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Technological Advances in Seismic Data Processing and Imaging

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: closed (20 March 2023) | Viewed by 49285

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Guest Editor
School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing 100083, China
Interests: seismic exploration; mineral exploration; passive reflection seismic; seismic imaging; seismic migration; GPU
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Guest Editor
Sch Geophys & Informat Technol, China Univ Geosci Beijing, Beijing 100083, China
Interests: reservoir characterization; seismic data; inversions

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Guest Editor
Sch Geophys & Informat Technol, China Univ Geosci Beijing, Beijing 100083, China
Interests: gravity anomalies; magnetotellurics; aeromagnetic survey; magnetic anomalies; analytic signal

Special Issue Information

Dear Colleagues,

Seismic exploration is a method with deeper exploration capabilities and higher resolution than potential geophysical methods and has been widely used in the fields of oil and gas exploration, mineral exploration, engineering, and environmental exploration. Seismic data processing includes many conventional steps such as static correction, denoising, deconvolution, migration, and multiple eliminations, all of which play an important role in improving the final imaging quality. This Special Issue will focus on the development of advanced seismic data processing and imaging technologies and their successful application. It also welcomes technological development on passive seismic and surface wave-related development. Seismic data processing with deep learning and parallel computing is also considered in this issue.

Dr. Guofeng Liu
Dr. Zhifu Zhang
Prof. Dr. Xiaohong Meng
Guest Editors

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Published Papers (24 papers)

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Editorial

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3 pages, 170 KiB  
Editorial
Special Issue on Technological Advances in Seismic Data Processing and Imaging
by Guofeng Liu
Appl. Sci. 2023, 13(21), 11789; https://doi.org/10.3390/app132111789 - 28 Oct 2023
Viewed by 1745
Abstract
Seismic exploration is a geophysical method with deeper exploration capabilities and higher resolution than potential geophysical methods [...] Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)

Research

Jump to: Editorial

14 pages, 20532 KiB  
Article
Application of Iterative Virtual Events Internal Multiple Suppression Technique: A Case of Southwest Depression Area of Tarim, China
by Mingtu Xiao, Junfa Xie, Weihong Wang, Wenqing Liu, Jiaqing Sun, Baozhong Jin, Tao Zhang, Yuhe Zhao and Yihui Wang
Appl. Sci. 2023, 13(15), 8832; https://doi.org/10.3390/app13158832 - 31 Jul 2023
Cited by 1 | Viewed by 1003
Abstract
The seismic records in the Cambrian southwest depression of the Tarim Basin exhibit discrepancies when compared to the actual geological setting, which is caused by the presence of multiples. Despite the application of the Radon transform, multiple interferences persist beneath the Cambrian salt [...] Read more.
The seismic records in the Cambrian southwest depression of the Tarim Basin exhibit discrepancies when compared to the actual geological setting, which is caused by the presence of multiples. Despite the application of the Radon transform, multiple interferences persist beneath the Cambrian salt in the pre-stack data, with significant variations in energy and frequency across the horizontal direction. In addition, other multiple suppression methods are also difficult to handle this problem. To address this issue, we have developed an iterative virtual event internal multiple suppression method for post-stack data. This novel algorithm extends the traditional virtual event internal multiple suppression approach, eliminating the need for data regularization and avoiding the problem of the traditional virtual events method requiring sequential extraction of primaries from relevant layers, which greatly improves computational efficiency and simplifies the implementation steps of the traditional method. Numerical experiments demonstrate the efficacy of our method in suppressing internal multiples in both synthetic and field data while preserving primary signals. When applied to real seismic data profiles, the iterative method yields structural characteristics that align more closely with sedimentary laws and reduces disparities in energy and frequency of multiples along the horizontal axis. Consequently, our method provides a robust foundation for subsequent hydrocarbon source rock prediction. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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16 pages, 14590 KiB  
Article
Three-Dimensional Processing of Reflections for Passive-Source Seismology Based on Geometric Design
by Yu Liu and Guofeng Liu
Appl. Sci. 2023, 13(10), 6126; https://doi.org/10.3390/app13106126 - 17 May 2023
Viewed by 1166
Abstract
Passive-source exploration is a method of seismic exploration that has loose requirements on the conditions of the surface, is cheap, and does not require excitation by an active source. The ambient seismic signals collected from the field over an extended period of time [...] Read more.
