Results 51 to 60 of about 2,936 (205)

Seismic waveform tomography with shot-encoding using a restarted L-BFGS algorithm

open access: yesScientific Reports, 2017
In seismic waveform tomography, or full-waveform inversion (FWI), one effective strategy used to reduce the computational cost is shot-encoding, which encodes all shots randomly and sums them into one super shot to significantly reduce the number of ...
Ying Rao, Yanghua Wang
doaj   +1 more source

Toward target-oriented FWI: An exact local wave solver applied to salt boundary inversion [PDF]

open access: yes, 2015
Seismic full waveform inversion (FWI) uses the gradient of the objective function for computing model updates. This requires computation of the forward and adjoint wavefields on the current model estimate.
Lewis, Winston   +2 more
core   +2 more sources

$\mathbf{\mathbb{E}^{FWI}}$: Multi-parameter Benchmark Datasets for Elastic Full Waveform Inversion of Geophysical Properties

open access: yes, 2023
Elastic geophysical properties (such as P- and S-wave velocities) are of great importance to various subsurface applications like CO$_2$ sequestration and energy exploration (e.g., hydrogen and geothermal). Elastic full waveform inversion (FWI) is widely applied for characterizing reservoir properties.
Feng, Shihang   +8 more
openaire   +2 more sources

MPI‐Based Approaches to Overlap Computation and I/O in Geophysical Simulations

open access: yesConcurrency and Computation: Practice and Experience, Volume 38, Issue 7, April 2026.
ABSTRACT Geophysical simulations, such as wave propagation, are often constrained by I/O bottlenecks, where a significant portion of the execution time is spent writing data to disk. This process frequently leaves expensive computational resources, such as GPUs, idle, directly impacting both performance and energy consumption.
Rodrigo C. Machado   +2 more
wiley   +1 more source

How Does Neural Network Reparametrization Improve Geophysical Inversion?

open access: yesJournal of Geophysical Research: Machine Learning and Computation
Full waveform inversion (FWI) is a high‐resolution seismic inversion technique and great efforts have been made to mitigate the multi‐solution problem, such as the traditional total variation (TV) regularization. Different from traditional regularization,
Yuping Wu, Jianwei Ma
doaj   +1 more source

Estimating Nuisance Parameters in Inverse Problems

open access: yes, 2012
Many inverse problems include nuisance parameters which, while not of direct interest, are required to recover primary parameters. Structure present in these problems allows efficient optimization strategies - a well known example is variable projection,
Aleksandr Y Aravkin   +17 more
core   +1 more source

A Parallel Evolution Strategy for Acoustic Full-Waveform Inversion [PDF]

open access: yes, 2014
In this work, we propose another alternative to find an initial velocity model for the acoustic FWI without any physical knowledge. Motivated by the recent growth of high performance computing (HPC), we tackle the high non-linearity of the problem to ...
Calandra, Henri   +3 more
core   +1 more source

$\omega$-FWI: Robust full-waveform inversion with Fourier-based metric

open access: yes, 2022
Full-waveform inversion is a cutting-edge methodology for recovering high-resolution subsurface models. However, one of the main conventional full-waveform optimization problems challenges is cycle-skipping, usually leading us to an inaccurate local minimum model.
Izzatullah, Muhammad, Alkhalifah, Tariq
openaire   +1 more source

New Zealand 3D Full Waveform Inversion (NZ3D-FWI) 2017-2018 field acquisition report

open access: yes, 2019
This report documents the acquisition and archiving of a major 3D active-source and passive seismic imaging experiment, NZ3D-FWI. The NZ3D-FWI project aims to image the Hikurangi subduction zone (upper and lower plates and plate boundary fault) along the north Hikurangi margin where shallow slow slip events occur.
Bell, R.   +18 more
openaire   +3 more sources

Pre-drill pore pressure prediction from 1D seismic velocity profile to 3D modeling using high resolution full waveform inversion velocity (FWI): deep water offshore, West Nile Delta

open access: yesGeomechanics and Geophysics for Geo-Energy and Geo-Resources, 2022
AbstractPore pressure prediction is one of the most critical steps while planning new well delivery activity in exploration fields in order to achieve the well target by delivering a safe well. It is very important to understand the structural and stratigraphic complexity that may influence formation pressure differences in the study area.
Maha Nabil El-Sayed Khattab   +3 more
openaire   +1 more source

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