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Deep-learning seismology
SM Mousavi, GC Beroza - Science, 2022 - science.org
Seismic waves from earthquakes and other sources are used to infer the structure and
properties of Earth's interior. The availability of large-scale seismic datasets and the …
properties of Earth's interior. The availability of large-scale seismic datasets and the …
Probabilistic inversion of seismic data for reservoir petrophysical characterization: Review and examples
D Grana, L Azevedo, L De Figueiredo, P Connolly… - Geophysics, 2022 - library.seg.org
The physics that describes the seismic response of an interval of saturated porous rocks with
known petrophysical properties is relatively well understood and includes rock physics …
known petrophysical properties is relatively well understood and includes rock physics …
Applications of deep neural networks in exploration seismology: A technical survey
SM Mousavi, GC Beroza, T Mukerji, M Rasht-Behesht - Geophysics, 2024 - library.seg.org
Exploration seismology uses reflected and refracted seismic waves, emitted from a
controlled (active) source into the ground, and recorded by an array of seismic sensors …
controlled (active) source into the ground, and recorded by an array of seismic sensors …
Sensing prior constraints in deep neural networks for solving exploration geophysical problems
One of the key objectives in geophysics is to characterize the subsurface through the
process of analyzing and interpreting geophysical field data that are typically acquired at the …
process of analyzing and interpreting geophysical field data that are typically acquired at the …
[HTML][HTML] GAN-based generation of realistic 3D volumetric data: A systematic review and taxonomy
A Ferreira, J Li, KL Pomykala, J Kleesiek, V Alves… - Medical image …, 2024 - Elsevier
With the massive proliferation of data-driven algorithms, such as deep learning-based
approaches, the availability of high-quality data is of great interest. Volumetric data is very …
approaches, the availability of high-quality data is of great interest. Volumetric data is very …
Imputation of missing well log data by random forest and its uncertainty analysis
Well logs are commonly used by geoscientists to infer and extrapolate physical properties of
subsurface rocks. However, at some depth intervals, well log values might be missing due to …
subsurface rocks. However, at some depth intervals, well log values might be missing due to …
Regularized elastic full-waveform inversion using deep learning
Z Zhang, T Alkhalifah - Advances in subsurface data analytics, 2022 - Elsevier
Elastic full-waveform inversion, which aims to match the waveforms of prestack seismic data,
potentially provides more accurate high-resolution reservoir characterization from seismic …
potentially provides more accurate high-resolution reservoir characterization from seismic …
Implicit seismic full waveform inversion with deep neural representation
Full waveform inversion (FWI) is arguably the current state‐of‐the‐art amongst
methodologies for imaging subsurface structures and physical parameters with seismic data; …
methodologies for imaging subsurface structures and physical parameters with seismic data; …
Seismic facies segmentation via a segformer-based specific encoder–decoder–hypercolumns scheme
Seismic facies classification plays an important role in oil and gas reservoir interpretation. In
the past few years, convolution neural network (CNN)-based models have been widely used …
the past few years, convolution neural network (CNN)-based models have been widely used …
Bayesian convolutional neural networks for seismic facies classification
The seismic response of geological reservoirs is a function of the elastic properties of porous
rocks, which depends on rock types, petrophysical features, and geological environments …
rocks, which depends on rock types, petrophysical features, and geological environments …