission modes of Stable voltage and current, as well as 8 current output levels ranging from 20 μAto 400 mA. Based on indoor measurement experiments of the standard resistance capacitance network model to ensure the functionality and stability of the device, consistency experiments, spectrum observation comparison experiments, and depth measurement device spectrum observation experiments were conducted using a symmetrical quadrupole device in Daweishan, Liuyang City, Hunan Province to obtain the electrical spectrum parameters of the formation outcrop. The experiment proves that the device can correctly obtain the observed spectrum and obtain the electrical parameters of the underground conductive medium through reasonable analysis of the spectrum. The results indicate that the device has the advantages of simple operation and strong anti-interference ability, providing an independent and practical measurement device for the measurement of the electrical spectrum parameters of geological outcrops. Through reasonable geological interpretation of the observed spectrum, it plays a certain supporting role in related geophysical exploration work and has good application value.

Natural Remanent Magnetization (NRM) of geological samples contains critical records to understand the evolution of geomagnetic fields. Self-Reversed Remanent Magnetization (SRM) refers to the phenomenon that certain magnetic materials acquire a remanent magnetization opposite to the direction of external magnetic field. SRM may occur in various geological settings. Understanding the SRM mechanism is essential for accurately establishing magnetostratigraphy, reconstructing plate tectonics, and interpreting past geomagnetic field variations. However, current researches on SRM in geological samples are mostly case studies, lacking a comprehensive synthesis of existing knowledge. This paper reviews the historical development of SRM research on geological samples, highlighting representative case studies on both natural and synthetic samples. Emphases are laid on features and physical mechanisms of SRM in different geological contexts, outlining the methodologies and techniques used for investigating SRM, and addressing current challenges and knowledge gaps. Future research should utilize interdisciplinary approaches to better understand the microscopic physical mechanisms and to advance the study of SRM.

The soil and groundwater pollution caused by gas station leakage is one of the main types of urban underground pollution. The soil and groundwater pollution caused by gas station leaks is one of the main types of urban underground pollution. In order to achieve this goal, we design a new acquisition method of three-dimensional inter-well resistivity tomography in this paper, evaluate and analyze the ability of this technique to finely characterize and quantitatively evaluate the pollution plume through application examples. The study shows that the monitoring technology designed in this paper has good ability to portray the pollution plume formed by small leakage from gas stations, the boundary of the pollution plume formed by secondary repeated leakage, and the diffusion process of the pollution plume caused by the change of the groundwater level; and the inverted three-dimensional spatial resistivity data of the pollution plume and the oil content-resistivity model can be used to estimate the three-dimensional spatial oil content of the plume and the total leakage volume. Based on the time series inversion of the three-dimensional resistivity data, a leakage level criterion is constructed based on the concept of grading. The research paper plays an important role in promoting the three-dimensional fine characterization technology of underground organic matter pollution plumes.

The Wudalianchi volcanic group is one of the youngest volcanic groups among the Cenozoic ones. As a typical example of intracontinental monogenetic volcano, it is characterized by clusters of small volcanic cones. A 1:5000 high-precision gravity survey is carried out in the western part of Wudalianchi to obtain the fine distribution features of regional magma chambers. This paper introduces the gravity density inversion method constrained by spectrum characteristics to obtain a three-dimensional underground density model of the region, and provides the spatial distribution of magma chambers based on their low-density features. There are three magma structures extending along northeast faults 5~10 km west of the Wudalianchi volcano, which appear as medium-high mountain landforms. There are two large magma chambers below the crater, and a large magma chamber at the depth of 30 km, which effectively supplies the formation of Wudalianchi volcano. Based on the density inversion results of this high-density gravity survey, it is revealed that magma structures exist at different depths in the Wudalianchi volcanic area, and it is proved that there are different stages of magma activities in this area, and that the formation of volcano is closely related to its faults. Such discoveries will provide important basic data for the further studies of the volcano.