Passive-source exploration is a method of seismic exploration that has loose requirements on the conditions of the surface, is cheap, and does not require excitation by an active source. The ambient seismic signals collected from the field over an extended period of time can be used to generate virtual-shot seismic records similar to those obtained from the seismic exploration of an active source based on the relevant correlations, and this can in turn yield information on the underground structure through a series of conventional methods of processing seismic data. Three-dimensional (3D) processing can mitigate the influence of the azimuth of random noise to yield a more representative underground structure, but requires intensive computation. In this paper, we propose a 3D method to compute reflections of a passive source based on the geometry of seismic exploration. Assuming a high quality of imaging, we use information on the predesigned geometry to choose and correlate noisy synthetic data on the reflections by a seismic body to create virtual shot data, and subsequently capture images of the 3D data on passive reflection. The use of the predesigned geometry ensures that only the important and useful parts of the dataset are used for correlation and imaging, where this reduces the cost of computation. The proposed method can thus efficiently generate high-quality 3D synthetic data. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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15 pages, 6115 KiB  
Article
Estimation of Relative Acoustic Impedance Perturbation from Reverse Time Migration Using a Modified Inverse Scattering Imaging Condition
by Hong Liang, Houzhu Zhang and Hongwei Liu
Appl. Sci. 2023, 13(9), 5291; https://doi.org/10.3390/app13095291 - 23 Apr 2023
Cited by 2 | Viewed by 1208
Abstract
Reverse Time Migration (RTM) is a preferred depth migration method for imaging complex structures. It solves the complete wave equation and can model all types of complex wave propagation with no dip limitation. Reverse time migration using the inverse scattering imaging condition produces [...] Read more.
Reverse Time Migration (RTM) is a preferred depth migration method for imaging complex structures. It solves the complete wave equation and can model all types of complex wave propagation with no dip limitation. Reverse time migration using the inverse scattering imaging condition produces structural images with an amplitude approximate to the reflectivity, which is a composite effect of the impedance and velocity changes in the acoustic media with variable velocity and density. In this study, we present a modified inverse scattering imaging condition to separate the effect of the impedance and velocity perturbations from the reflectivity. The proposed imaging condition is designed to predict the relative impedance perturbation by selecting near-angle reflections during common-shot RTM. We validate our approach on synthetic models and show that the proposed method can estimate reliable impedance perturbation. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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17 pages, 5877 KiB  
Communication
Seismic Periodic Noise Attenuation Based on Sparse Representation Using a Noise Dictionary
by Lixia Sun, Xinming Qiu, Yun Wang and Chao Wang
Appl. Sci. 2023, 13(5), 2835; https://doi.org/10.3390/app13052835 - 22 Feb 2023
Cited by 3 | Viewed by 1588
Abstract
Periodic noise is a well-known problem in seismic exploration, caused by power lines, pump jacks, engine operation, or other interferences. It contaminates seismic data and affects subsequent processing and interpretation. The conventional methods to attenuate periodic noise are notch filtering and some model-based [...] Read more.
Periodic noise is a well-known problem in seismic exploration, caused by power lines, pump jacks, engine operation, or other interferences. It contaminates seismic data and affects subsequent processing and interpretation. The conventional methods to attenuate periodic noise are notch filtering and some model-based methods. However, these methods either simultaneously attenuate noise and seismic events around the same frequencies, or need expensive computation time. In this work, a new method is proposed to attenuate periodic noise based on sparse representation. We use a noise dictionary to sparsely represent periodic noise. The noise dictionary is constructed based on ambient noise. An advantage of our method is that it can automatically suppress monochromatic periodic noise, multitoned periodic noise and even periodic noise with complex waveforms without pre-known noise frequencies. In addition, the method does not result in any notches in the spectrum. Synthetic and field examples demonstrate that our method can effectively subtract periodic noise from raw seismic data without damaging the useful seismic signal. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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16 pages, 8924 KiB  
Article
Sparse Parabolic Radon Transform with Nonconvex Mixed Regularization for Multiple Attenuation
by Qiuying Wu, Bin Hu, Cai Liu and Junming Zhang
Appl. Sci. 2023, 13(4), 2550; https://doi.org/10.3390/app13042550 - 16 Feb 2023
Viewed by 1750
Abstract
The existence of multiple reflections brings difficulty to seismic data processing and interpretation in seismic reflection exploration. Parabolic Radon transform is widely used in multiple attenuation because it is easily implemented, highly robust and efficient. However, finite seismic acquisition aperture of seismic data [...] Read more.
The existence of multiple reflections brings difficulty to seismic data processing and interpretation in seismic reflection exploration. Parabolic Radon transform is widely used in multiple attenuation because it is easily implemented, highly robust and efficient. However, finite seismic acquisition aperture of seismic data causes energy diffusion in the Radon domain, which leads to multiple residuals. In this paper, we propose a sparse parabolic Radon transform with the nonconvex Lq1-Lq2(0<q1,q2<1) mixed regularization (SPRTLq1-Lq2) that constrains the sparsity of primary and multiple reflections to overcome the energy diffusion and improve the effect of multiple attenuation, respectively. This nonconvex mixed regularization problem is solved approximately by the alternating direction method of multipliers (ADMM) algorithm, and we give the convergence conditions of the ADMM algorithm. The proposed method is compared with least squares parabolic Radon transform (LSPRT) and sparse parabolic Radon transform based on L1 regularization (SPRTL1) for multiple attenuation in the synthetic data and field data. We demonstrate that it improves the sparsity and resolution of the Radon domain data, and better results are obtained. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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17 pages, 4510 KiB  
Article
Simulation of Elastic Wave Propagation Based on Meshless Generalized Finite Difference Method with Uniform Random Nodes and Damping Boundary Condition
by Siqin Liu, Zhusheng Zhou and Weizu Zeng
Appl. Sci. 2023, 13(3), 1312; https://doi.org/10.3390/app13031312 - 18 Jan 2023
Cited by 1 | Viewed by 1641
Abstract
When the grid-based finite difference (FD) method is used for elastic wavefield forward modeling, it is inevitable that the grid divisions will be inconsistent with the actual velocity interface, resulting in problems related to the stepped grid diffraction and inaccurate travel time of [...] Read more.
