Reflection Full Waveform Inversion With Second-Order Optimization Using the Adjoint-State Method

TL;DR: Li et al. as mentioned in this paper proposed a hybrid network (AG-ResUnet) involving fully convolutional layers, attention mechanism, and residual unit to estimate velocity models from common source point (CSP) gathers.

TL;DR: A novel AVO inversion process is developed to estimate fluid saturation and effective pressure changes in oil and gas reservoirs from time-lapse seismic data, incorporating prior constraints and regularization to achieve stable solutions for ill-posed inversion problems.

TL;DR: Simultaneous inversion of velocity and density using data- and model-driven approaches for accurate density estimation

TL;DR: In this article , the Hessian operator was introduced into reflection traveltime inversion and reflection waveform inversion in the framework of second-order optimization to improve the accuracy and convergence rate.

TL;DR: In this paper, the frequency-domain inversion (FDI) method was proposed to solve the non-linear problem of extracting a smooth background velocity model from surface seismic-reuse data.

TL;DR: A new discretization strategy is defined that depends on the maximum effective offset present in the surface seismic survey: the larger the range of offsets, the fewer frequencies are required.

TL;DR: In this article, the authors show that the Frechet derivatives of the objective function can be obtained for tomographic and (finite) source inversions based on just two numerical simulations for each earthquake: one calculation for the current model and a second, "adjoint" calculation that uses time-reversed signals at the receivers as simultaneous, fictitious sources.

TL;DR: In this article, the authors present a seismic mapping of reflectors in the presence of an arbitrary velocity model, dipping and curved reflectors, diffractions, ghosts, surface elevation variations, and multiple reflections.