Wide Field Electromagnetic Method(WFEM) is an important means of middle and deep mineral exploration. According to the characteristics of WFEM data, a laterally constrainted pseudo-two-dimensional algorithm (SD-WLCI) based on skin depth weighting is proposed in this paper. Through two two-dimensional theoretical models, it is proved that the algorithm can effectively improve the horizontal continuity of deep inversion results in WFEM and improve the resolution of layer interface. In addition, the influences of three regularization factor search methods (linear search method, cooling method and adaptive regularization factor method) on this algorithm are compared in detail. The results show that the linear search method is superior to the other two methods in terms of work efficiency and stability within the comparison range. Finally, this paper applies the skin-depth weighted lateral constraint algorithm to the inversion of wide-field electromagnetic data measured in a mining area of Dongguashan, Tongling. The inversion results are highly consistent with the actual geological conditions, which provides a reliable geophysical basis for the subsequent prediction of middle-deep mineral resources and borehole location. By comparing with the traditional lateral constraint inversion results, The practicability and necessity of this algorithm in the inversion of the measured data of wide-field electromagnetic method are proved.

Accurate identification of deep carbonate microfacies is crucial for reservoir characterization and sweet spot prediction. Deep carbonate reservoirs usually exhibit complex compositions and numerous microfacies types, leading to dramatic challenges and low accuracy in microfacies identification. This study employs conventional logging curves, elemental mud logging curves, and processed mineral interpretation logs from deep carbonate reservoirs as input. A Residual Long Short-Term Memory (ResLSTM) network-based supervised model is developed to establish nonlinear mapping relationships between logging data and carbonate microfacies for intelligent reservoir microfacies identification. The test results demonstrate that: (1) The residual structure incorporated in the ResLSTM network effectively mitigates gradient vanishing and explosion issues during network training. Compared with traditional LSTM networks, the proposed ResLSTM achieves over 10% improvement in prediction accuracy for deep carbonate microfacies. (2) For thin interbedded layers within the reservoir, the ResLSTM model achieves 92.4% microfacies prediction accuracy, demonstrating its strong robustness. These findings highlight the ResLSTM's superior capability in handling the heterogeneity and complex patterns inherent in deep carbonate reservoirs. Furthermore, the tests also demonstrate that the distribution of training data exerts a significant influence on prediction accuracy of ResLSTM. Specifically, in scenarios of input data imbalance, the ResLSTM tends to develop a pronounced predictive bias toward the majority lithofacies categories due to their numerical dominance in the training set. The systemic bias introduced by imbalanced lithofacies distributions presents a critical challenge in petrophysical machine learning applications, demanding urgent methodological innovations to enhance model generalizability across minority facies classes.

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.

Geochemical logging has emerged as a cornerstone in the exploration and evaluation of unconventional oil and gas resources, owing to its ability to provide comprehensive data on reservoir characteristics. This paper aims to present a comprehensive review of the theoretical foundations, technological advancements, and future prospects in this field. Utilizing the Litho Scanner tool as a representative example, this study investigates its high-resolution and high-accuracy capabilities, enabling precise measurements of elemental concentrations, mineral compositions, and Total Organic Carbon (TOC). Recent progress in instrument development, including pulsed neutron sources and advanced scintillation crystals like LaBr₃ and CeBr₃, has significantly improved the reliability and resolution of geochemical logging tools. Additionally, the integration of Artificial Intelligence (AI) and Machine Learning (ML) algorithms has revolutionized data processing methodologies, enhancing mineral quantification efficiency and reducing uncertainty. Case studies demonstrate the successful application of geochemical logging in complex reservoir characterization, highlighting its superiority in evaluating mineralogy, porosity, and hydrocarbon saturation while minimizing reliance on traditional core analyses. This paper also discusses emerging trends, such as the miniaturization and multifunctionality of logging instruments, the development of intelligent detectors, and the increasing use of real-time data analysis through cloud-based platforms. The synthesis between geochemical logging and other advanced logging techniques, such as nuclear magnetic resonance (NMR) and dielectric dispersion, is projected to further enhance reservoir evaluation capabilities. In conclusion, geochemical element logging is poised to play an increasingly critical role in unconventional resource exploration, environmental monitoring, and mineral prospecting. Driven by technological innovation and interdisciplinary integration, its continued evolution is expected to create new opportunities for accurate, cost-effective, and sustainable resource development.

