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Minerals
Special Issues
Theory and Applications of Seismic Inversion
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Theory and Applications of Seismic Inversion

A special issue of Minerals (ISSN 2075-163X). This special issue belongs to the section "Mineral Exploration Methods and Applications".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 7799

Special Issue Editors

Dr. Mehrdad Soleimani Monfared

E-Mail Website
Guest Editor
1. Geophysical Institute (GPI), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
2. Department of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran
Interests: seismic inversion; seismic imaging; velocity model analysis; seismic geological interpretation
Dr. Behshad Jodeiri Shokri

E-Mail Website
Guest Editor
School of Surveying and Built Environment, University of Southern Queensland, Toowoomba, QLD, Australia
Interests: geophysics; environmental geophysics; mining engineering; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Dr. Amin Roshandel Kahoo

E-Mail Website
Guest Editor
Department of Mining, Petroleum, and Geophysics, Shahrood University of Technology, Shahrood, Iran
Interests: seismic data analysis; AVO; seismic attributes

Special Issue Information

Dear Colleagues,

Seismic inversion consists of a wide range of methods, techniques and algorithms, each dealing with a specific part in the whole range of seismic data analysis and interpretation. Seismic inversion is not only the heart of the seismology and seismic exploration, but is always at the leading edge of investigation and research. Advanced methods in waveform inversion algorithms are still rapidly developing towards resolving the problem of seismic imaging in complex geological structures, resolving the obstacles of obtaining high seismic images from deep earth and using the contribution of all information imbedded in recorded data by inversion of the full waveform in full-waveform inversion methods. In velocity analysis, the inversion methods largely consist of investigations on seismic inversion. Traveltime tomography, gridded or layer-based and hybrid inversion techniques are among the seismic inversion methods that are developing rapidly and finding vast application in the chain of seismic data processing and interpretation. The researchers who investigate the development of inversion methods for deriving velocity models are welcomed to consider submitting their work to this Special Issue. 

These methods are an important part of the leading edge of seismic inversion investigations. Manuscripts addressing these state-of-the-art methods in seismic inversion are of great interest in this Special Issue. Ambiguities in the geological interpretation of seismic data are also greatly reduced by interpreting images and models obtained through the inversion of seismic data in cooperation with other sources of geophysical data. Therefore, manuscripts dealing with joint inversion, integrated inversion and cooperative inversion also attract substantial interest from the researchers working on seismic inversion. Considering the increasing application of machine learning (ML) and deep learning (DL) methods in seismic inversion, researchers studying the application of ML/DL in seismic inversion methods are welcomed to submit manuscripts.

This Special Issue is organized into three sections:

  • Section 1 Seismic inversion in the field of waveform inversion—seismic imaging and migration, velocity model building.
  • Section 2 Seismic inversion in modelling rock physical and petrophysical parameters, facie analysis, AVO analysis, colored inversion and prestack inversion.
  • Section 3 Seismic inversion in cooperation with other geophysical data inversions used in joint inversion, cooperative inversion and integrated inversion.

Dr. Mehrdad Soleimani Monfared
Dr. Behshad Jodeiri Shokri
Dr. Amin Roshandel Kahoo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Minerals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • waveform inversion
  • traveltime tomography
  • image-domain inversion
  • bayesian/intelligent inversion
  • stochastic/deterministic inversion
  • probabilistic/geostatistical inversion
  • acoustic/elastic impedance inversion
  • AVO/simultaneous/colored inversion
  • cooperative/joint/integrated inversion
  • facies controlled/rock physics inversion

Published Papers (5 papers)

