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As one of the main seismic imaging methods, conventional reverse time migration (RTM) may not produce high-quality images in areas with non-flat surfaces and anisotropy because the complex surfaces have a great impact on seismic wave simulation, resulting in strong scattering waves. In addition, in isotropic acoustic (ISO) RTM, the neglection of the anisotropic effects will lead to incorrect travel times during source and receiver wavefield extrapolation. To overcome these problems, we develop a topographic pseudo-acoustic vertical transverse isotropic (VTI) RTM algorithm based on the body-fitted grid. In this method, we first derive anisotropic pseudo-acoustic wave equations in the curvilinear coordinate system. Then, the Lebedev grid finite-difference scheme is used to update these equations to simulate wavefields. Finally, we use the source-normalized cross-correlation imaging condition to realize RTM. Numerical tests are performed to evaluate the feasibility and applicability of the proposed method. The imaging results show that the proposed method can remove the effect of surface topography and anisotropy on seismic wave propagation and improve migration imaging precision.

Located in Douala V (Cameroon), Makepé Missoké is a lowland area that is influenced by the Tongo Bassa and Ngongué rivers. The site has a closed dumpsite, that operated from the 1975’s to 2003 for the disposal and storage of domestic waste produced in Douala. Geoelectric profiling (ERT) coupled with seismo-electric imaging was used to characterize the shallow aquifer of the Douala subbasin and map subsurface pollution. Fourteen geoelectrical profiles were deployed between June and August 2018 and March 2019. Along these lines, 49 sets of seismo-electric point data were collected in December 2021. A total of 118 wells drilled (2018) were used to obtain water level and topographic data. The aquifer geometry, hydraulic characteristics, permeability, lithology and leachate plume extent were determined. This survey enables us to visualize waste infiltration and migration within Makepé. The drilled wells indicate that the main lithologies observed are clay, sandy clay, sand, clayey sand and gravel. The leachate plume observed after processing the electric profiles had a resistivity signature of ≤ 10 Ωm, and high electrical conductivity are observed in some wells. The leachate migrates within the subsurface along a northwest‒southwest trend, where ground water pollution is observed due to leachate infiltration. This infiltration resulted in poor water quality indices in some collected samples. Such pollution is common in unconfined aquifers (< 50 m) due to the absence of a confining layer at the landfill. An increase in resistivity values with depth toward the northeast direction indicates progressive vertical dilution during leachate mineralization. This study integrated geoelectric and seismo-electric tomography with basic water chemistry analysis to effectively characterize the groundwater within the phreatic Quaternary/Mio-Pliocene aquifers of the Douala basin.

The accurate simulation of anisotropic media is critical in seismic imaging and inversion. In recent years, some scholars have dedicated efforts to the study of precise elastic waves in anisotropic media; however, it is easy to separate P-wave and S-wave from elastic wave fields in isotropic media but difficult to separate them in anisotropic media. To address this issue, others have proposed pseudo-pure-wave equations based on the theory of wave-mode separation, but shear wave interference still exists. Therefore, we derived the first-order pure quasi-P-wave equation with no shear wave component in orthorhombic anisotropic media (ORT) which is common in the Earth’s crust and has very important research value. The presence of a pseudodifferential operator in the equation poses a challenge for solving. In order to solve the pure wave equation, we decomposed the original pseudodifferential operator into an elliptic differential operator and a scalar operator, both of which are easily solvable. In addition, we extended the equation from ORT media to tilted ORT (TORT) media. The example results indicate that our pure quasi-P-wave equation can yield a more stable and accurate P-wave field. The pure wave equation we propose can be applied in reverse time migration (RTM), the least squares RTM (LSRTM), and even the full waveform inversion (FWI).

