Article
Environmental Sciences
Cong Luo, Jing Ba, Qiang Guo
Summary: As an important geophysical data processing technique, seismic inversion estimates subsurface rock properties with seismic observations. However, anisotropic inversion for VTI media suffers from high nonlinearity. This work proposes a sequential anisotropic inversion method for VTI media that combines Bayesian linear and simulated annealing nonlinear inversion schemes. The adaptive optimization parameters of simulated annealing are assisted by the linear result, which enhances stability and extends applicability.
Article
Geochemistry & Geophysics
Jian Sun, Kristopher Innanen, Tianze Zhang, Daniel Trad
Summary: Full waveform inversion (FWI) is a state-of-the-art method for imaging subsurface structures and physical parameters with seismic data, but it faces challenges in implementation and use. The implicit full waveform inversion (IFWI) algorithm, designed with deep neural representations, shows improved convergence and the ability to capture high-resolution subsurface structures. Although uncertainty analysis is not fully solved, IFWI addresses it meaningfully by approximating Bayesian inference. Numerical experimentation suggests that IFWI has a strong capacity for generalization and is suitable for multi-scale joint geophysical inversion.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
(2023)
Article
Computer Science, Information Systems
Ting Wang, Peng Shao, Shanhui Liu, Guangquan Li, Fuhao Yang
Summary: This paper proposes a Multi-Mechanism Particle Swarm Optimization (HGSPSO) algorithm that optimizes the position update formula and dynamically updates inertia weights to accelerate convergence and help particles jump out of local extrema. Experimental results show that this algorithm outperforms five comparison algorithms in all evaluation metrics and assessment schemes.
Article
Geochemistry & Geophysics
Zeyu Zhao, Mrinal K. Sen, Bertrand Denel, Dong Sun, Paul Williamson
Summary: A hybrid optimization framework is proposed for full waveform inversion (FWI) problems, which incorporates derivative information into the model update rule and improves the convergence speed to tackle the local minima issue of non-linear inverse problems.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
(2022)
Article
Computer Science, Interdisciplinary Applications
Victor Jose Cavalcanti Bezerra Guedes, Susanne Taina Ramalho Maciel, Marcelo Peres Rocha
Summary: The open-source software package Refrapy, written in Python, allows for seismic refraction data analysis with basic waveform processing, first breaks picking, and inversion through time-terms analysis or traveltimes tomography, with GUI interaction. The software successfully recovered geometry and velocity values of synthetic models and provided a detailed interpretation through joint inversion techniques. Results from real data analysis showed compatibility with a well-established commercial software, representing geological context satisfactorily.
COMPUTERS & GEOSCIENCES
(2022)
Review
Geochemistry & Geophysics
Yudi Pan, Lingli Gao
Summary: Shallow-seismic full-waveform inversion (FWI) is an effective method for accurate reconstruction of near-surface models. However, it suffers from ill-posedness and high computational cost. The recently proposed random-objective waveform inversion (ROWI) method shows better efficiency and robustness than FWI.
SURVEYS IN GEOPHYSICS
(2023)
Article
Computer Science, Artificial Intelligence
Sina Nayeri, Reza Tavakkoli-Moghaddam, Zeinab Sazvar, Jafar Heydari
Summary: This study proposes a mixed-integer programming model to allocate and schedule rescue teams in a response phase of disaster management under uncertainty. The developed heuristic-based simulated annealing algorithm is used to solve the NP-hard problem efficiently. The sensitivity analysis on crucial parameters of the model is reported for further insights.
Article
Geochemistry & Geophysics
Anselme F. E. Borgeaud, Frederic Deschamps
Summary: Using one-dimensional full-waveform inversion, the study simultaneously infers the S-velocity and anelastic structures of the mantle beneath Northern South America and Central America. The research highlights the importance of correcting for out-of-plane focusing effects to obtain reasonable QS models and suggests lateral variations in the fraction of post-perovskite due to differences in temperature perturbations inferred from VS and QS.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
(2021)
Article
Computer Science, Artificial Intelligence
Shameem Ahmed, Khalid Hassan Sheikh, Seyedali Mirjalili, Ram Sarkar
Summary: Feature selection plays a crucial role in machine learning, helping to improve classification accuracy while reducing computational resources. This paper introduces a hybrid optimizer BSNDO based on GNDO and SA, demonstrating its effectiveness through comparisons and tests on multiple datasets.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Multidisciplinary
Mingyu Yu, Fei Cheng, Jiangping Liu, Daicheng Peng, Zhijian Tian
Summary: Tunnel seismic detection methods are important for tunnel engineering, but current methods often lack accuracy in acquired geological information and physical properties. This study applies a frequency-domain acoustic full-waveform inversion method and discusses the influence of frequency group selection strategy and tunnel observation system settings on inversion results. Improved strategies are proposed to enhance resolution in imaging tunnel structure and physical parameters.
Article
Geosciences, Multidisciplinary
Jianyong Song, Zhifang Yang, Hong Cao, Weiguang He, Wenyong Pan, Meng Li, Na Tian
Summary: Full waveform inversion is a method used to reconstruct subsurface structures by matching synthetic and observed waveforms. In this study, a combinatory inversion strategy based on seismic events is proposed to address the challenges caused by inaccurate source wavelets and model artifacts. The strategy incorporates Gaussian time windows and the optimal transport function to improve the accuracy of the inversion results. The effectiveness of the strategy is demonstrated through synthetic experiments and real-land seismic data inversion.
FRONTIERS IN EARTH SCIENCE
(2023)
Article
Geochemistry & Geophysics
Pan Zhang, Rui Gao, Liguo Han, Zhanwu Lu
Summary: This study presents a new method for high-precision velocity imaging at crustal scale using deep reflection seismic profiles, namely refraction waves FWI. Experimental results on the deep reflection seismic profiles in the central part of Lhasa Terrane show that the refraction FWI images have higher resolution and can better describe the lateral boundaries of strata in different eras.
Article
Computer Science, Artificial Intelligence
Chunjian Shang, Liang Ma, Yong Liu, Shuo Sun
Summary: Waste sorting is an urgent and important issue in China, but there is a lack of research on mathematical models or algorithms for waste collection and transportation. Therefore, this paper proposes a new transportation model for waste management system and an efficient algorithm based on cross-entropy and simulated annealing, and verifies the effectiveness and universality of these methods through experiments.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Geochemistry & Geophysics
Wei Zhang, Jinghuai Gao, Zhaoqi Gao, Hongling Chen
Summary: The article presents a new approach to FWI based on adjoint-driven deep learning, using a fully convolutional network to achieve high-resolution inversion of subsurface velocity. It addresses the issues of ill-posedness, nonlinearity, and cycle-skipping that are common in traditional methods.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Geochemistry & Geophysics
Ali Gholami, Hossein S. Aghamiry, Stephane Operto
Summary: Full-waveform inversion (FWI) is an optimization problem that estimates subsurface model parameters by matching predicted and observed seismograms. Unlike standard FWI, which uses a penalty method, the augmented Lagrangian formulation of the method of multipliers (MM) is used in the proposed approach called multiplier waveform inversion (MWI). MWI has faster convergence speed and improved stability compared with FWI, and can converge to an accurate solution of the inverse problem even without low-frequency data.
