Classical travel-time tomography struggles to resolve the heterogeneity within the medium.To address this challenge,this paper proposes a tomography method based on Hamiltonian Monte Carlo(HMC)sampling.In this method,forward modeling utilizes the fast marching method(FMM),governed by the Eikonal equation.For inversion,velocity parameters are expressed as probability distributions,and samples representing these parameters are obtained by employing a Markov chain.This chain is generated from the distributions.The Markov chain is controlled by an artificial Hamiltonian system.In this system,the models are treated as high-dimensional particles.These particles advance through trajectories in the extended phase space.HMC uses the derivatives of the forward equations to enable long-distance transitions between models.This approach enhances sample independence and maintains a high acceptance rate.Results demonstrate that this tomography method can accurately invert the position and shape of velocity anomalies,as well as the heterogeneity in stochastic medium models.This method provides a novel approach for seismic tomography.It can accurately characterize subsurface structures and is valuable for seismic exploration and geophysical studies.

Accurate reconstruction of subsurface structures represents a critical challenge in wave-equation inversion and resource exploration. The Born approximation, which assumes primary dominance, serves as the theoretical foundation for imaging and inversion methods. However, strong multiple reflections violate this assumption, leading to misinterpretation of mid-deep structures and distortion in reservoir assessment. Although the Marchenko multiple elimination (MME) method possesses theoretical advantages, its practical application is constrained by input data requirements such as ultra-high signal-to-noise ratio and ideally source wavelet deconvolution. These limitations stem from MME's purely numerical iteration process, which propagates errors and generates non-causal artifacts when the aforementioned requirements are not perfectly met. Conventional approaches merely adapt to MME's requirements through data preprocessing without addressing the fundamental limitation of its iterative algorithm: the lack of a regional constraint. This study proposes an optimal transport-based Marchenko iterative framework that utilizes the Wasserstein distance as an objective, transforming the originally pointwise numerical correlation-based iteration into a regionally-constrained distribution system. By minimizing the distributional discrepancy between predicted and observed wavefields, our method simultaneously resolves phase and amplitude mismatches, fundamentally suppressing error propagation. Validation using both synthetic and field data demonstrates that the proposed approach significantly enhances the stability, accuracy, and computational efficiency of multiple suppression, providing reliable support for mid-deep imaging and complex reservoir characterization.

Karst formations near the surface in complex geological settings scatter seismic waves, adversely affecting the signal-to-noise ratio (SNR) of seismic data. Accurately characterizing the formation mechanisms of low SNR seismic data is vital for enhancing the efficacy of seismic exploration. This study introduces a composite multi-scale random medium modeling technique that addresses the characteristics of random heterogeneous media in karst regions. The methodology superimposes various random perturbations of different scales in the same area. The elastic wave spectral element method (SEM) is employed to numerically simulate the seismic wave field in complex karst environments. A case study in Guangxi, China, demonstrates that the composite multi-scale random medium modeling approach effectively captures the characteristics of the medium. The simulated data generated using the elastic wave SEM closely resembling actual data. This paper offers insights into the formation mechanisms of low SNR seismic data in complex karst areas. These insights provide valuable references for advancing seismic data processing techniques.

Fast beam migration (FBM), characterized by its super-high efficiency in velocity model building, consists of three main steps: beam forming, beam propagation, and image forming. The super-high efficiency is achieved by beam forming, as it needs only to be performed once for one dataset and is independent of velocity, and the other two steps take relatively little time. However, compared to the beam-propagation and image-forming steps, the beam-forming step is still quite time-consuming owing to the high-dimensional computing problem of estimating the source and receiver slope orientation of a beam. Furthermore, previous methods for estimating the source and receiver slope orientation of a beam struggled to deal with intersecting events, leading to poor imaging results for complex subsurface structures, such as unconformities or faults, where events often intersect. We propose the use of a three-step multimodal optimization method based on the neighborhood crowding differential evolution (NCDE) algorithm to estimate the source and receiver slope orientation of a beam during the beam-forming step, which can quickly and accurately obtain slope orientations when events intersect. We first test the three-step multimodal optimization algorithm on a 3D super-gather and provide the parameter criteria. We then apply the FBM based on the three-step multimodal optimization algorithm to the Marmousi 2 and 3D SEG/EAGE salt models. Both results demonstrate that the proposed method can image intersecting events well and that the imaging quality of complex zones is improved. We also apply the proposed method to a 2D offshore seismic dataset containing abundant intersecting events, which validates the practicality of the proposed method.

