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Related papers: Borehole acoustic full-waveform inversion

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Full waveform inversion (FWI) is crucial for reconstructing high-resolution subsurface models, but it is often hindered, considering the limited data, by its null space resulting in low-resolution models, and more importantly, by its…

Geophysics · Physics 2025-10-23 Xinquan Huang , Fu Wang , Tariq Alkhalifah

Full-waveform inversion (FWI) is an advanced technique for reconstructing high-resolution subsurface physical parameters by progressively minimizing the discrepancy between observed and predicted seismic data. However, conventional FWI…

Geophysics · Physics 2025-03-04 Chao Song , Tariq Alkhalifah , Umair Bin Waheed , Silin Wang , Cai Liu

Seismic waves bring information from the physical properties of the earth to the surface. Full waveform inversion (FWI) is a local optimization technique which tries to invert the recorded wave fields to the physical properties. An…

Geophysics · Physics 2017-12-27 Nasser Kazemi

We propose and test a method to reduce the dimensionality of Full Waveform Inversion (FWI) inputs as computational cost mitigation approach. Given modern seismic acquisition systems, the data (as input for FWI) required for an…

Machine Learning · Computer Science 2026-01-06 Maayan Gelboim , Amir Adler , Mauricio Araya-Polo

Full Waveform Inversion (FWI) is an important geophysical technique considered in subsurface property prediction. It solves the inverse problem of predicting high-resolution Earth interior models from seismic data. Traditional FWI methods…

Full-Waveform Inversion (FWI) is a high-resolution technique used in geophysics to evaluate the physical parameters and construct subsurface models in a noisy and limited data scenario. The ill-posed nature of the FWI turns this a…

Full waveform inversion (FWI) is an iterative nonlinear waveform matching procedure subject to wave-equation constraint. FWI is highly nonlinear when the wave-equation constraint is enforced at each iteration. To mitigate nonlinearity,…

Optimization and Control · Mathematics 2019-10-29 Hossein S. Aghamiry , Ali Gholami , Stephane Operto

We describe a new method, full waveform inversion by model extension (FWIME) that recovers accurate acoustic subsurface velocity models from seismic data, when conventional methods fail. We leverage the advantageous convergence properties…

Geophysics · Physics 2022-05-31 Guillaume Barnier , Ettore Biondi , Robert G. Clapp , Biondo Biondi

Full waveform inversion (FWI) is a high-resolution seismic inversion technique popularly used in oil and gas exploration. Traditional FWI employs the $l_2$ norm measurement to minimize the misfit between observed and predicted seismic data.…

Geophysics · Physics 2025-04-03 Liangsheng He , Chao Song , Cai Liu

We propose a formulation of full-wavefield inversion (FWI) as a constrained optimization problem, and describe a computationally efficient technique for solving constrained full-wavefield inversion (CFWI). The technique is based on using a…

Geophysics · Physics 2014-10-28 Musa Maharramov , Biondo Biondi

Seismic full-waveform inversion (FWI) uses full seismic records to estimate subsurface velocity structure. This requires a highly nonlinear and nonunique inverse problem to be solved, and Bayesian methods have been used to quantify…

Geophysics · Physics 2021-04-13 Xin Zhang , Andrew Curtis

Full-waveform inversion (FWI) is a method that utilizes seismic data to invert the physical parameters of subsurface media by minimizing the difference between simulated and observed waveforms. Due to its ill-posed nature, FWI is…

Geophysics · Physics 2025-02-18 Xintong Dong , Zhengyi Yuan , Jun Lin , Shiqi Dong , Xunqian Tong , Yue Li

Objectives: Full-waveform inversion (FWI) is a high-resolution geophysical imaging technique that reconstructs subsurface velocity models by iteratively minimizing the misfit between predicted and observed seismic data. However, under…

Machine Learning · Computer Science 2026-03-17 Xinyi Zhang , Caiyun Liu , Jie Xiong , Qingfeng Yu

Full-Waveform Inversion (FWI) is a nonlinear iterative seismic imaging technique that, by reducing the misfit between recorded and predicted seismic waveforms, can produce detailed estimates of subsurface geophysical properties.…

Geophysics · Physics 2024-11-22 Vahid Negahdari , Seyed Reza Moghadasi , Mohammad Reza Razvan

Full waveform inversion (FWI) is a process in which seismic numerical simulations are fit to observed data by changing the wave velocity model of the medium under investigation. The problem is non-linear, and therefore optimization…

Computational Engineering, Finance, and Science · Computer Science 2017-06-06 Eran Treister , Eldad Haber

Full-waveform inversion (FWI) is an effective method for imaging subsurface properties using sparsely recorded data. It involves solving a wave propagation problem to estimate model parameters that accurately reproduce the data. Recent…

Optimization and Control · Mathematics 2025-05-02 Ali Gholami

Producing reliable acoustic subsurface velocity models still remains the main bottleneck of the oil and gas industry's traditional imaging sequence. In complex geological settings, the output of conventional ray-based or wave-equation-based…

Geophysics · Physics 2022-06-07 Guillaume Barnier , Ettore Biondi , Robert G. Clapp , Biondo Biondi

Full waveform inversion (FWI) often faces challenges due to inadequate seismic observations, resulting in band-limited and geologically inaccurate inversion results. Incorporating prior information from potential velocity distributions,…

Geophysics · Physics 2025-07-02 Fu Wang , Xinquan Huang , Tariq Alkhalifah

Full waveform inversion (FWI) is able to construct high-resolution subsurface models by iteratively minimizing discrepancies between observed and simulated seismic data. However, its implementation can be rather involved for complex wave…

Machine Learning · Computer Science 2025-06-24 Feng Liu , Haipeng Li , Guangyuan Zou , Junlun Li

Full-waveform inversion (FWI) is a powerful geophysical imaging technique that infers high-resolution subsurface physical parameters by solving a non-convex optimization problem. However, due to limitations in observation, e.g., limited…

Numerical Analysis · Mathematics 2023-11-09 Xiong-Bin Yan , Keke Wu , Zhi-Qin John Xu , Zheng Ma
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