Rain-induced loess landslides are especially prevalent in the Chinese Loess Plateau (CLP). Some became fatal landslide disasters, leading to numerous casualties and significant socioeconomic losses. Extreme precipitation is the main cause of landslide occurrence. Therefore, in this study we discuss the correlation between seven extreme precipitation indices, single continuous precipitation events and fatal landslides in the CLP using Pearson correlation analysis. We also predict future precipitation under climate changes using five optimal CMIP6 models. During the period 2004–2016, fatal landslides in the CLP increased at a rate of 0.6 per year, with frequent landslide events occurring especially in the central and southwestern parts of the CLP. We find that SDII (simple daily intensity precipitation index) and R×5day (max 5-day precipitation amount) show spatial distribution that are consistent with fatal landslides. Extreme precipitation events were frequent after year 2000; and several extreme precipitation indices show an increasing trend with a higher magnitude since 2000 than before 2000. In particular, in 2013 when the number of fatal landslides was as high as 17, SDII, R95pTOT (extremely wet days), R25mm (very heavy precipitation days), and R×5day all showed abrupt increases. Single continuous precipitation events have profound effects on fatal landslides. We show that single continuous precipitation events with cumulative precipitation of 185–235 mm and duration of 6 days or longer have the highest correlation with fatal landslides. As the increasing occurrence of extreme rainfall events by the global warming, the CLP may face more fatal landslides in the future, especially in the high emission scenario of greenhouse gases (GHGs).

The thick Quaternary loess on the Loess Plateau of China produces strong seismic attenuation, resulting in weak reflections from subsurface exploration targets. Accurately simulating seismic wavefield in the Loess Plateau is important for guiding subsequent data processing and interpretation. We present a 2D/3D wavefield simulation method for the Loess Plateau using a viscoacoustic wave equation with explicitly expressed quality factor. To take into account the effect of irregular surface, we utilize a vertically deformed grid to represent the topography, and solve the viscoacoustic wave equation in a regular computational domain that conforms to topographic surface. Grid deformation introduces the partial derivatives such as ∂vx/∂z and ∂vy/∂z in the wave equation, which is difficult to be accurately computed using traditional staggered-grid finite-difference method. To mitigate this issue, a finite-difference scheme based on a fully staggered-grid is adopted to solve the viscoacoustic wave equation. Numerical experiments for a simple layer model and 2D/3D realistic Loess Plateau models demonstrate the feasibility and adaptability of the proposed method. The 3D modeling results show comparable amplitude and waveform characteristics to the field data acquired from the Chinese Loess Plateau, suggesting a good performance of the proposed modeling method.

Variable-grid methods have the potential to save computing costs and memory requirements in forward modeling and least-squares reverse-time migration (LSRTM). However, due to the inherent difficulty of automatic grid discretization, conventional variable-grid methods have not been widely used in industrial production. We propose a variable-grid LSRTM (VG-LSRTM) method based on an adaptive sampling strategy to improve computing efficiency and reduce memory requirements. Based on the mapping relation of two coordinate systems, we derive variable-grid acoustic wave equation and its corresponding Born forward modeling equation. On this basis, we develop a complete VG-LSRTM framework. Numerical experiments on a layered model validate the feasibility of the proposed VG-LSRTM algorithm. LSRTM tests on a modified Marmousi model demonstrate that our method can save computational costs and memory requirements with little accuracy loss.

The identification of karst caves in seismic imaging profiles is a key step for reservoir interpretation, especially for carbonate reservoirs with extensive cavities. In traditional methods, karst caves are usually detected by looking for the string of beadlike reflections (SBRs) in seismic images, which are extremely time-consuming and highly subjective. We propose an end-to-end convolutional neural network (CNN) to automatically and effectively detect karst caves from 2D seismic images. The identification of karst caves is considered as an image recognition problem of labeling a 2D seismic image with ones on caves and zeros elsewhere. The synthetic training data set including the seismic imaging profiles and corresponding labels of karst caves are automatically generated through our self-defined modeling and data augmentation method. Considering the extreme imbalance between the caves (ones) and non-caves (zeros) in the labels, we adopt a class-balanced loss function to maintain good convergence during the training process. The synthetic tests demonstrate the capability and stability of our proposed network, which is capable of detecting the karst caves from the seismic images contaminated with severe random noise. The physical simulation data example also confirms the effectiveness of our method. To overcome the generalization problem of training the neural network with only synthetic data, we introduce the transfer learning strategy and obtain good results on the seismic images of the field data.