When the grid-based finite difference (FD) method is used for elastic wavefield forward modeling, it is inevitable that the grid divisions will be inconsistent with the actual velocity interface, resulting in problems related to the stepped grid diffraction and inaccurate travel time of reflected waves. The generalized finite difference method (GFDM), which is based on the Taylor series expansion and weighted least square fitting, solves these problems. The partial derivative of the unknown parameters in the differential equation is represented by the linear combination of the function values of adjacent nodes. In this study, the Poisson disk node generation algorithm and the centroid Voronoi node adjustment algorithm were combined to obtain an even and random node distribution. The generated nodes fit the internal boundary more accurately for model discretization, without the presence of diffracted waves caused by the stepped grid. To avoid the instability caused by the introduction of boundary conditions, a Cerjan damping boundary condition was proposed for boundary reflection processing. The test results generated by the different models showed that the generalized finite difference method can effectively solve the problems related to inaccurate travel time of reflection waves and stepped grid diffraction. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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13 pages, 3389 KiB  
Article
Study on Seismic Attenuation Based on Wave-Induced Pore Fluid Dissolution and Its Application
by Ziqi Jin, Xuelin Zheng, Ying Shi and Weihong Wang
Appl. Sci. 2023, 13(1), 74; https://doi.org/10.3390/app13010074 - 21 Dec 2022
Viewed by 1553
Abstract
Seismic wave attenuation is affected by wave-induced pore fluid dissolution. The mechanism of wave-induced pore fluid dissolution is the mutual dissolution between different fluids caused by pore fluid pressure. Compared with the traditional WIFF (wave-induced fluid flow) mechanism, the wave-induced pore fluid dissolution [...] Read more.
Seismic wave attenuation is affected by wave-induced pore fluid dissolution. The mechanism of wave-induced pore fluid dissolution is the mutual dissolution between different fluids caused by pore fluid pressure. Compared with the traditional WIFF (wave-induced fluid flow) mechanism, the wave-induced pore fluid dissolution mechanism can predict the attenuation of the seismic frequency band and can be used in well-to-seismic calibration. Conventional methods neglect the velocity dispersion caused by the interaction between pore fluids, which will lead to errors in attenuation prediction. In this paper, we focus on accurately predicting the velocity dispersion at low porosity and permeability, which can be used in multi-scale data matching. The stretch between the synthetic data by using logging data and seismic data needs to be calibrated for more accurate interpretation. The kernel of well-to-seismic calibration is the knowledge of the velocity dispersion between the logging frequency band and seismic frequency band. We calibrate the difference between the two kinds of data by using the rock physical model. Both the model test and field data application prove the feasibility and accuracy of the proposed strategy. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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13 pages, 13090 KiB  
Article
Seismic Coherent Noise Removal of Source Array in the NSST Domain
by Minghao Yu, Xiangbo Gong and Xiaojie Wan
Appl. Sci. 2022, 12(21), 10846; https://doi.org/10.3390/app122110846 - 26 Oct 2022
Cited by 2 | Viewed by 1507
Abstract
The technique of the source array based on the vibroseis can provide the strong energy of a seismic wave field, which better meets the need for seismic exploration. The seismic coherent noise reduces the signal-to-noise ratio (SNR) of the source array seismic data [...] Read more.
The technique of the source array based on the vibroseis can provide the strong energy of a seismic wave field, which better meets the need for seismic exploration. The seismic coherent noise reduces the signal-to-noise ratio (SNR) of the source array seismic data and affects the seismic data processing. The traditional coherent noise removal methods often cause some damage to the effective signal while suppressing coherent noise or cannot suppress the interference wave effectively at all. Based on the multi-scale and multi-direction properties of the non-subsampled Shearlet transform (NSST) and its simple mathematical structure, the seismic coherent noise removal method of source array in NSST domain is proposed. The method is applied to both the synthetic seismic data and the filed seismic data. After processing with this method, the coherent noise of the seismic data is greatly removed and the effective signal information is greatly protected. The analysis of the results demonstrates the effectiveness and practicability of the proposed method on coherent noise attenuation. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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13 pages, 5875 KiB  
Article
Research on Initial Model Construction of Seismic Inversion Based on Velocity Spectrum and Siamese Network
by Luping Sun, Ling Ding and Xiangchun Wang
Appl. Sci. 2022, 12(20), 10593; https://doi.org/10.3390/app122010593 - 20 Oct 2022
Viewed by 1545
Abstract
The initial model plays an important role in seismic inversion. Generally, the initial model is constructed by lateral extrapolation of parameters under horizons constraints. However, without horizon data, initial modeling becomes a challenging task. Velocity spectrum is a 2D image that can reflect [...] Read more.
