Geophysical Prospecting

Papers
(The H4-Index of Geophysical Prospecting is 16. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)
ArticleCitations
A fully unsupervised and highly generalized deep learning approach for random noise suppression63
Seismic data interpolation using deep learning with generative adversarial networks54
Seismic ground‐roll noise attenuation using deep learning52
Three‐dimensional Marchenko internal multiple attenuation on narrow azimuth streamer data of the Santos Basin, Brazil31
Aerial magnetic mapping with an unmanned aerial vehicle and a fluxgate magnetometer: a new method for rapid mapping and upscaling from the field to regional scale29
Seismic noise attenuation by signal reconstruction: an unsupervised machine learning approach26
Convolutional neural networks for automated microseismic detection in downhole distributed acoustic sensing data and comparison to a surface geophone array25
Erratic noise suppression using iterative structure‐oriented space‐varying median filtering with sparsity constraint23
Convolutional neural network inversion of airborne transient electromagnetic data22
An artificial neural network approach for the inversion of surface wave dispersion curves20
Pure P‐ and S‐wave equations in transversely isotropic media18
Combining discrete cosine transform and convolutional neural networks to speed up the Hamiltonian Monte Carlo inversion of pre‐stack seismic data18
Quantitative pore‐type characterization from well logs based on the seismic petrophysics in a carbonate reservoir17
Denoising of magnetotelluric data using K‐SVD dictionary training17
Multi‐parameter reflection waveform inversion for acoustic transversely isotropic media with a vertical symmetry axis17
Characterization of a carbonate reservoir using elastic full‐waveform inversion of vertical seismic profile data16
Cable reverberations during wireline distributed acoustic sensing measurements: their nature and methods for elimination16
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