Complex Geological Structures Research Articles

Three-Dimensional Inversion of Long-Offset Transient Electromagnetic Method over Topography

The long-offset transient electromagnetic method (LOTEM) is widely employed in geophysical exploration, including environmental investigation, mineral exploration, and geothermal resource exploration. However, most interpretations of LOTEM data assume a flat Earth, and the commonly used one-dimensional (1D) interpretation encounters significant challenges in achieving reliable geological interpretations when topography is ignored. To address these challenges, this study presents an effective three-dimensional (3D) LOTEM inversion method. In this study, we discretize the simulation domain using unstructured tetrahedra to accurately simulate complex geological structures. The finite-element time-domain (FETD) method is utilized to calculate the LOTEM forward responses, and the limited-memory BFGS (L-BFGS) optimization method is employed for 3D LOTEM inversion. To avoid explicit calculation of sensitivity, we obtain the product of the transposed sensitivity matrix and the vector through adjoint forward modeling. Several synthetic models are used to verify the developed program, and the influence of topography on LOTEM inversion is examined. The numerical results demonstrate that topography can significantly impact the inversion result, potentially leading to incorrect geological interpretations. Finally, the developed inversion algorithm is applied to a realistic ore model from Voisey’s Bay, Labrador, Canada. The 3D inversion successfully reconstructs the spatial distribution of the ore body, further confirming the effectiveness of the developed algorithm.

Visualization facilitates uncertainty evaluation of multiple-point geostatistical stochastic simulation

Stochastic simulation is an essential method for modeling complex geological structures in geosciences. Evaluating the uncertainty of the realizations of stochastic simulations can better describe real phenomena. However, uncertainty evaluation of stochastic simulation methods remains a challenge due to the limited data from geological surveys and the uncertainty in reliability estimation with stochastic simulation models. In addition, understanding the sensitivity of the parameters in stochastic simulation models is invaluable when exploring the parameters with a higher influence on the uncertainty associated with predictions generated from stochastic simulation. To facilitate uncertainty evaluation in stochastic simulation methods, we use the circular treemap as an interactive workflow to explore prediction uncertainty in and the parameter sensitivity of multiple-point geostatistical (MPS) stochastic simulation methods. In this work, we present a novel visualization framework for assessing the uncertainty in MPS stochastic simulation methods and exploring the parameter sensitivity of the MPS methods. We present a new indicator to integrate multiple metrics that characterize geospatial features and visualize these metrics to assist domain experts in making decisions. Parallel coordinates-scatter matrix plots and multi-dimensional scaling (MDS) plots are used to analyze the parametric sensitivity of MPS stochastic simulation methods. The realizations and parameters of two MPS stochastic simulation methods are used to test the applicability of the proposed visualization workflow and the visualization methods. The results demonstrate that our workflow and the visualization methods can assist experts in finding the model with less uncertainty and improve the efficiency of parameter adjustment using different MPS stochastic simulation methods.

Seismic spatially variant noise suppression method in the Tarim Basin based on FFDNet and transfer learning

Due to a complex geologic structure and ultradeep reservoir location, noise distribution of prestack seismic data in the Tarim Basin is nonuniform. However, most of the current seismic random noise suppression methods lack the flexibility to deal with spatially variant random noise. To address this issue, we have developed an intelligent denoising method for seismic spatially variant random noise and applied it in the Tarim Basin. On the basis of denoising convolutional neural network (DnCNN), we add an extra channel to the input and introduce a tunable noise level map as input. The noise level map has the same dimensions as the input noisy seismic data, and each element in the noise level map corresponds to a denoising level. By adjusting the noise level map, a single model can handle noise with different levels as well as spatially variant noise. Due to the lack of labeled field data in the Tarim Basin, we introduce a transfer learning scheme that transfers features of effective signals learned from synthetic data to the denoiser for field data. The network learns the general and invariant features of an effective signal from a large number of easily obtained synthetic data and then learns the real effective signal characteristics from a small amount of approximately clean field data in the target area by fine-tuning. The processing results of synthetic and field data demonstrate that, compared with f- x deconvolution, dictionary learning, and DnCNN, our method exhibits high effectiveness in suppressing spatially variant random noise and preserves effective signals better.