The initial model plays an important role in seismic inversion. Generally, the initial model is constructed by lateral extrapolation of parameters under horizons constraints. However, without horizon data, initial modeling becomes a challenging task. Velocity spectrum is a 2D image that can reflect the characteristics of the formations. We regard the problem of establishing the initial model as the problem of similarity analysis of seismic lateral characteristics and propose a method of establishing the initial inversion model based on velocity spectrum and Siamese network. Firstly, the lateral variation of formation characteristics is tracked on velocity spectra generated by common depth point (CDP) gathers. Then, the target tracking results at different CDP positions are obtained with the triple Siamese network. Finally, the discrete inversion parameters are extrapolated along the tracking paths to obtain the initial inversion model. The Siamese network can quickly obtain the similarity of 2D images and does not need manual labels. The theoretical and practical results show that our method can efficiently generate the initial model that conforms to the seismic structure and stratigraphic characteristics without the constraint of interpreted horizon data. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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21 pages, 9261 KiB  
Article
Seismic Structure Beneath the Molucca Sea Collision Zone from Travel Time Tomography Based on Local and Regional BMKG Networks
by Gazali Rachman, Bagus Jaya Santosa, Andri Dian Nugraha, Supriyanto Rohadi, Shindy Rosalia, Zulfakriza Zulfakriza, Sungkono Sungkono, David P. Sahara, Faiz Muttaqy, Pepen Supendi, Mohamad Ramdhan, Ardianto Ardianto and Haunan Afif
Appl. Sci. 2022, 12(20), 10520; https://doi.org/10.3390/app122010520 - 18 Oct 2022
Cited by 3 | Viewed by 3115
Abstract
The Molucca Sea Plate, and Sangihe and Halmahera plates have a complex tectonic setting and interact to create the Molucca Sea Collision Zone. We re-picked 1647 events recorded from 2010 to 2017 from 32 of The Agency for Meteorology, Climatology, and Geophysics (BMKG) [...] Read more.
The Molucca Sea Plate, and Sangihe and Halmahera plates have a complex tectonic setting and interact to create the Molucca Sea Collision Zone. We re-picked 1647 events recorded from 2010 to 2017 from 32 of The Agency for Meteorology, Climatology, and Geophysics (BMKG) stations and obtained P- and S-arrivals of ~17,628 phases. Hypocenter locations were determined using the software NonLinLoc. Then, we performed a travel time tomography in order to image the subsurface and approximate the Molucca Sea Plate subduction angle beneath Sulawesi’s north arm, the relationship subduction zone and volcanic activity in Halmahera, and depth comparison of the Molucca Sea Plate. Our results show that (i) high Vp, high Vs, and low Vp/Vs are associated with the Molucca Sea Plate beneath Sulawesi’s north arm, and the approximate subduction angle is ~40°. (ii) Low Vp, low Vs, and high Vp/Vs beneath the northern and southern Halmahera Volcanic Arc are associated with a possible magma source. Volcanoes in the north have experienced eruptions and are dormant in the south. This group of volcanoes is connected by partial melting above the Molucca Sea Plate subducts to the east. (iii) High Vp, high Vs, and low Vp/Vs are interpreted as double subduction of the Molucca Sea Plate. It is submerged deeper in the north compared with the south, which is nearer to the surface. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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12 pages, 4300 KiB  
Article
Reverse Time Migration Imaging Using SH Shear Wave Data
by Chengyao Zhou, Wenjie Yin, Jun Yang, Hongmei Nie and Xiangyang Li
Appl. Sci. 2022, 12(19), 9944; https://doi.org/10.3390/app12199944 - 3 Oct 2022
Cited by 1 | Viewed by 1864
Abstract
In this paper, we discussed the reverse time migration imaging of compressional wave (P-wave) and horizontally polarized shear wave (SH shear wave) seismic data, together with P- and SH shear wave constrained velocity model building. In the Sanhu area in Qaidam Basin, there [...] Read more.
In this paper, we discussed the reverse time migration imaging of compressional wave (P-wave) and horizontally polarized shear wave (SH shear wave) seismic data, together with P- and SH shear wave constrained velocity model building. In the Sanhu area in Qaidam Basin, there are large areas of gas clouds, which leads to poor P-wave seismic imaging. The P and SH shear wave seismic data of a co-located survey line with the same acquisition geometry were used to access their imaging capability using reverse time migration. We first estimated the change in P-wave and SH shear wave velocity ratio using pre-stack time migration (PSTM) for constraining the overall depth domain velocity model. Additionally, we then used an eighth-order finite difference scheme for P-wave reverse time migration on a variable grid and used the sixth-order combined compact difference (CCD) wave field simulation method for SH shear wave reverse time migration on a regular grid. The results show that the constrained velocity model produces a good match in the overall geological structure shown in the P-wave and SH shear wave reverse time migration results. However, in the gas cloud areas, SH shear wave reverse time migration has obvious imaging advantages, which can clearly image the structure inside the gas clouds. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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39 pages, 25298 KiB  
Article
Estimation of Litho-Fluid Facies Distribution from Zero-Offset Acoustic and Shear Impedances
by Mohammed Fathy Gouda, Abdul Halim Abdul Latiff and Seyed Yasser Moussavi Alashloo
Appl. Sci. 2022, 12(15), 7754; https://doi.org/10.3390/app12157754 - 1 Aug 2022
Cited by 1 | Viewed by 2228
Abstract
Seismic data are considered crucial sources of data that help identify the litho-fluid facies distributions in reservoir rocks. However, different facies mostly have similar responses to seismic attributes. In addition, seismic anisotropy negatively affects the facies predictors extracted from seismic data. Accordingly, this [...] Read more.
