2 citations · 4 across the 10 of their papers we have counts for
10 papers
Multidimensional deconvolution with shared bases
Daria Sushnikova, Matteo Ravasi, David Keyes
We address the estimation of seismic wavefields by means of Multidimensional Deconvolution (MDD) for various redatuming applications. While offering more accuracy than conventional…
Robust Full Waveform Inversion with deep Hessian deblurring
Mustafa Alfarhan, Matteo Ravasi, Fuqiang Chen +1
Full Waveform Inversion (FWI) is a technique widely used in geophysics to obtain high-resolution subsurface velocity models from waveform seismic data. Due to its large computation…
Upside down Rayleigh-Marchenko: a practical, yet exact redatuming scheme for seabed seismic acquisitions
Ning Wang, Matteo Ravasi
Ocean-bottom seismic plays a crucial role in resource exploration and monitoring. However, despite its undoubted potential, the use of coarse receiver geometries poses challenges t…
Plug-and-Play regularized 3D seismic inversion with 2D pre-trained denoisers
Nick Luiken, Juan Romero, Miguel Corrales +1
Post-stack seismic inversion is a widely used technique to retrieve high-resolution acoustic impedance models from migrated seismic data. Its modelling operator assumes that a migr…
Laterally constrained low-rank seismic data completion via cyclic-shear transform
David Vargas, Ivan Vasconcelos, Nick Luiken +1
A crucial step in seismic data processing consists in reconstructing the wavefields at spatial locations where faulty or absent sources and/or receivers result in missing data. Sev…
Explainable Artificial Intelligence driven mask design for self-supervised seismic denoising
Claire Birnie, Matteo Ravasi
The presence of coherent noise in seismic data leads to errors and uncertainties, and as such it is paramount to suppress noise as early and efficiently as possible. Self-supervise…