Multi-scale strategies such as starting from the low-frequency and early-arrival part of recorded data are commonly used in full waveform inversion (FWI) to maneuver complex nonlinearity. An alternative way is to apply appropriate filtering and conditioning to the misfit gradient in the model domain. In acoustic constant-density media, we prove that velocity and impedance sensitivity kernels are equivalent to applying a high-pass and a low-pass scattering-angle filter to a conventional single-parameter velocity (CSV) kernel. The high-pass scattering-angle filter allows the velocity kernel to include low-wavenumber updates (tomography component). In contrast, the low-pass scattering-angle filter helps the impedance kernel to yield high-wavenumber updates (migration component). The velocity model can be updated using a hybrid gradient of two components combined with appropriate weights. This FWI scheme is able to overcome the potential nonlinearity and partially mitigate the cycle-skipping problem. Numerical examples for the SEG/EAGE overthrust model and the Marmousi model demonstrate that the hybrid gradient facilitates FWI to converge faster to the true model even in cases when conventional CSV-based FWI fails.

With high imaging accuracy, high signal-to-noise ratio, and good amplitude balance, least-squares reverse time migration (LSRTM) is an imaging algorithm suitable for deep high-precision oil and gas exploration. However, the computational costs limit its large-scale industrial application. The difference between traditional reverse time migration (RTM) and LSRTM is whether to eliminate the effect of the Hessian operator or not while solving Hessian matrix explicitly or eliminating the effect of the Hessian matrix implicitly has a very high requirement on computation or storage capacity. We simulate the inverse Hessian by training a cycle-consistent generative adversarial network (cycleGAN) to construct a mapping relationship between the RTM results and the true reflectivity models. The trained network is directly applied to the RTM imaging results, which improves the imaging quality while significantly reducing the calculation time. We select three velocity models and two velocity models respectively to generate the training and validation data sets, where the validation data is not involved in the training process. The prediction results on the validation data sets show that the trained network significantly improves the imaging quality with almost no additional in computational effort. Finally, we apply the network trained with only synthetics to the field data. The predicted results confirm the effectiveness and good generalization of the proposed method.

The ground-based artificial source electromagnetic signal transmitted to space will form a pair of intensity regions over the station and its conjugate point. In order to study the position and intensity of the strongest points in the two regions, the power-spectrum density (PSD) of the electric field on board the Zhangheng-1 satellite (CSES) was selected when it passed over the NWC artificial source transmitting station. The selected frequency is centered at 19.8 kHz with a bandwidth of 200 Hz. The strongest point is defined as the location with the maximum power spectral density of ±10° around the NWC station within 5 days, which is the revisiting period of the CSES. The results show that statistical characteristics of strongest points vary as day/night, local/conjugate point, longitude/latitude, and different components of electric field vectors. In terms of longitude deviation, it is mostly westward offset at night and on both sides in the day over the NWC but opposite at the conjugate point. In terms of latitude deviations, it is equator-ward at night and the same during the day with a smaller deviation. While over the conjugate point, it is northward offset in the day and both at night with a bigger offset. In terms of intensity, it is stable without obvious seasonal changes over the NWC and its conjugate point. The intensity of PSD is higher at night than during the day. For the PSD intensity of the three components, the descending order over the NWC is Ead, Eab, and Ecd at night and Ecd, Ead, and Eab in the day, and the opposite is true for over the conjugate point.

The ultra-deep fault-karst structure discovered in the Tarim Basin in Western China is a fractured-vuggy carbonate reservoir with great potential for development. The diffraction generated by fractures, small-scale caves and vugs is often used for reservoir identification and seismic interpretation. Since the diffraction is much weaker than the reflection, it is difficult to separate the diffraction from the full wavefield. We use a plane-wave destruction (PWD) filter to extract the diffraction from the full data. In order to obtain a high-accuracy and amplitude-preserving imaging profile, we use the least-squares reverse time migration (LSRTM) method to image the separated diffraction. The large amount of calculation is the most challenging problem of the LSRTM algorithm. In view of this, we develop an adaptive sampling strategy to improve computing efficiency and reduce memory requirement. We use a fault model, a vugs-fractures model, and a fault-karst model to demonstrate the effectiveness and practicability of the proposed method. The numerical examples show that the proposed method can enhance the imaging resolution of the fault-karst structure and save computing cost without losing accuracy. In addition, a test on field data processing demonstrates the advantages of our algorithm.