Seismic data are considered crucial sources of data that help identify the litho-fluid facies distributions in reservoir rocks. However, different facies mostly have similar responses to seismic attributes. In addition, seismic anisotropy negatively affects the facies predictors extracted from seismic data. Accordingly, this study aims at estimating zero-offset acoustic and shear impedances based on partial-stack inversion by two methods: statistical modeling and a multilayer feed-forward neural network (MLFN). The resulting impedance volumes are compared to those obtained from isotropic simultaneous inversion by using impedance logs. The best impedance volumes are applied to Thomsen’s anisotropy equations to solve for the anisotropy parameters Epsilon and Delta. Finally, the shear and acoustic impedances are transformed into elastic properties from which the facies and fluid distributions are predicted by using the logistic regression and decision tree algorithms. The results obtained from the MLFN show better matching with the impedance and facies logs compared to those obtained from isotropic inversion and statistical modeling. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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12 pages, 2534 KiB  
Article
Seismic Velocity Anomalies Detection Based on a Modified U-Net Framework
by Ziqian Li, Jiwei Jia, Zheng Lu, Jian Jiao and Ping Yu
Appl. Sci. 2022, 12(14), 7225; https://doi.org/10.3390/app12147225 - 18 Jul 2022
Cited by 2 | Viewed by 1844
Abstract
Accurate and efficient reconstruction of hidden geological structures under the surface is the main task of high-resolution Velocity Model Building (VMB). The most commonly used methods in practice are Tomography and Full Waveform Inversion (FWI), which rely heavily on the initial model. Recently, [...] Read more.
Accurate and efficient reconstruction of hidden geological structures under the surface is the main task of high-resolution Velocity Model Building (VMB). The most commonly used methods in practice are Tomography and Full Waveform Inversion (FWI), which rely heavily on the initial model. Recently, deep learning types of methods have received widespread attention and have performed well in many tasks such as image segmentation and classification. Therefore, it is of great significance to introduce deep learning algorithms into the VMB procedure to accelerate the production cycle, especially for the velocity anomalies detection, which is crucial for a high-resolution initial model. In this paper, a modified U-Net framework is proposed and applied directly on the seismic shot gathers to identify anomalies in the early stage of VMB, which can provide a suitable initial guess for the following large-scale VMB procedures such as FWI. The numerical examples show the power of the proposed method on synthetic data. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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19 pages, 6259 KiB  
Article
The Combined Compact Difference Scheme Applied to Shear-Wave Reverse-Time Migration
by Chengyao Zhou, Wei Wu, Pengyuan Sun, Wenjie Yin and Xiangyang Li
Appl. Sci. 2022, 12(14), 7047; https://doi.org/10.3390/app12147047 - 12 Jul 2022
Cited by 3 | Viewed by 1424
Abstract
In this paper, the combined compact difference scheme (CCD) and the combined supercompact difference scheme (CSCD) are used in the numerical simulation of the shear-wave equation. According to the Taylor series expansion and shear-wave equation, the fourth-order discrete scheme of the displacement field [...] Read more.
In this paper, the combined compact difference scheme (CCD) and the combined supercompact difference scheme (CSCD) are used in the numerical simulation of the shear-wave equation. According to the Taylor series expansion and shear-wave equation, the fourth-order discrete scheme of the displacement field is established; then, the CCD and CSCD schemes are used to calculate the spatial derivative of the displacement field. Additionally, the accuracy, dispersion, and stability of the CCD and CSCD are analyzed, and numerical simulation analyses are carried out using 1D uniform models. Lastly, based on the processing of artificial boundary reflection using PML boundary conditions, shear-wave reverse-time migrations are carried out using synthetic data. The results show that (1) CCD and CSCD have smaller truncation errors, higher simulation precision, and lower numerical dispersion than other normal difference schemes; (2) CCD and CSCD can use the coarse grid and larger time step to calculate, with less memory and high computational efficiency; (3) finally, the result of the shear-wave reverse-time migration of the 2D synthetic data model show that the reverse-time migration imaging is clear, and the proposed method for shear-wave reverse-time migration is practical and effective. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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11 pages, 5434 KiB  
Article
Elastic Reverse Time Migration for Weakly Illuminated Structure
by Liwei Song, Ying Shi, Wei Liu and Qiang Zhao
Appl. Sci. 2022, 12(10), 5264; https://doi.org/10.3390/app12105264 - 23 May 2022
Cited by 3 | Viewed by 1724
Abstract
One of the most effective techniques to obtain PP and PS images is elastic reverse time migration which employs multi-component seismic data. The two types of complementary images play an important role in reducing blind spots in seismic exploration. However, the migration image [...] Read more.