DGM-MDS: Dynamic grouting monitoring with a novel multi-channel distributed system

With the development of engineering construction, the construction of underground space with complex geological structures is increasing, resulting in more potential engineering problems (e.g., water inrush). Grouting, as a technology for prevention and control, has been widely used in engineering applications such as tunnel construction and pile foundation engineering. To the best of our knowledge, a trenchless visualization method, which can effectively control and evaluate grouting fluid filling of underground space for energy saving, environmental protection and reliable construction quality, is underexplored today. To this end, a novel distributed wireless sensor network-based solution is proposed in this paper. Specifically, metal electrodes are first inserted into the ground in the grouting area to collect data from underground space during the grouting process. Then, by leveraging resistivity inversion imaging software, an effective dynamic monitoring can be achieved so that the grouting effect can be evaluated accurately by observing the grouting diffusion, filling range and evolution process in the underground. Finally, the proposed distributed system can collect multiple profile data in quasi real-time by flexible wireless networking mode, leading to comprehensive and effective monitoring of underground filling for grouting engineering. Experiments on lossy clay area show the effectiveness of our proposed distributed system for engineering monitoring in the field of grouting.

Influence of dikes in a rock mass on the stability of a mine working under the action of a gravitational-tectonic stress field

The purpose of the research – to analyse the effect of a complex lithological structure on the stability of mine workings. The relevance of the work. The need to take into account complex geological structure is one of the most important factors affecting the stability of rock outcrops. By this we mean the lithological structure and the presence of lithological heterogeneities. The difference in physical and mechanical, and particularly deformation properties, between lithologic alterations and host rocks can lead to unfavorable rock pressure conditions during excavation and operation. The research’s methods. In this work, we study rock mass behavior in the presence of lithologic inhomogeneities with different characteristics using spatial numerical models. Using geological data and rating techniques, the transition from physical and mechanical properties of the sample to the properties of the massif is done. The results of the work and its area of application. The work provides an overview of the occurrence of lithological heterogeneities, and of lithology as a factor influencing the stability of mine workings. Moreover, numerical models with different physical and mechanical properties of dikes were built and analyzed and the actual section of the mine workings underlain by a monkeit dike was taken for the analysis of the influence of lithological differences on the stability of mine workings. Conclusion. The simplification and idealization of massif as a continuous medium leads to loopholes in stress- strain state of massif.

Forward modeling of direct-current resistivity data on unstructured grids using an adaptive mimetic finite-difference method

An effective solver for the direct-current (DC) resistivity forward-modeling problem should be capable of accommodating arbitrary electrode layouts, adapting the mesh to topography and complex geologic structures, and adaptively refining the mesh to ensure high solution accuracy. We use the capability of the mimetic finite-difference method in naturally accommodating meshes with nonconforming elements to develop adaptive and parallel cell-based (CB) and vertex-based (VB) mimetic schemes for the forward modeling of DC resistivity data on unstructured meshes. A diffusion problem in mixed form and Poisson’s problem are solved in the CB and VB schemes, respectively. The mesh adaptivity involves an iterative h-refinement conducted by a regular subdivision of the marked elements together with a 2-irregularity condition. Goal-oriented residual- and gradient-based error estimators are used to mark the elements for refinement in the CB and VB schemes, respectively. To evaluate the accuracy and efficiency of the mimetic schemes, we use two benchmark models with analytical solutions and standard linear and quadratic finite-element solutions. The numerical results for apparent resistivity from both mimetic schemes accurately approximate the reference analytical and numerical values. Furthermore, on similar meshes, the VB mimetic scheme is found to be less demanding than the CB method in terms of computational resource requirement. We also develop a grid-based mesh generation technique based on the body-centered cubic lattice to generate high-quality initial meshes. Using benchmark examples, we validate this mesh generation method and demonstrate its versatility by discretizing a model of a thin dike where a standard Delaunay mesh generator fails to generate a mesh. Moreover, we display the effectiveness of the presented mimetic approach and the grid-based mesh generation technique using a realistic example with topography and parallelization over a large number of sources.