Forensic military geophysics is a new branch of military geophysics in the field of military intelligence reconnaissance and identification with high-resolution measurements of the shallow underground layers of geophysical methods on typical military scenes including of the medium and small-scale battlefield spaces of tactics and combat military activities, which is used to directly verify the geological structure information of the reachable area, so as to infer the geophysical characteristics of the detection targets in the unreachable area by a close analogy of similarity in geological environment, and to solve the problem of effective reconnaissance and identification of geological intelligence evidence in the unfamiliar battlefield environment. A series of geophysical methods mainly include electrical methods, electromagnetic methods, seismic exploration and magnetic methods, which are applied to military scenes of the known battlefield environmental survey and the unknown battlefield intelligence reconnaissance. The key of the application to forensic military geophysical methods is similarity, contrast, rapidity, and non-destructive testing, which extremely could be in accordance with reconnaissance and identification to the physical characteristics of hidden objects as evidence constraints of battlefield environmental intelligence. The three types of typical examples consisting of projectile contact explosion damage effect in battlefield reconnaissance, military vehicle maneuverability in trace identification, and hidden target search underwater indicated that the resistivity method, R-wave survey and Ground Penetrating Radar (GPR) have a good identification effect on the remains evidence from military activities in shallow subsurface. This paper proposes that the multi-method application of forensic military geophysics is suitable to investigate and take the evidence for subsurface geological information of battlefield dynamic change conditions. The combination of geological and geophysical methods can effectively enhance the evidence identification effect. A multifaceted approach to the study of forensic geophysics and military geology will promote the theoretical innovation and practical application of military geophysics.

Lithology forms the foundation for evaluating high-quality reservoirs and is crucial for effective hydrocarbon development. Deep tight sandstone reservoirs are characterized by significant burial depth, complex lithology and strong vertical heterogeneity, leading to challenges for traditional well-log lithology identification. This study focuses on the deep tight sandstone reservoirs of the Jurassic Sangonghe Formation within the Taibei Sag, Turpan-Hami Basin. Integrating core, thin section, laboratory analyses, and conventional well logs through core-log calibration, reservoir lithology was classified into siltstone, fine sandstone, medium sandstone, coarse sandstone, and sandy conglomerate based on median grain size. The results demonstrate that the Sangonghe Formation reservoirs exhibit complex and diverse lithologies, dominated by fine, medium, and coarse sandstones. The primary pore type is intragranular dissolution pores. A machine learning-based lithology prediction model was developed using gamma ray (GR), deep resistivity (RD), shallow resistivity (RS), acoustic transit time (DT), bulk density (DEN), and compensated neutron log (CNL) curves as input features, with median grain size as the prediction label. The model achieved a high coefficient of determination (R²) of 0.897 on the test dataset, showing strong agreement with core-measured data and enabling continuous vertical lithology classification in single well. Application to blind wells confirmed the model's generalization capability and prediction reliability, overcoming limitations imposed by scarce core data on reservoir evaluation. Further coupling analysis of lithology and physical properties reveals that lithology significantly controls reservoir quality, with medium and coarse sandstones exhibiting optimal properties and representing the primary lithology for high-quality reservoir development. This study provides theoretical and technical support for sweet spot prediction and efficient gas reservoir development in tight sandstones of the Sangonghe Formation, Taibei Sag.

