High-resolution velocity models developed using full-waveform inversion (FWI) can image fine details of the nature and structure subsurface. Using a 3D FWI model hyper-thinned crust at Deep Galicia Margin (DGM) west Iberia, we constrain this margin by comparing its with those in other similar tectonic settings. Velocities representative both upper lower continental are present, but there is no ...

Stream ecosystems provide invaluable ecosystem services but are highly impacted in need of water quality monitoring for habitat change impacts. Freshwater macroinvertebrate (FWI) assemblages have been shown to be good indicators and known vulnerable land-use land cover (LULC) other changes. The goal this case study was use an existing dominant LULC analysis the Neponset River watershed, Massach...

Abstract The influence of flow configuration on flame-wall interaction (FWI) premixed flames within turbulent boundary layers has been investigated. Direct numerical simulations (DNS) two different configurations for interacting with chemically inert isothermal and adiabatic walls in fully developed have performed. first is an oblique wall (OWI) a V-flame channel the second head-on (HOI) planar...

The influence of thermal wall boundary conditions on the behaviour scalar statistics during flame-wall interaction (FWI) premixed flames within turbulent layers has been investigated. Three-dimensional direct numerical simulations (DNS) two different flow configurations for interacting with chemically inert isothermal as well adiabatic walls in fully developed have performed. first configuratio...

We present a new seismic inversion method that uses deep learning (DL) features for the subsurface velocity model estimation. The DL feature is low-dimensional representation of high-dimensional data, which automatically generated by convolutional autoencoder (CAE) and preserved in latent space. contains key information input data. Therefore, instead directly comparing waveform differences betw...

Seismic full-waveform inversion (FWI) provides high resolution images of the subsurface by exploiting information in recorded seismic waveforms. This is achieved solving a highly nonnlinear and nonunique inverse problem. Bayesian inference therefore used to quantify uncertainties solution. Variational method that probabilistic, solutions efficiently using optimization. The has been applied 2D F...

Abstract 2015 saw the strongest El Niño event in historical record, resulting extreme drought conditions Brazil. As may also lead to greater fire danger, this study uses Brazil as a case examine whether and what extent human-induced climate change has contributed weather Cerrado southern Amazonia transitional forests known Arc of deforestation. Our results show that anthropogenic is indeed driv...

Abstract The development of an accurate velocity model is the significant target in Full Waveform Inversion (FWI) process where data fitting carried out based on ill-posed technique. In FWI technique optimization plays a crucial role through which objective function minimizes, related to misfit between observed and modelled data. However, influence external factors such as errors (local minima)...

State-of-the-art seismic imaging techniques treat inversion tasks such as full-waveform (FWI) and least-squares reverse time migration (LSRTM) partial differential equation-constrained optimization problems. Due to the large-scale nature, gradient-based algorithms are preferred in practice update model iteratively. Higher-order methods converge fewer iterations but often require higher computat...

The augmented Lagrangian (AL) method provides a flexible and efficient framework for solving extended-space full-waveform inversion (FWI), constrained nonlinear optimization problem whereby we seek model parameters wavefields that minimize the data residuals satisfy wave-equation constraint. AL-based wavefield reconstruction inversion, also known as iteratively refined extends search space of F...