Evaluation of the nature of saturation of the reservoirs of the achimov formation by well-logging in conditions of low permeability and facies heterogeneity

Despite the fact that the history of studying the geology of the achimov formation spans several decades, the volume of depletion of the reserves of these deposits is small, and the number of fields where the achimov formations have been put into commercial development is few. This is due to the complex geological structure of the reservoirs, vertical and lateral heterogeneity, reduced porosity and permeability properties, and low values of the oil saturation factor. In the presented work, a generalization and analysis of all petrophysical information was made, typification of sections according to well logging with the possibility of using individual petrophysical function to assess the nature of reservoir saturation and the hydrocarbon saturation index. To create a petrophysical substantiation of well logging interpretation, both historical and current core studies in the framework of this study by the authors of the article were involved. The typification of the sections of the achimov formation was carried out on the basis of a detailed lithological study of the core using special studies such as scanning electron microscopy and computed microtomography. Identification of different types of section will allow in the future to correct the further hydrodynamic model for predicting the nature of the inflow and will significantly increase the reliability of assessing the nature of saturation and the hydrocarbon saturation index of heterogeneous deposits of the achimov formation.

IMPROVEMENT OF THE METHODOLOGY FOR MODELING THE PERMEABILITY CUBE TAKING INTO ACCOUNT THE HETEROGENEITY OF THE STRUCTURE OF THE PORE SPACE OF THE PAY ZONES OF THE SOUTH TATAR ARCH

This article analyzed the results of laboratory studies of the core of the terrigenous Devonian of one of the oil fields of the South Tatar Arch. It is shown that the studied productive deposits have a complex geological structure. Therefore, when constructing a three-dimensional geological-hydrodynamic model, it was proposed to use the FZI parameter and the coefficients of relative and volumetric clay content. Based on the FZI parameter, four conditional groups of reservoirs characterized by certain ranges of changes in geological properties were identified within the studied productive deposits. Further, for each conditional group of reservoirs, an independent correlation of permeability and porosity coefficients was built. To use the results of detailed geological structure, this article proposes a new methodology for modeling the permeability cube, taking into account the heterogeneity of the structure of the pore space and the distribution of relative shale. The results of the permeability cube according to the proposed method are compared with the results of the permeability cube according to the traditional method. This comparison showed that using the proposed new method, not only the distribution of the permeability coefficient within the studied volume was clarified, but also the average value increased from 253.6 to 421.9 mD. It has been shown that using a new method of modeling the permeability cube, there is a better convergence with the historical data on the development of the object under study. Based on the results of the adaptation of the 3D hydrodynamic model, a detailed analysis of the current state of development and development of reserves as of the date of study was carried out. It was noted that the use of this new method makes it possible to increase the reliability of the forecast and estimate of the distribution of residual mobile oil reserves in threedimensional geological and hydrodynamic modeling.

3D Airborne EM Forward Modeling Based on Finite-Element Method with Goal-Oriented Adaptive Octree Mesh

The finite-element (FE) method for three-dimensional (3D) airborne electromagnetic (AEM) modeling can flexibly simulate complex geological structures at high accuracy. However, it has low efficiency and high computational requirements. To solve these problems, one needs to generate meshes more reasonably. In view of this, we develop an adaptive octree meshing scheme for frequency-domain AEM modeling. The octree meshes have the characteristics of regularity and flexibility, while the adaptive algorithm can effectively refine the mesh locally. In our adaptive mesh generation, the posterior errors and weighted coefficients are used to construct the final weighted posterior errors. We verify the accuracy of our method by comparing its results with semi-analytical solutions for a half-space model. Furthermore, we use the spectral-element (SE) method and our method to calculate EM responses for an abnormal block model and compare their computational costs. The results show that our adaptive scheme has obviously technical advantages over SE method for AEM modeling with multiple frequencies and multiple survey stations. Finally, we calculate a model with complex geological structures to verify the feasibility of our algorithm in complex geological circumstances.