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Research

12 pages, 8144 KiB  
Article
Bayesian Linear Seismic Inversion Integrating Uncertainty of Noise Level Estimation and Wavelet Extraction
by Xiuwei Yang, Ningbo Mao and Peimin Zhu
Minerals 2023, 13(1), 16; https://doi.org/10.3390/min13010016 - 23 Dec 2022
Viewed by 1540
Abstract
Seismic impedance inversion is an important method to identify the spatial characteristics of underground rock physical properties. Seismic inversion results and uncertainty evaluation are the important scientific basis for risk decision-making in oil and gas development. Under the assumption that the impedance and [...] Read more.
Seismic impedance inversion is an important method to identify the spatial characteristics of underground rock physical properties. Seismic inversion results and uncertainty evaluation are the important scientific basis for risk decision-making in oil and gas development. Under the assumption that the impedance and the error of the observed seismic data meet the Gaussian distribution or log–Gaussian distribution, the Bayesian linear seismic inversion can analytically obtain the posterior probability distribution of impedance. However, errors from observation, calculation, model and other factors can lead to an inaccurate and incomplete uncertainty evaluation. In this paper, the noise variance is used to represent the noise level of seismic data and the uncertainties from seismic wavelet extraction and noise level estimation are considered in inversion. Assuming that the probability distribution of the noise variance meets the inverse gamma distribution and the seismic wavelet meets the Gaussian distribution, we could obtain the conditional distribution for one variable given another analytically using well-log data and seismic data. In order to integrate the uncertainty from noise level estimation and wavelet extraction into the seismic impedance inversion, the Gibbs sampler algorithm was applied to draw a set of realizations of noise variance and wavelet. For each realization, the corresponding posterior probability model of impedance was achieved by Bayesian linear inversion and the final posterior probability of the impedance model was obtained by integrating all the single posterior probabilities for each pair of wavelet and noise variance. Synthetic and real data experiments showed that the uncertainties of seismic wavelet extraction and noise level estimation have an important influence on inversion results and their uncertainties. The proposed method could effectively integrate the uncertainty of wavelet and noise estimation to obtain a more accurate and comprehensive uncertainty evaluation. Under the assumption that the model meets the linear relationship and the parameters meet some specified distribution, the proposed method has high calculation efficiency. However, it also loses some accuracy when the assumptions are not completely consistent with the actual situation. Full article
(This article belongs to the Special Issue Theory and Applications of Seismic Inversion)
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16 pages, 9091 KiB  
Article
Study on the Improved Method for Calculating Traveltime and Raypath of Multistage Fast Marching Method
by Qiong Wu, Hong-Ze Mi, Yong-Bo Li and Yan-Gui Li
Minerals 2022, 12(12), 1624; https://doi.org/10.3390/min12121624 - 16 Dec 2022
Viewed by 1081
Abstract
The traditional Fast Marching Method (FMM) based on the finite-difference scheme can solve the traveltime of first arrivals; however, the accuracy and efficiency of FMM are usually affected by the finite-difference schemes and grid size. The Vidale finite-difference scheme and double-grid technology are [...] Read more.
The traditional Fast Marching Method (FMM) based on the finite-difference scheme can solve the traveltime of first arrivals; however, the accuracy and efficiency of FMM are usually affected by the finite-difference schemes and grid size. The Vidale finite-difference scheme and double-grid technology are adopted to replace the traditional first-order and second-order finite-difference schemes in this paper to improve the computation accuracy and efficiency. The traditional FMM does not provide the corresponding raypath calculation methods, and in view of the interoperability of FMM and the linear travel time interpolation (LTI) method, we introduce the linear interpolation method into FMM ray tracing to compute the raypath and take into consideration the secondary source located inside the grid cell to improve the accuracy and stability of the raypath calculation. With these measures and the application of the multistage approach, we successfully completed the improved Multistage FMM (MFMM) ray tracing, which can track first arrivals and any type of primary and multiple reflection waves. Through the theoretical and actual field model tests, the computation accuracy and efficiency of the improved MFMM are proven to be higher than that under traditional first-order and second-order finite-difference schemes, the correctness and effectiveness of the interpolation method for raypath calculation are verified, and the improved MFMM has demonstrated good adaptability and stability for complex models. The improvements for the MFMM in this paper are successfully applied in two-dimensional cases and need to be extended to three-dimensional situations. Full article
(This article belongs to the Special Issue Theory and Applications of Seismic Inversion)
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46 pages, 23608 KiB  
Article
Decomposition and Properties of the Traveltime Sensitivity Kernels in Transversely Isotropic Elastic Media
by Houzhu Zhang, Hong Liang, Hongwei Liu and Yang Zhao
Minerals 2022, 12(12), 1583; https://doi.org/10.3390/min12121583 - 10 Dec 2022
