Výsledky vyhledávání - "M. Chambefort"

Building and Understanding Deep Neural Networks Components for Seismic Processing: Lessons Learned

Autor: J. Messud, M. Chambefort

Publikováno v: 82nd EAGE Annual Conference & Exhibition.

Summary Learning how to best mimic seismic processing algorithms or workflows with deep learning (DL) has become a very active field of research. However, seismic processing own particularities may necessitate adaptations of current DL methods. In th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::be9fb955debbcc15d5568cdc24f8a186
https://doi.org/10.3997/2214-4609.202011287

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Understanding How a Deep Neural Network Architecture Choice Can Be Related to a Seismic Processing Task

Autor: J. Messud, M. Chambefort

Publikováno v: First EAGE Digitalization Conference and Exhibition.

Summary One of the many challenges in the way of the adoption of Deep Learning (DL) for seismic processing is the understanding of deep neural network (DNN) architecture and components with the associated underlying physics involved in a specific pro

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8a7710c9e55e6cc420b34d7b7365abf7
https://doi.org/10.3997/2214-4609.202032076

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Leveraging a Supervised Machine Learning Toolkit For Better Seismic Processing Quality Control

Autor: S. Clémençon, E. Chautru, M. Chambefort, N. Salaun

Publikováno v: 81st EAGE Conference and Exhibition 2019.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8376de41f5268aeee523c2a407e69b38
https://doi.org/10.3997/2214-4609.201901618

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Detailed Surface Multiple Prediction Using Split-spread Broadband Seismic Marine Data in a Complex Sea Floor Environment

Autor: R. Soubaras, G. Henin, V. Danielsen, J. Deprey, J.E. Lie, R. Sablon, M. Chambefort, A. Pica, E. Dhelie, S. Le Roy

Publikováno v: 80th EAGE Conference and Exhibition 2018
80th EAGE Conference and Exhibition 2018, Jun 2018, Copenhagen, France

Summary Seismic data for hydrocarbon exploration in the Barents Sea can be difficult to interpret because of severe contamination of the sections by residual diffracted multiples. These multiples mainly result from significant scars of the sea floor

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45daf6ee47f0d04e6c6170d3f4b3667a
https://hal.archives-ouvertes.fr/hal-02181134

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New Design and Advanced Processing for Frac Jobs Monitoring

Autor: E. Rebel-Schissele, D. Pandolfi, M. Chambefort, T. Bardainne

Publikováno v: Proceedings.

The main goal of frac monitoring is to obtain a clear definition of event characterization to ultimately compute SRV. Enhancement in signal-to-noise ratio is one of the key elements used to discriminate a successful technique from others. While in th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::aefe1d4ee82122eab48fb132049b0e14
https://doi.org/10.3997/2214-4609.20142345

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