Seismic characterization of geologically complex geothermal reservoirs by combining structure-oriented filtering and attributes analysis

In geothermal systems, the geologic structure is a decisive factor in controlling fluid flow. Several geothermal systems around the world are located in complex geological structures, such as closely spaced and intersecting faults and fractures, folds, and dykes. Seismic data provides high-resolution images of complex structures that can be used to explore geothermal reservoirs. In fact, faults and fractures have subtle geologic edges that produce significant lateral variations in seismic data. Volumetric seismic attributes are quite effective for detecting these discontinuities in seismic data but are sensitive to noise and velocity accuracy. In North China, a deeply buried carbonate structure presents a geologically complex system with fault-controlled geothermal circulation. However, due to the deep burial depth and structural complexity, seismic reflection beneath the buried-hill has a low-quality, making it difficult to detect the characteristics of the fault edges. In this study, we first develop a structural architecture of the buried-hill carbonate reservoirs to show the development characteristics in vertical and plane directions. Next, we propose an intelligent workflow based on structure-oriented filtering and sensitive seismic attributes to investigate structural complexity (faults and fractures) in the basin for geothermal reservoir exploration. The results show that by combining the proposed structure-oriented filtering and sensitive volumetric seismic attributes, we can generate high-resolution seismic images to characterize fault edges, geometries, and fracture anomalies in structurally complex settings in order to identify upflow locations along the faults and fractures in geothermal systems. We further validated the fracture networks distribution by superimposing the extracted attributes with seismic fault networks and fracture density map using multilayer feedforward neural network. This workflow provides a reliable basis for the characterization of geothermal reservoirs in deep-buried and structurally controlled geothermal fields.

A Set of Geophysical Fields for Modeling of the Lithosphere Structure and Dynamics in the Russian Arctic Zone

This paper presents a set of various geological and geophysical data for the Arctic zone, including some detailed models for the eastern part of the Russian Arctic zone. This hard-to-access territory has a complex geological structure, which is poorly studied by direct geophysical methods. Therefore, these data can be used in an integrative analysis for different purposes. These are the gravity field, heat flow, and various seismic tomography models. The gravity field data include several reductions calculated during our preceding studies, which are more appropriate for the study of the Earth’s interiors than the initial free air anomalies. Specifically, these are the Bouguer, isostatic, and decompensative gravity anomalies. A surface heat flow map included in the dataset is based on a joint inversion of multiple geophysical data constrained by the observations from the International Heat Flow Commission catalog. Available seismic tomography models were analyzed to select the best one for further investigation. We provide the models for the sedimentary cover and the Moho depth, which are significantly improved compared to the existing ones. The database provides a basis for qualitative and quantitative analysis of the region.

Index active tectonic relative of Karangsambung geopark area, Central Java, Indonesia: assessment for developing geological disaster-based areas

Karangsambung as a “subduction fossil” of the Cretaceous-Paleocene on the island of Java, has a complex geological structure. The current subduction process in the south of Java with a north-south compression force has contributed to the reactivation of the geological structure in Karangsambung. The index active tectonic relative (IAT) of the Karangsambung area reflects the current level of tectonic activity. IAT is obtained from quantitative calculations of geomorphic indices, including streams length - gradients index (Sl), the ratio of valley floor width to valley height (Vf), basin asymmetry (Af), basin shape (Bs). mountain front sinuosity (Smf), the hypsometric integral (HI), and drainage density (Dd). The index active tectonic relative (IAT) calculation with an average IAT value of 2.37 indicates that tectonic activity is in the medium/moderate category. In addition, an attempt was made to compare the regional neotectonic activity with the relative tectonic activity of the study area. Based on this geomorphic analysis, the study area may have a lower seismic risk but needs to be evaluated more carefully for regional seismic hazards. The IAT value can be used as an initial reference for geological disaster assessment, especially earthquakes hazard in the development of the Karangsambung National Geopark Area.