Viewed by 1046
Abstract
This study discusses the properties and decompositions of the traveltime sensitivity kernels in elastic isotopic and transversely isotropic media. Analytical solutions in homogeneous isotropic elastic media are derived and help better understand their properties. One key component is the kernel phase function which [...] Read more.
This study discusses the properties and decompositions of the traveltime sensitivity kernels in elastic isotopic and transversely isotropic media. Analytical solutions in homogeneous isotropic elastic media are derived and help better understand their properties. One key component is the kernel phase function which determines the frequency components of the sensitivity kernels, the geometrical setting of the Fresnel zones, and the resolving ability for velocity inversion. For the purpose of exploration seismology, the sensitivity kernels for finite-frequency traveltime inversion in transversely isotropic elastic media are expressed in terms of Thomsen’s anisotropic parameters. The sensitivity kernels in anisotropic media can be decomposed into the summation of the isotropic terms constructed by the elastic properties in the symmetry direction and the correction terms due to the presence of anisotropy. Sensitivity kernels computed from different types of acquisitions contain information for different parameters. We compare the kernels computed using finite-difference with those by dynamic ray tracing. We conclude that the full wave numerical method is able to provide high-resolution kernels, which form the basis for 3D finite-frequency traveltime inversion for velocity and anisotropic parameters. Full article
(This article belongs to the Special Issue Theory and Applications of Seismic Inversion)
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14 pages, 8212 KiB  
Article
Quantitative Evaluation of Faults by Combined Channel Wave Seismic Transmission-Reflection Detection Method
by Yanhui Wu, Guowei Zhu, Wei Wang, Mengbo Zhang and Zhen Gao
Minerals 2022, 12(8), 1022; https://doi.org/10.3390/min12081022 - 14 Aug 2022
Cited by 1 | Viewed by 1171
Abstract
The quantitative detection of faults using the channel wave seismic method has been a major but challenging area of interest. In this study, we adopted an effective technical process to evaluate fault attribution. First, we use integrated transmission and reflection channel wave information [...] Read more.
The quantitative detection of faults using the channel wave seismic method has been a major but challenging area of interest. In this study, we adopted an effective technical process to evaluate fault attribution. First, we use integrated transmission and reflection channel wave information to improve the accuracy of extraction velocity. Then, the location of the fault is determined by the elliptical tangent offset method, and feature extraction and fault location extension determination are achieved through logistic regression and a neural network. This is combined with the prior geological information, the fractional dimension D to the quantitative analysis of the fault throw. Data regarding the 4203 working face of a mine in Shanxi, China, are considered as an example. Two groups of faults were predicted, with the location error in the f30 fault position as 6.7 m. In addition, the f29 fault throw first increased, and then gradually decreased from the return airway to the haulage gateway. These predicted results have been drill-verified and were used to modify the original design. The proposed method has good stability and promising application prospects for fault evaluation. Full article
(This article belongs to the Special Issue Theory and Applications of Seismic Inversion)
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19 pages, 8213 KiB  
Article
Elastic Impedance Simultaneous Inversion for Multiple Partial Angle Stack Seismic Data with Joint Sparse Constraint
by Ronghuo Dai, Cheng Yin and Da Peng
Minerals 2022, 12(6), 664; https://doi.org/10.3390/min12060664 - 24 May 2022
Cited by 4 | Viewed by 1926
Abstract
Elastic impedance (EI) inversion for partial angle stack seismic data is a key technology in seismic reservoir prediction within the oil and gas industry. EI inversion provides a consistent framework to invert partial angle stack seismic data, just as the AI inversion does [...] Read more.
Elastic impedance (EI) inversion for partial angle stack seismic data is a key technology in seismic reservoir prediction within the oil and gas industry. EI inversion provides a consistent framework to invert partial angle stack seismic data, just as the AI inversion does for post-stack data. The commonly used EI inversion process is angle by angle. Hence, the inverted EI for different angles may be nonconforming, especially for the seismic data with a low signal-to-noise ratio. This paper proposes to simultaneously invert multiple partial angle stack seismic data to obtain EI for different angles at once. To obtain conformable EI, we used the joint sparse constraint on the reflection coefficients for different angles. Then, the objective function for simultaneous EI inversion was constructed. Next, synthetic seismic data profiles with three different angles were used to show the superiority of the proposed EI inversion method compared to the conventional method. At last, a real seismic data line was used to test the feasibility of the proposed method in practice. The inversion results of synthetic data and real data showed that it provides an effective new alternative method to estimate EI from partial stack seismic data. Full article
(This article belongs to the Special Issue Theory and Applications of Seismic Inversion)
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