9 citations · 15 across the 4 of their papers we have counts for
6 papers
Wavefield reconstruction inversion modelling of Marchenko focusing functions
Ruhul F. Hajjaj, Sjoerd A. L. de Ridder, Philip W. Livermore +1
Marchenko focusing functions are in their essence wavefields that satisfy the wave equation subject to a set of boundary, initial, and focusing conditions. Here, we show how Marche…
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…
The potential of self-supervised networks for random noise suppression in seismic data
Claire Birnie, Matteo Ravasi, Tariq Alkhalifah +1
Noise suppression is an essential step in any seismic processing workflow. A portion of this noise, particularly in land datasets, presents itself as random noise. In recent years,…
A Joint Inversion-Segmentation approach to Assisted Seismic Interpretation
Matteo Ravasi, Claire Emma Birnie
Structural seismic interpretation and quantitative characterization are historically intertwined processes. The latter provides estimates of properties of the subsurface which can…
On the implementation of large-scale integral operators with modern HPC solutions -- Application to 3D Marchenko imaging by least-squares inversion
Matteo Ravasi, Ivan Vasconcelos
Numerical integral operators of convolution type form the basis of most wave-equation-based methods for processing and imaging of seismic data. As several of these methods require…
PyLops -- A Linear-Operator Python Library for large scale optimization
Matteo Ravasi, Ivan Vasconcelos
Linear operators and optimisation are at the core of many algorithms used in signal and image processing, remote sensing, and inverse problems. For small to medium-scale problems,…