In seismic exploration, the multiple suppression is crucial for accurate subsurface imaging and resource identification. Internal multiples, generated by multiple reflections at impedance interfaces, act as interference signals that can mislead resource exploration. Compared to traditional methods, the conventional Marchenko multiple elimination (C-MME) method allows for the direct extraction of primary waves from seismic records without requiring a macro velocity model or predictive subtraction, thereby preserving effective signals. However, challenges, such as low signal-to-noise ratios (SNRs) and high-density sampling requirements, have hindered its application to field land seismic data. To address these challenges of C-MME in field seismic data processing, we propose a compressive sensing-based Marchenko multiple elimination (CS-MME) method, which incorporates efficient denoising, reconstruction, and deconvolution capabilities. In this study, the CS-MME method has demonstrated exceptional performance in processing field land seismic data, successfully overcoming the aforementioned challenges. marking the first successful implementation of Marchenko multiple elimination (MME) on field land data.

Abstract The exploration of urban underground spaces is of great significance to urban planning, geological disaster prevention, resource exploration, and environmental monitoring. However, due to severe interferences, conventional seismic methods cannot adapt to the complex urban environment well. Since adopting the single-node data acquisition method and taking the seismic ambient noise as the signal, the microtremor horizontal to vertical spectral ratio (HVSR) method can effectively avoid the strong interference problems caused by the complex urban environment, which could obtain information such as S-wave velocity and thickness of underground formations by fitting the microtremor HVSR curve. Nevertheless, HVSR curve inversion is a multi-parameter curve fitting process. Conventional inversion methods can easily converge to the local minimum, directly affecting the inversion results’ reliability. Thus, we propose a HVSR inversion method based on the multimodal forest optimization algorithm, which uses the efficient clustering technique and can locate the global optimum quickly. Tests on synthetic data show that the inversion results of the proposed method are consistent with the forward model. Both the adaption and stability to the abnormal layer velocity model are also demonstrated. The results of the real field data are also verified by the drilling information.

In the processing of conventional marine seismic data, seawater is often assumed to have a constant velocity model. However, due to static pressure, temperature difference and other factors, random disturbances may often frequently in seawater bodies. The impact of such disturbances on data processing results is a topic of theoretical research. Since seawater sound velocity is a difficult physical quantity to measure, there is a need for a method that can generate models conforming to seawater characteristics. This article will combine the Munk model and Perlin noise to propose a two-dimensional dynamic seawater sound velocity model generation method, a method that can generate a dynamic, continuous, random seawater sound velocity model with some regularity at large scales. Moreover, the paper discusses the influence of the inhomogeneity characteristics of seawater on wave field propagation and imaging. The results show that the seawater sound velocity model with random disturbance will have a significant influence on the wave field simulation and imaging results.

The exploration of urban underground spaces is of great significance to urban planning,geological disaster prevention,resource exploration and environmental monitoring.However,due to the existing of severe interferences,conventional seismic methods cannot adapt to the complex urban environment well.Since adopting the single-node data acquisition method and taking the seismic ambient noise as the signal,the microtremor horizontal-to-vertical spectral ratio(HVSR)method can effectively avoid the strong interference problems caused by the complex urban environment,which could obtain information such as S-wave velocity and thickness of underground formations by fitting the microtremor HVSR curve.Nevertheless,HVSR curve inversion is a multi-parameter curve fitting process.And conventional inversion methods can easily converge to the local minimum,which will directly affect the reliability of the inversion results.Thus,the authors propose a HVSR inversion method based on the multimodal forest optimization algorithm,which uses the efficient clustering technique and locates the global optimum quickly.Tests on synthetic data show that the inversion results of the proposed method are consistent with the forward model.Both the adaption and stability to the abnormal layer velocity model are demonstrated.The results of the real field data are also verified by the drilling information.

Magma emplacement can restrict the nature and distribution of an ore deposit, and is an important topic for the study of mineralization mechanisms. Previous studies of magma emplacement have focused mainly on the superimposed mineralization of multi-stage magma in time, whereas the superimposed characteristics and mineralization of different magma emplacement in space are unclear. We estimate a 3-D multiple geophysical model in the Shuangjianzishan Ag–Pb–Zn district, northeastern China, using gravity, magnetic, magnetotelluric and seismic data. The model describes the distribution of buried magmatic rocks related to mineralization in the ore district and highlights the detailed structure and connection of volcanism and intrusion. The volcanism is characterized by a tree-like structure consisting of a near-conical channel and an annular fault system; the intrusion appears as a dome-shaped structure, and its lateral distribution is controlled by faults. The geophysical results reveal a deep fault system connecting volcanism and intrusion. Combining the results with regional geology, petrophysical properties and borehole information, we propose a composite metallogenic model for the ore district, which is that the volcanism caused the ore-bearing magma to migrate to the present-day location of the base of the ore deposit through the deep fault system, and formed an intrusive complex with the ore-bearing magma emplaced in a dome below the present-day location of the deposit. This resulted in the formation of complex and fault-controlled ore bodies. Reviewing the global metallogenic characteristics related to magmatism, our results demonstrate the magma emplacement pattern of a composite volcanic-intrusive system may be an important factor for the formation of super-large deposits.