One of the most effective techniques to obtain PP and PS images is elastic reverse time migration which employs multi-component seismic data. The two types of complementary images play an important role in reducing blind spots in seismic exploration. However, the migration image of deep structures is always blurred due to the shielding effect of overburden rock on seismic waves. To overcome this issue, we develop an elastic reverse time migration approach for insufficient illumination. This approach contains two crucial elements. The first is that we derive an elastic wave equation to extract the wavefields associated with the exploration target using the staining algorithm. Secondly, we develop an inner product imaging condition with a filter to mute migrated artifacts. The filter, consisting of two vectors, determines which part of the wavefield is contributed to imaging. Synthetic examples exhibit that the proposed elastic reverse time migration method can improve the signal-to-noise ratio of PP and PS images of weakly illuminated structures. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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16 pages, 9002 KiB  
Article
Processing the Artificial Edge-Effects for Finite-Difference Frequency-Domain in Viscoelastic Anisotropic Formations
by Jixin Yang, Xiao He and Hao Chen
Appl. Sci. 2022, 12(9), 4719; https://doi.org/10.3390/app12094719 - 7 May 2022
Cited by 2 | Viewed by 1709
Abstract
Real sedimentary media can usually be characterized as transverse isotropy. To reveal wave propagation in the true models and improve the accuracy of migrations and evaluations, we investigated the algorithm of wavefield simulations in an anisotropic viscoelastic medium. The finite difference in the [...] Read more.
Real sedimentary media can usually be characterized as transverse isotropy. To reveal wave propagation in the true models and improve the accuracy of migrations and evaluations, we investigated the algorithm of wavefield simulations in an anisotropic viscoelastic medium. The finite difference in the frequency domain (FDFD) has several advantages compared with that in the time domain, e.g., implementing multiple sources, multi-scaled inversion, and introducing attenuation. However, medium anisotropy will lead to the complexity of the wavefield in the calculation. The damping profile of the conventional absorption boundary is only defined in one single direction, which produces instability when the wavefields of strong anisotropy are reflected on that truncated boundary. We applied the multi-axis perfectly matched layer (M-PML) to the wavefield simulations in anisotropic viscoelastic media to overcome this issue, which defines the damping profiles along different axes. In the numerical examples, we simulated seismic wave propagation in three viscous anisotropic media and focused on the wave attenuation in the absorbing layers using time domain snapshots. The M-PML was more effective for wave absorption compared to the conventional perfectly matched layer (PML). In strongly anisotropic media, the PML became unstable, and prominent reflections appeared at truncated boundaries. In contrast, the M-PML remained stable and efficient in the same model. Finally, the modeling of the stratified cross-well model showed the applicability of this proposed algorithm to heterogeneous viscous anisotropic media. The numerical algorithm can analyze wave propagation in viscoelastic anisotropic media. It also provides a reliable forward operator for waveform inversion, wave equation travel-time inversion, and seismic migration in anisotropic viscoelastic media. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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12 pages, 8860 KiB  
Article
Fault Imaging of Seismic Data Based on a Modified U-Net with Dilated Convolution
by Jizhong Wu, Ying Shi and Weihong Wang
Appl. Sci. 2022, 12(5), 2451; https://doi.org/10.3390/app12052451 - 26 Feb 2022
Cited by 8 | Viewed by 1875
Abstract
Fault imaging follows the processing and migration imaging of seismic data, which is very important in oil and gas exploration and development. Conventional fault imaging methods are easily influenced by seismic data and interpreters’ experience and have limited ability to identify complex fault [...] Read more.
Fault imaging follows the processing and migration imaging of seismic data, which is very important in oil and gas exploration and development. Conventional fault imaging methods are easily influenced by seismic data and interpreters’ experience and have limited ability to identify complex fault areas and micro-faults. Conventional convolutional neural network uniformly processes feature maps of the same layer, resulting in the same receptive field of the neural network in the same layer and relatively single local information obtained, which is not conducive to the imaging of multi-scale faults. To solve this problem, our research proposes a modified U-Net architecture. Two functional modules containing dilated convolution are added between the encoder and decoder to enhance the network’s ability to select multi-scale information, enhance the consistency between the receptive field and the target region of fault recognition, and finally improve the identification ability of micro-faults. Training on synthetic seismic data and testing on real data were carried out using the modified U-Net. The actual fault imaging shows that the proposed scheme has certain advantages. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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11 pages, 4654 KiB  
Article
Ground Roll Attenuation of Multicomponent Seismic Data with the Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD) Method
by Liying Xiao, Zhifu Zhang and Jianjun Gao
Appl. Sci. 2022, 12(5), 2429; https://doi.org/10.3390/app12052429 - 25 Feb 2022
Cited by 7 | Viewed by 2533
Abstract
Multicomponent seismic exploration provides more wavefield information for imaging complex subsurface structures and predicting reservoirs. Ground roll is strongly coherent noise in land multicomponent seismic data and exhibits similar features, which are strong energy, low frequency, low velocity and dispersion, in each component. [...] Read more.