With the rapid development of China's economy, the consumption of shallow mineral resources continues to intensify, and the geological exploration work in China continues to advance to deep and complex areas, the exploration of deep geological resources in our country is also confronted with multiple challenges, such as detection depth, anti-interference ability, and measurement accuracy. The demand for deep exploration is also increasing, and the demand for the domestic distributed magnetotelluric acquisition station is becoming increasingly urgent. In this paper, a domestic ultra-wideband distributed acquisition station DMT-V1 for magnetotelluric detection is designed and developed. Combined with LORA autonomous network and 4G networking communication technology, remote real-time data monitoring and remote data download are realized. The developed acquisition station consists of 2 electric field channels and 3 magnetic field channels, and supports low noise fluxgate sensor, long period induction magnetic sensor, magnetic sensor field calibration; MT (Magnetotelluric) and LMT (ultra-long period Magnetotelluric) methods are supported. The AD converter uses a 32-bit high-precision ADC chip CX1282, and is equipped with a low-power hardware processor. Under ARM intermittent operation mode, the power consumption of the acquisition station can be less than 1W@12VDC. Field detection experiments were carried out on this system. Comparative tests with advanced foreign instruments showed that the performance indicators of the DMT-V1 acquisition station generally reached the international advanced level. Field application tests of the DMT-V1 acquisition station were conducted respectively in different regions, and its detection frequency could reach up to 100000 seconds, supports MT and LMT methods, and has the characteristics of high stability, low power consumption, high precision, light weight and portability. The application scope of this equipment covers shallow mineral exploration, deep and ultra-deep oil and gas exploration, and the investigation of the electrical structure of the crust and upper mantle.

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.

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.

Grotto temples are invaluable cultural heritage and crucial physical resources for studying the history of Buddhism and ancient sculptural art in China. However, they are susceptible to natural environmental factors like weathering and erosion, which can lead to the development of joints, fractures, and karst cavities in the rock of the grotto ceilings. These geological issues can cause water leakage and structural instability, threatening the long-term preservation of the caves and their wall sculptures. To tackle these challenges, we employed a combined approach using ground-coupled shielded antennas with center frequencies of 400 MHz and 270 MHz. This method utilizes a grid layout for comprehensive non-destructive detection of concealed geological structures in the ceiling of a specific grotto temple. The collected Ground Penetrating Radar (GPR) data from the grid lines were then analyzed using three-dimensional (3D) visualization techniques. The results reveal that the integrated use of 400 MHz and 270 MHz antennas not only allows for the detailed delineation of geological anomalies, such as lithological interfaces, fractures, and karst cavities within the cave ceilings, but also clearly outlines the topographic relief of the rock mass. Furthermore, the 3D visualization of the GPR data enables viewing and analyzing the 3D radar data volume from various angles and dimensions, providing an intuitive representation of the rock structure, anomalies, and other relevant information. This significantly enhances the efficiency and accuracy of data interpretation. The application of GPR non-destructive detection technology is highly beneficial for analyzing the geological causes and pathways of water leakage in grotto temples. It provides an important basis for water hazard management, cultural relic preservation, and reinforcement efforts.

Amplitude spectrum is one of the most commonly used mathematical quantitative analysis tools in seismic data analysis, and its theoretical basis is the Fourier transform. Through the amplitude spectrum analysis, we can convert the time domain data to the frequency domain to observe and compare the data from the two aspects of amplitude and phase. At present, according to the different calculation methods, the spectral analysis of the time domain signal after the Fourier transform mainly has different forms, such as amplitude spectrum, power spectral density, and noise density. This paper according to the corresponding calculation formula of three frequency spectrum dimensions of the form firstly, and then classify the normalization method commonly used in data analysis, and an analysis was conducted on the amplitude spectra of velocity\acceleration geophone, combination effects, and coupling effects. It is believed that when conducting spectral analysis, the dimensions of spectral analysis should be clearly defined, and then compared to reveal the physical properties of spectral analysis results, clarify the mathematical relationship between data performance and physical background, ensure data quality, and improve exploration effectiveness.

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.