Using Wide-Angle Reflection Wave Technology to Detect Seismic Inversion Data of Complex Geological Structure Zone for a Future Smart World

Abstract The South Yellow Sea has complex geological conditions such as small seismic wave impedance differences between shallow and deep marine sedimentary formations. The energy of the reflection wave in the deep phase is weak at the same phase axis, making it difficult to identify the effective reflection information of the marine target layer, especially the deep parts covered by high-speed layers. It is extremely difficult to image the carbonate stratum of the Mesozoic and Paleozoic. For this reason, wide-angle reflection wave technology is used to detect seismic inversion data of complex geological structures. According to the comparative analysis of the actual seismic data and inversion simulation data in the South Yellow Sea area, it is verified that under the condition of complex geological structure, with the aid of inversion simulation data, effective waves and interference waves can be identified, which can guide the optimization of acquisition parameters in the deep target formation area of the South Yellow Sea, where imaging is difficult, in view of the factors affecting the imaging accuracy of the marine carbonate formation of the middle and Paleozoic, and this is conducive to improving the acquisition parameter quality of seismic data.

Reprocessing 2-D airgun seismic reflection data SALTFLU (salt deformation and sub-salt fluid circulation in the Algero-Balearic abyssal plain) in the Balearic promontory and the Algerian basin

In an ever more challenging context for the acquisition of seismic data in the Mediterranean Sea, reprocessing to improve the quality of legacy data has become increasingly important. This work presents the newly reprocessed, open access dataset SALTFLU acquired in the Algerian basin by the National Institute of Oceanography and Applied Geophysics (OGS) in 2012. We apply a ‘broadband’ reprocessing strategy adapted for offset-limited (3 km streamer for a target 4 km below the sea level) airgun reflection seismic data acquired in deep water settings. We then assess if the reprocessed images provide new geological insights on the Mediterranean sub-surface. The workflow relies on an integrated approach combining geophysics and geological interpretation to iteratively build the velocity model. In this way we aim to tackle some of the challenges linked to imaging deep complex geological structures containing high velocity contrasts with 2-D, offset-limited seismic data. We first broaden the bandwidth of the data through multi-domain de-noising, deghosting and a source designature using an operator derived from the seabed reflection. We then perform iterative migration velocity analysis, pre-stack time migration and multiple attenuation in the Radon domain to obtain time-migrated images. The initial velocity model is derived from the resulting time migration velocities, and geologically driven model updates are generated using a combination of travel-time tomography, seismic interpretation of the major salt horizons and velocity gradient flooding. The gradient flooding aims to reproduce the large scale first-order velocity variations, while the travel-time tomography aims to resolve the smaller second-order velocity variations. The results improve our deep geological knowledge of the under-explored Algerian basin down to the base salt and the pre-salt. Fluid indicators are imaged within the Plio-Quaternary of the Algerian basin, which we interpret as thermogenic or biogenic gas sourced from either the Messinian Upper Unit or from the pre-salt, migrating through a hydro-fractured salt. The reprocessed data image lateral and vertical seismic facies variation within the Messinian units that could shed new light on the tectono-stratigraphic processes acting during the Messinian Salinity Crisis. It also reveals numerous previously unresolved volcanic structures within the Formentera basin.