Multicomponent seismic exploration provides more wavefield information for imaging complex subsurface structures and predicting reservoirs. Ground roll is strongly coherent noise in land multicomponent seismic data and exhibits similar features, which are strong energy, low frequency, low velocity and dispersion, in each component. Ground roll attenuation is an important step in seismic data processing. In this study, we utilized multivariate empirical mode decomposition to multicomponent seismic data for attenuating ground roll. By adding extra components containing independent white noise, noise-assisted multivariate empirical mode decomposition is adopted to overcome the mode-mixing effect in standard empirical mode decomposition. This method provides a more robust analysis than the standard empirical mode decomposition EMD method performed separately for each component. Multicomponent seismic data are decomposed into different intrinsic mode functions in frequency scale. According to different frequency scales of seismic reflection wave and ground roll, intrinsic mode functions with low frequency are eliminated to suppress ground roll, and the remaining are reconstructed for seismic reflection waves. Synthetic and field data tests show that the proposed approach performs better than the traditional attenuation method. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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12 pages, 7367 KiB  
Article
Least-Squares Reverse Time Migration in Imaging Domain Based on Global Space-Varying Deconvolution
by Bo Li, Minao Sun, Chen Xiang and Yingzhe Bai
Appl. Sci. 2022, 12(5), 2361; https://doi.org/10.3390/app12052361 - 24 Feb 2022
Cited by 2 | Viewed by 2009
Abstract
The classical least-squares migration (LSM) translates seismic imaging into a data-fitting optimization problem to obtain high-resolution images. However, the classical LSM is highly dependent on the precision of seismic wavelet and velocity models, and thus it suffers from an unstable convergence and excessive [...] Read more.
The classical least-squares migration (LSM) translates seismic imaging into a data-fitting optimization problem to obtain high-resolution images. However, the classical LSM is highly dependent on the precision of seismic wavelet and velocity models, and thus it suffers from an unstable convergence and excessive computational costs. In this paper, we propose a new LSM method in the imaging domain. It selects a spatial-varying point spread function to approximate the accurate Hessian operator and uses a high-dimensional spatial deconvolution algorithm to replace the common-used iterative inversion. To keep a balance between the inversion precision and the computational efficiency, this method is implemented based on the strategy of regional division, and the point spread function is computed using only one-time demigration/migration and inverted individually in each region. Numerical experiments reveal the differences in the spatial variation of point spread functions and highlight the importance to use a space-varying deconvolution algorithm. A 3D field case in Northwest China can demonstrate the effectiveness of this method on improving spatial resolution and providing better characterizations for small-scale fracture and cave units of carbonate reservoirs. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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15 pages, 6458 KiB  
Article
Multi-Task Deep Learning Seismic Impedance Inversion Optimization Based on Homoscedastic Uncertainty
by Xiu Zheng, Bangyu Wu, Xiaosan Zhu and Xu Zhu
Appl. Sci. 2022, 12(3), 1200; https://doi.org/10.3390/app12031200 - 24 Jan 2022
Cited by 10 | Viewed by 3542
Abstract
Seismic inversion is a process to obtain the spatial structure and physical properties of underground rock formations using surface acquired seismic data, constrained by known geological laws and drilling and logging data. The principle of seismic inversion based on deep learning is to [...] Read more.
Seismic inversion is a process to obtain the spatial structure and physical properties of underground rock formations using surface acquired seismic data, constrained by known geological laws and drilling and logging data. The principle of seismic inversion based on deep learning is to learn the mapping between seismic data and rock properties by training a neural network using logging data as labels. However, due to high cost, the number of logging curves is often limited, leading to a trained model with poor generalization. Multi-task learning (MTL) provides an effective way to mitigate this problem. Learning multiple related tasks at the same time can improve the generalization ability of the model, thereby improving the performance of the main task on the same amount of labeled data. However, the performance of multi-task learning is highly dependent on the relative weights for the loss of each task, and manual tuning of the weights is often time-consuming and laborious. In this paper, a Fully Convolutional Residual Network (FCRN) is proposed to achieve seismic impedance inversion and seismic data reconstruction simultaneously, and a method based on the homoscedastic uncertainty of the Bayesian model is used to balance the weights of the loss function for the two tasks. The test results on the synthetic datasets of Marmousi2, Overthrust, and Volve field data show that the proposed method can automatically determine the optimal weight of the two tasks, and predicts impedance with higher accuracy than single-task FCRN model. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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13 pages, 6642 KiB  
Article
Application of an Automatic Noise or Signal Removal Algorithm Based on Synchrosqueezed Continuous Wavelet Transform of Passive Surface Wave Imaging: A Case Study in Sichuan, China
by Jie Fang, Guofeng Liu and Yu Liu
Appl. Sci. 2021, 11(24), 11718; https://doi.org/10.3390/app112411718 - 9 Dec 2021
Cited by 2 | Viewed by 2326
Abstract
Passive surface wave imaging based on noise cross-correlation has been a research hotspot in recent years. However, because randomness of noise is difficult to achieve in reality, prominent noise sources will inevitably affect the dispersion measurement. Additionally, in order to recover high-fidelity surface [...] Read more.