Abstract The numerical simulation and characteristic analysis of VSP seismic data in the complex Loess Plateau area is of great significance to the design of seismic acquisition systems and the velocity modeling in near-surface areas. In this paper, we establish a velocity model of complex Loess Plateau and design three VSP acquisition systems in this model. Then, a finite difference method (FDM) for seismic modeling in the complex topographical condition is used to simulate the VSP data in this model with the above acquisition systems. Finally, based on the analysis to these data, some basic characteristics of VSP data in the complex Loess Plateau area are obtained and their significances to seismic exploration in this area are given.

Surface wave exploration plays a vital role in obtaining target detection information by analyzing and retrieving the dispersion curve of surface waves.Although surface wave exploration technology originated in the 1960s,it has experienced significant advancements in recent decades and has found widespread applications in earthquake disaster and volcanic activity prediction,deep geological structure analysis,engineering construction,mining area and goaf assessment,subsidence area detection,and near-surface structure investigation,including celestial bodies such as stars.This paper aims to provide a comprehensive overview of surface wave exploration technology.It begins by discussing two types of data sources,namely active source and passive source,and proceeds to review the fundamental theory of surface wave exploration based on dispersion curve analysis and observations of horizontal and vertical amplitude ratios.This paper also provides a brief introduction to the surface wave inversion method.Additionally,it highlights the various application domains of surface wave exploration,outlines the current development trend,and presents future prospects for this technology.

Abstract The horizontal layered refined grid is adopted in the conventional finite difference method (FDM) of variable refined grid for the numerical simulation of wave equation. But, the method cannot well adapt to the characteristics of undulated topography and the variation of velocity structure in near-surface region. To solve this problem, a numerical simulation of wave equation using FDM with undulated variable refined grid is proposed in this paper. The grids are generated according to the undulated topography and the spatial distribution of velocity in the near-surface region from low-velocity to the high-velocity layer. For ensuring the accuracy while taking into account the computational efficiency, the FDM with variable coefficient in above grids is used to discretize the acoustic wave equation. The numerical evaluation and example show that the same accuracy as the method using fine grid can be obtained by the new method. However, its computational time is only 43.6% of the one spent by the fine grid. Furthermore, the new method can also stably adapt to the real complex loess plateau near-surface model in a working area of Ordos Basins.

The horizontal layered refined grid is adopted in the conventional finite difference method of variable refined grid for the wave equation based numerical simulation. But the method cannot well adapt to the characteristics of rugged topography and the variation of velocity structure in near-surface region. To solve this problem, a wave equation based numerical simulation using finite difference method with rugged variable refined multigrid is proposed in this paper. This method encrypts the grid based on rugged topography and velocity distribution characteristics of low-velocity layer to high-speed layer near the surface and adopts the variable-coefficient difference schemes in different meshes to discretize the acoustic wave equation, in order to ensure the accuracy of wave field simulation and calculation efficiency. Furthermore, in order to further guarantee the precision of wave field simulation near the surface, the difference schemes in the smallest grids near the earth’s surface are not processed by order reduction. For the wave field of the virtual ghost points above the surface, a normal virtual ghost extrapolation method incorporating free surface boundary conditions is proposed. The numerical evaluation and example show that the algorithm significantly improves the computational efficiency by encrypting the grids in different regions of the velocity model. Taking the actual model of loess plateau as an example, the ratio of time consumption to conventional 1 m×1 m grid is 43.3% and the simulation accuracy is basically consistent with the fine grid, the simulation error is controlled within 10 -12 . The algorithm shows good near-surface scattering suppression and boundary absorption effect, and can stably adapt to the actual complex near-surface media.

Urban areas pose a challenge for the application of the H/V method due to a high degree of artificial noise. The existing methods fall short in reducing the noise of strong interference data. To solve this issue, a new approach called the HVSR curve reconstruction method is introduced in this paper. The method employs the UPEMD technique to analyze the data component, and the extracted signal is evaluated based on the correlation coefficient between the IMFs and the original micro-motion data, trend extraction of micro-motion data, and secondary extraction. This signal is then utilized to retrieve information about the layers, and the effectiveness of the proposed method is demonstrated.

