[HTML][HTML] The potential of self-supervised networks for random noise suppression in seismic data

C Birnie, M Ravasi, S Liu, T Alkhalifah - Artificial Intelligence in …, 2021 - Elsevier
Noise suppression is an essential step in many seismic processing workflows. A portion of
this noise, particularly in land datasets, presents itself as random noise. In recent years …

Cola: Exploiting compositional structure for automatic and efficient numerical linear algebra

A Potapczynski, M Finzi, G Pleiss… - Advances in Neural …, 2024 - proceedings.neurips.cc
Many areas of machine learning and science involve large linear algebra problems, such as
eigendecompositions, solving linear systems, computing matrix exponentials, and trace …

An unsupervised deep-learning method for porosity estimation based on poststack seismic data

R Feng, T Mejer Hansen, D Grana, N Balling - Geophysics, 2020 - library.seg.org
We propose to invert reservoir porosity from poststack seismic data using an innovative
approach based on deep-learning methods. We develop an unsupervised approach to …

[HTML][HTML] Systematic review of machine learning techniques to predict anxiety and stress in college students

A Daza, N Saboya, JI Necochea-Chamorro… - Informatics in medicine …, 2023 - Elsevier
Background Anxiety is considered one of the most common pathologies that people go
through frequently, this being the main cause of illness and disability in students since it is …

Seismic acoustic impedance inversion via optimization-inspired semisupervised deep learning

H Chen, J Gao, W Zhang, P Yang - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Seismic acoustic impedance inversion (SAII) aims at recovering the subsurface impedance
to achieve lithology interpretation. However, its ill-posedness and nonlinearity pose a great …

Seismic Noise Interferometry and Distributed Acoustic Sensing (DAS): Inverting for the Firn Layer S‐Velocity Structure on Rutford Ice Stream, Antarctica

W Zhou, A Butcher, AM Brisbourne… - Journal of …, 2022 - Wiley Online Library
Firn densification profiles are an important parameter for ice‐sheet mass balance and
palaeoclimate studies. One conventional method of investigating firn profiles is using …

Formulating event-based image reconstruction as a linear inverse problem with deep regularization using optical flow

Z Zhang, AJ Yezzi, G Gallego - IEEE Transactions on Pattern …, 2022 - ieeexplore.ieee.org
Event cameras are novel bio-inspired sensors that measure per-pixel brightness differences
asynchronously. Recovering brightness from events is appealing since the reconstructed …

A joint inversion-segmentation approach to assisted seismic interpretation

M Ravasi, C Birnie - Geophysical Journal International, 2022 - academic.oup.com
Structural seismic interpretation and quantitative characterization are historically intertwined
processes. The latter provides estimates of the properties of the subsurface, which can be …

Scattering-based focusing for imaging in highly complex media from band-limited, multicomponent data

D Vargas, I Vasconcelos, Y Sripanich, M Ravasi - Geophysics, 2021 - library.seg.org
Reconstructing the details of subsurface structures deep beneath complex overburden
structures, such as subsalt, remains a challenge for seismic imaging. Over the past few …

Time-domain multidimensional deconvolution: A physically reliable and stable preconditioned implementation

D Vargas, I Vasconcelos, M Ravasi, N Luiken - Remote Sensing, 2021 - mdpi.com
Multidimensional deconvolution constitutes an essential operation in a variety of
geophysical scenarios at different scales ranging from reservoir to crustal, as it appears in …