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Fedor Krasnov,Alexander Butorin
Pág. 6 - 10
Leading experts around the world analyzed geophysical images daily by and with the development of computer vision technologies, attempts should be made to automate this process. Image data can be acquired quickly using consumer digital cameras, or p...
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Alexander Butorin,Fedor Krasnov
Pág. 7 - 16
The study considers the actual issue of improving the accuracy of mapping in fracturing using microseismic monitoring. The given question is first of all in connection with increasing volume of hydraulic fracturing at the development of modern hydrocarbo...
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Fedor Krasnov,Alexander Butorin
Pág. 42 - 49
This article proposes a method of estimating the dominant frequency of a wave field along a seismic trace, developed on the basis of the spectral inversion method. The basis of the proposed algorithm is the estimation of the dominant frequency from the r...
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Fedor Krasnov,Alexander Butorin,Alexander Sitnikov
Pág. 20 - 26
Collecting relevant evidence from seismic data is one of the standard milestones in the timeline of geological modeling.Automation of this process is difficult due to the lack of labeled dataset and computing resources.The authors of this paper used comp...
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Fedor Krasnov,Alexander Butorin
Pág. 21 - 27
The authors continue to study the application of machine learning methods to Geophysics problems. The focus of this work was the procedure for selecting frequencies for RGB-mixing. Previous work of the authors in this direction used a heuristic app...
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Fedor Krasnov and Alexander Butorin
Sparse spikes deconvolution is one of the oldest inverse problems, which is a stylized version of recovery in seismic imaging. The goal of sparse spike deconvolution is to recover an approximation of a given noisy measurement T = W ∗ r + W 0 ...
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