As a parameter that quantitatively measures the shielding effect of the Earth’s magnetic field on energetic particles, the geomagnetic cutoff rigidities will change significantly with the long-term change of geomagnetic field. In this article, by using the numerical simulation method, combined with the variation trend of the Earth’s main field International Geomagnetic Reference Field (IGRF) model and the energetic particles’ windows (EPWs), the variation characteristics of the cutoff rigidities of geomagnetic energetic particles in the vertical direction from 1965 to 2025 were studied. The study found that there is a close relationship between the cutoff latitude corresponding to the cutoff rigidities and the background magnetic field intensity, but they are not in a simple linear relationship. The changes of the cutoff rigidities and geomagnetic field in the northern and southern hemispheres are asymmetric. The weakening of the geomagnetic field will push the cutoff latitudes toward the near equatorial region in the southern hemisphere, but for northern hemisphere the phenomenon is not always credible. In the northern hemisphere, the areas of EPWs will decrease at a relative rate of 0.03%/yr, but in the southern hemisphere, it will increase at a rate of about 0.05%/yr to 0.12%/yr. The long-term trajectory of the positions of the EPWs’ central points do not correspond to geomagnetic poles, nor the magnetic dip poles, relatively speaking, its position is closer to the geomagnetic poles. The study can be used for a long-term forecasting of cutoff rigidities caused by background geomagnetic field variations.

Hainan Island, the largest island in the northwestern South China Sea (SCS), is characterized by many tropical mountainous rivers that flow into the SCS. The geochemistry of these riverine sediments and the factors controlling the weathering intensity are still not well understood. In this study, sedimentary geochemistry has been investigated by using 45 riverine sediments collected from 18 major rivers on Hainan Island. The Hainan riverine sediments are only first-cycle rather than polycyclic sediments, and they faithfully reflect the present weathering intensity. The high and steady values of the Chemical Index of Alteration (CIA) indicate that the riverine sediments at different parts of the Hainan Island have overall undergone intensive chemical weathering. The low values of Weathering Index of Parker (WIP) and high αCa, αK, αSr, and αBa values of north Hainan indicate the highest weathering degree, which is mainly influenced by the flat topography. The values of αNa, αK, αSr, and αBa of southwest Hainan which are higher than those of east Hainan suggest that the leaching of elements such as Na, K, Sr, and Ba is more extreme (i.e., more intensive weathering). These are mainly caused by the different physical denudation due to different summer precipitation. Overall, the Hainan Island is featured by intensive chemical weathering and is classified as a typical transport-limited weathering regime. Therefore, the geochemistry of the riverine sediments of the Hainan Island is different from that of sediments in tectonically active regions (e.g., Taiwan Island).

The abnormal electromagnetic emissions recorded by DEMETER (the Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions) satellite associated with the April 6, 2010 Mw 7.8 northern Sumatra earthquake are examined in this study. The variations of wave intensities recorded through revisiting orbits from August 2009 to May 2010 indicate that some abnormal enhancements at Extremely Low Frequency range of 300–800 Hz occurred from 10 to 3 days before the main shock, while they remained a relatively smooth trend during the quiet seismic activity times. The perturbation amplitudes relative to the background map which were built by using the same-time seasonal window (February 1 to April 30) data from 2008 to 2010 further suggest strong enhancements of wave intensities during the period prior to the earthquake. We further computed the wave propagation parameters for the electromagnetic field waveform data by using the Singular Value Decomposition method, and results show that there are certain portions of the Extremely Low Frequency emissions obliquely propagating upward from the Earth toward outer space direction at 10 and 6 days before the main shock. The potential energy variation of acoustic-gravity wave suggests the possible existence of acoustic-gravity wave stability with wavelengths roughly varying from 5.5 to 9.5 km in the atmosphere at the time of the main shock. In this study, we comprehensively investigated the link between the electromagnetic emissions and the earthquake activity through a convincing observational analysis, and preliminarily explored the seismic-ionospheric disturbance coupling mechanism, which is still not fully understood at present by the scientific community.