activity
20202026
most citedStochastic Multi-Dimensional Deconvolution

24 citations · 56 across the 9 of their papers we have counts for

collaborators
Showing physics.geo-phShow all

7 papers · 1 filter

physics.geo-ph2024

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…

physics.geo-ph2023★ 4 cited

IntraSeismic: a coordinate-based learning approach to seismic inversion

Juan Romero, Wolfgang Heidrich, Nick Luiken +1

Seismic imaging is the numerical process of creating a volumetric representation of the subsurface geological structures from elastic waves recorded at the surface of the Earth. As…

physics.geo-ph2023★ 1 cited

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…

physics.geo-ph2023

Why POCS works, and how to make it better

Matteo Ravasi, Nick Luiken

Projection Over Convex Sets (POCS) is one of the most widely used algorithms in geophysical data processing to interpolate seismic data. Whilst usually described as a modification…

physics.geo-ph2023★ 12 cited

Seeing through the CO2 plume: joint inversion-segmentation of the Sleipner 4D Seismic Dataset

Juan Romero, Nick Luiken, Matteo Ravasi

4D seismic inversion is the leading method to quantitatively monitor fluid flow dynamics in the subsurface, with applications ranging from enhanced oil recovery to subsurface CO2 s…

physics.geo-ph2022★ 9 cited

A hybrid approach to seismic deblending: when physics meets self-supervision

Nick Luiken, Matteo Ravasi, Claire E. Birnie

To limit the time, cost, and environmental impact associated with the acquisition of seismic data, in recent decades considerable effort has been put into so-called simultaneous sh…

physics.geo-ph2022★ 24 cited

Stochastic Multi-Dimensional Deconvolution

Matteo Ravasi, Tamil Selvan, Nick Luiken

Seismic datasets contain valuable information that originate from areas of interest in the subsurface; such seismic reflections are however inevitably contaminated by other events…