3D convolutional neural Network-based 3D mineral prospectivity modeling for targeting concealed mineralization within Chating area, middle-lower Yangtze River metallogenic Belt, China

The Chating area is situated within the Middle-Lower Yangtze River Metallogenic Belt, China. Several concealed skarn and porphyry-type deposits have been discovered in this area, indicating high potential for hosting hydrothermal deposits. However, due to the complex geological structure, exploration risks significantly increase with increasing depth. To overcome this challenge, three-dimensional mineral prospectivity modeling (3DMPM) has begun to be widely applied for mapping the prospectivity of deep-seated and concealed mineralization. However, most previous studies on 3DMPM were based on shallow supervised machine learning models and dimensionality-reduced 3D predictive maps. Although these models have shown good results, they may lose spatial correlation within the 3D predictive maps and fail to explore nonlinear correlations between the 3D predictive maps and mineralization. Meanwhile, 3D geological models are the most important basis of the 3DMPM, however, in the past, few studies have incorporated the optimization of the 3D geological models into the process of 3DMPM. Therefore, this paper initially builds and optimizes 3D geological models through implicit 3D geological modeling and “total litho-inversion” approach. Subsequently, the 3D predictive maps are generated by employing various 3D methods, which are further integrated using a 3D convolutional neural network (3D CNN) model to identify highly prospective areas for mineralization. The results show that the highly prospective areas identified by the 3DMPM include not only the training data but also other mineral deposits that have previously been discovered within the study area. In addition, compared with the Logistic Regression model (LR), Support Vector Machines (SVM), and Radom Forest (RF), the 3D CNN performs better prediction capabilities due to its enhanced ability to capture the correlations between 3D predictive maps and multiple types of mineral deposits. It suggests that the 3DMPM based on the 3D CNN model has commendable predictive capabilities in identifying prospective mineralization areas, and some new highly prospective areas can be considered as priority areas for future exploration of concealed mineralization within the Chating Area.

Geological Structure Control of The Distribution Quartz Vein as Mineralization Pathway In Kawatuna Area, Palu City Indonesia

The Kawatuna area has a complex geological structure condition and is estimated to be a weak zone for hydrothermal solutions to rise and then accumulate into deposits in the form of veins. Based on this, it makes this area interesting to study. This study aims to determine the condition of the geological structure and its influence on the condition of the distribution of veins in the study area. The method used is surface geological mapping and geological structures analysis. Based on surface geological mapping, it was found that the study area was composed of schist rock units, gneiss, granodiorite, and molasses units. The geological structure that developed in the study area consisted of shear joints in the form of systematic and non-systematic shear joints and shear faults. The distribution of quartz veins in the study area has a general direction of northwest-southeast and northeast-southwest. The presence of mineralization in the form of quartz veins in the study area is strongly controlled by the presence of geological structures that form an oblique convergence fault model that shows a dilatational movement force. The deposit opening system formed in the study area is a jog deposit system in which pull-apart basin fracture arrays develop which are characterized by the presence of tension fractures/veins.

Special Characteristics and Stability Analysis of Bank Slope Deposits with Special Geotechnical Structures in High and Cold Valleys

Due to the special internal and external dynamic action of the Qinghai-Tibet Plateau, the high and cold valleys are typically characterized by high-steep terrain, dry and cold climate, lithologic diversity, complex geological structure, and frequent occurrence of earthquakes. In this study, the types of special geotechnical structures of bank slope deposits in high and cold valleys are summarized based on field investigation, field and laboratory tests, and numerical simulation. These special deposits include colluvial-deluvial deposits, terrace deposits, early debris flow deposits, and landslide deposits. The formation mechanism, physical and mechanical properties, and stability analysis of these deposits were studied. The results show that the formation mechanism of various deposits is different, which is closely related to the intense geological tectonic action, the weathering and unloading action intensified by freezing and thawing cycles, and the special rock and soil structure in the high and cold valleys. Different material compositions have obvious effects on the physical and mechanical properties of the deposits, thus affecting the stability and deformation characteristics of the deposits. Under natural and saturated conditions, the stability of different types of the deposits is different, which is mainly related to the special geotechnical structure of various deposits. Compared with that before the reservoir impoundment, the stability factor of various deposits after the reservoir impoundment is significantly reduced. The performances can be provided as a reference for evaluating the stability of bank slope deposits in high and cold valleys.