Passive surface wave imaging based on noise cross-correlation has been a research hotspot in recent years. However, because randomness of noise is difficult to achieve in reality, prominent noise sources will inevitably affect the dispersion measurement. Additionally, in order to recover high-fidelity surface waves, the time series input during cross-correlation calculation is usually very long, which greatly limits the efficiency of passive surface wave imaging. With an automatic noise or signal removal algorithm based on synchrosqueezed continuous wavelet transform (SS-CWT), these problems can be alleviated. We applied this method to 1-h passive datasets acquired in Sichuan province, China; separated the prominent noise events in the raw field data, and enhanced the cross-correlation reconstructed surface waves, effectively improving the accuracy of the dispersion measurement. Then, using the conventional surface wave inversion method, the shear wave velocity profile of the underground structure in this area was obtained. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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21 pages, 5282 KiB  
Article
The Characteristics of Seismic Rotations in VTI Medium
by Lixia Sun, Yun Wang, Wei Li and Yongxiang Wei
Appl. Sci. 2021, 11(22), 10845; https://doi.org/10.3390/app112210845 - 17 Nov 2021
Cited by 1 | Viewed by 1646
Abstract
Under the assumptions of linear elasticity and small deformation in traditional elastodynamics, the anisotropy of the medium has a significant effect on rotations observed during earthquakes. Based on the basic theory of the first-order velocity-stress elastic wave equation, this paper simulates the seismic [...] Read more.
Under the assumptions of linear elasticity and small deformation in traditional elastodynamics, the anisotropy of the medium has a significant effect on rotations observed during earthquakes. Based on the basic theory of the first-order velocity-stress elastic wave equation, this paper simulates the seismic wave propagation of the translational and rotational motions in two-dimensional isotropic and VTI (transverse isotropic media with a vertical axis of symmetry) media under different source mechanisms with the staggered-grid finite-difference method with respect to nine different seismological models. Through comparing the similarities and differences between the translational and rotational components of the wave fields, this paper focuses on the influence of anisotropic parameters on the amplitude and phase characteristics of the rotations. We verify that the energy of S waves in the rotational components is significantly stronger than that of P waves, and the response of rotations to the anisotropic parameters is more sensitive. There is more abundant information in the high-frequency band of the rotational components. With the increase of Thomsen anisotropic parameters ε and δ, the energy of the rotations increases gradually, which means that the rotational component observation may be helpful to the study of anisotropic parameters. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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32 pages, 12947 KiB  
Article
Near-Surface Geological Structure Seismic Wave Imaging Using the Minimum Variance Spatial Smoothing Beamforming Method
by Ming Peng, Dengyi Wang, Liu Liu, Chengcheng Liu, Zhenming Shi, Fuan Ma and Jian Shen
Appl. Sci. 2021, 11(22), 10827; https://doi.org/10.3390/app112210827 - 16 Nov 2021
Cited by 2 | Viewed by 2383
Abstract
Erecting underground structures in regions with unidentified weak layers, cavities, and faults is highly dangerous and potentially disastrous. An efficient and accurate near-surface exploration method is thus of great significance for guiding construction. In near-surface detection, imaging methods suffer from artifacts that the [...] Read more.
Erecting underground structures in regions with unidentified weak layers, cavities, and faults is highly dangerous and potentially disastrous. An efficient and accurate near-surface exploration method is thus of great significance for guiding construction. In near-surface detection, imaging methods suffer from artifacts that the complex structure caused and a lack of efficiency. In order to realize a rapid, accurate, robust near-surface seismic imaging, a minimum variance spatial smoothing (MVSS) beamforming method is proposed for the seismic detection and imaging of underground geological structures under a homogeneous assumption. Algorithms such as minimum variance (MV) and spatial smoothing (SS), the coherence factor (CF) matrix, and the diagonal loading (DL) methods were used to improve imaging quality. Furthermore, it was found that a signal advance correction helped improve the focusing effect in near-surface situations. The feasibility and imaging quality of MVSS beamforming are verified in cave models, layer models, and cave-layer models by numerical simulations, confirming that the MVSS beamforming method can be adapted for seismic imaging. The performance of MVSS beamforming is evaluated in the comparison with Kirchhoff migration, the DAS beamforming method, and reverse time migration. MVSS beamforming has a high computational efficiency and a higher imaging resolution. MVSS beamforming also significantly suppresses the unnecessary components in seismic signals such as S-waves, surface waves, and white noise. Moreover, compared with basic delay and sum (DAS) beamforming, MVSS beamforming has a higher vertical resolution and adaptively suppresses interferences. The results show that the MVSS beamforming imaging method might be helpful for detecting near-surface underground structures and for guiding engineering construction. Full article
(This article belongs to the Special Issue Technological Advances in Seismic Data Processing and Imaging)
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