As a sedimentary mineral, most sandstone type uranium deposits are formed in petroliferous basins. Therefore, we can fully tap the residual economic value of historical logging and 3D seismic data measured for oil and gas to search for sandstone type uranium deposits. However, a large amount of acoustic logging data are missing in the target stratum of the uranium reservoir in that it is not the main stratum of oil and gas. A reconstructed method of acoustic logging data based on clustering analysis and with the low-frequency compensation of deterministic inversion is proposed to solve this problem. Secondly, we can use these logging data with seismic data to obtain the 3D inversion data volume representing the sand body of the uranium reservoir based on seismic lithological inversion. Then, we can also delimit the 3D spatial range of sandstone type uranium deposits in petroliferous basins based on the calibration of uranium anomaly and sub-body detection. Finally, a 3D field data example is given to test and analyze the effectiveness of the above research schemes.

The state of sea surface fluctuation has a very important influence on wave field propagation and model space imaging. In conventional marine seismic data acquisition and processing, the sea surface is treated as a horizontal interface. In the actual acquisition of marine seismic data, due to the influence of wind, waves, ocean currents, etc., the sea surface presents a state of high and low fluctuations, so that the reflected waves from the bottom reflection interface will cause strong scattering of the wave field after being reflected by the seawater fluctuation interface, resulting in the reflection of seismic records. The jitter and distortion of the wave event axis will ultimately affect the imaging effect. In order to have a deeper understanding of the influence of the existence of undulating sea surface on wave field propagation and migration imaging, this paper firstly gives dynamic boundary conditions including wave spectrum information based on the small amplitude wave equation of hydrodynamics, starting from the boundary conditions, and then on this basis constructs the undulating sea surface velocity model. On the constructed model, the wave field propagation characteristics were analyzed by freezing the sea surface at different times, and the wave field propagation law of the undulating sea surface at different freezing times and the impact on reflection seismic records and migration imaging were studied. The research results show that, whether it is a simple layered medium model or a complex seabed model with a large water depth, the fluctuations of different sea surface shapes directly affect the wave field record and the wave field snapshot shape, and at the same time have a large impact on the migration imaging results. As the depth of seawater increases. The impact on the simple model gradually becomes smaller, but for the complex model, the effect is still very serious.

The travel-time calculation and characteristic analysis for first arrival in the 3D complex loess plateau area are of great significance to the analysis of the kinematic characteristics for seismic waves, the design of the seismic acquisition system, especially the first arrival picking and tomography inversion. To solve this problem: Firstly, the partition local variable density and unequal distance grid is adopted to divide the velocity model of 3D complex loess plateau; Then, a local travel-time algorithm of bilinear interpolation is established based on Fermat principle and upwind scheme and a modified group marching method is adopted as the scheme of wave-front expansion; Finally, the accuracy and efficiency of the algorithm and the characteristics of first arrival travel-time in the 3D complex loess plateau area are investigated by using the theoretical model. The results show that: We can greatly reduce the computational error caused by the singularity of the source and adapt to the complex seismic geological conditions of the 3D complex loess plateau unconditional stably and flexibly by using the scheme of variable density grid; Compared with the 3D layered uniform model, the travel-time field and time distance curve of seismic first arrival in 3D complex loess plateau area are more complex.

The sea-surface interface between ocean and air is time varying and can be spatially rough as a result of wind, tides, and currents; the shape of this interface changes over time under the influence of wind, tides, etc. As a result, waves impinging on the sea surface are continuously scattered. In the case of marine seismic, the multiple-scattered waves propagate downward into the underwater formation and result in complex seismic responses. To understand the structure of the responses, we have adopted a multistage algorithm for computing the scattered waves at the sea surface. Specifically, we first extrapolate the upgoing incident waves stepwise using thin-slab approximation from the scattering theory based on the De Wolf approximation of the Lippmann-Schwinger equation. Then, we implement the air-water boundary condition at the sea surface. Finally, we use the irregular boundary processing technique to compute the time-varying undulating sea-surface scattered waves from different scattering stages. To overcome the angular limitation of the original parabolic approximation, we introduce a multidirectional parabolic approximation based on computational electromagnetics. Numerical tests indicate that the multistage algorithm presented here can accurately calculate sea-surface scattered waves and should be useful in investigating the structure of marine seismic responses.

高斯束偏移在复杂区域成像潜力巨大,其成像质量和效率受偏移参数和速度模型光滑的影响.基于此,利用理论推导、模型试算进行分析,推导了高斯束偏移的基本原理与模型光滑原理,利用Marmousi模型进行了试算研究.研究结果表明:高斯束偏移成像过程中,浅层成像精度会随最大出射角度增大而提高;射线覆盖完全时,减少傍轴射线数量成像效率提高;高斯窗半宽增加会提高偏移成像精度,但过大则图像失真;随着高斯束半宽减小,成像精度增加,但过小则浅层精度减小;高斯束中心间隔减小则成像精度提高,但成像效率变低;随着速度模型整体光滑次数的增加,成像精度逐渐增加,光滑50次时,偏移成像效果最佳.