Прямые методы моделирования движения автотранспорта в окрестности подкрепленного склона

The dynamic impact of moving vehicles can cause effects leading to landslide processes in slopes. Even insignificant displacements and speeds lead to a relative displacement of the layers. In this case, the physical and mechanical parameters of the soils that make up the slope can change significantly. For example, the decrease in adhesion C may be analogous to the decrease in the force of static friction by the transition to sliding friction. This is due to the fact that the mutual movement leads to slippage of small soil fragments relative to each other. The influence of vehicles on possible landslide processes increases with an obvious tendency to increase the speed and mass of the rolling stock. This, as well as the complex geological structure of the slopes and the need to take into account the reinforcing structures, leads to the need to build refined mechanical and mathematical models for the joint operation of road structures, the slope and the reinforcing structures in a dynamic formulation.
 The creation of a refined model of the slope geometry, the highway and the slope reinforcement structures are today solved mainly by the finite element method (FEM). The problem of constructing a numerical solution of such problems based on direct methods of integrating the equations of motion is topical. In this case, it is necessary to take into account the change in the distribution of masses when moving vehicles along the road at different speeds.
 In any of works of the author [1-6], an explicit absolutely stable scheme for integrating the equations of motion of the FEM was used to solve this problem.
 This article considers testing of the method by comparing numerical solutions with known ones for problems that are simpler in terms of topological structure. Namely, the comparison of the method with the solutions of the classical problem "movement of a massive load along a massive beam" was carried out. V.V. Bolotin's solution [7-9] was adopted as a "reference" one. Numerical solutions showed a high degree of convergence of results by the proposed and "reference" methods.

Reconstructing Three-dimensional geological structures by the Multiple-point statistics method coupled with a deep neural network: A case study of a metro station in Guangzhou, China

A credible large-scale three-dimensional (3D) geological model constructed from a small amount of local high-density data provides a vital data infrastructure for the design and construction of metro lines. The multiple-point statistics (MPS) method has successfully generated 3D geological models in many fields. However, the global cognition of the spatial relations between geological objects is difficult to reconstruct using a local optimization strategy with moving templates in the MPS simulation. This study presented an MPS simulation approach for constructing 3D geological structures with two-dimensional (2D) cross-sections, where the MPS process was coupled with a fully connected deep neural network (FCDNN) simulation. The core idea of the proposed method was that the global features of each geological object were generated from the trained FCDNN, the input parameter of which was the subsurface depth. Then, the entire model was constructed on the initial model using the following iterative MPS process: the semantic relationship of geological objects was extracted from 2D cross-sections and used as a constraint in the modeling process, which ensured the order of the stratigraphic sequence and rationality of the geological structure in the final model. The joint objective function of the proposed method was composed of the loss function of the FCDNN and conventional MPS objective function constrained by the spatial semantics of geological objects. The concrete example in the Jiangtai Road Metro Station of Guangzhou Line 11, China illustrated that the details of the complex geological structures could be obtained accurately by the presented method. The global features from the trained FCDNN provided the basic geometry for the final model, which overcame the limitations of the conventional MPS method.

A new implementation of the beam migration by using a model-driven variable grid strategy

Beam migration offers higher imaging accuracy, better flexibility, stability and adaptability than conventional ray migration, while the variable grid method achieves lower storage and higher efficiency under the same accuracy by means of different grid generation of the velocity model. However, the efficiency and accuracy of Gaussian beam migration are strongly affected by the algorithm used for Gaussian beam summation whose key step is to find the underground point at which the local beam contributes relevantly to the reconstruction of the Green's function. Conventionally, one uses Hale's recursive search method that firstly searches on a global coarse grid and then interpolated to a local fine one. Practical experience shows that this method can greatly improve the efficiency of the beam scanning, but causes some wavy discontinuities and imaging artifacts as well. To solve this problem, we present a new method called “model-driven variable grid strategy”. In this strategy, a key step is to establish a relationship between the vertical gradient of the velocity model and the local grid constants through local velocity gradient with respect to the global average velocity. Numerical tests on synthetic and field data show that the new method has a minimal need on computer resources and can largely improve the accuracy and efficiency of the beam migration in regions with complex geological structures.