A Data-Driven Method for Permeability Estimation of Rough Fractures

C. A.S. Ferreira; T. Kadeethum; N. Bouklas; H. M. Nick

doi:10.3997/2214-4609.202210810

A Data-Driven Method for Permeability Estimation of Rough Fractures

C. A.S. Ferreira, T. Kadeethum, N. Bouklas, H. M. Nick

Cornell University

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

The work presented here is novel in the application of the image-to-image translation concept for scaling-up highly heterogeneous aperture distributions of fractures in a porous medium. We show that this framework can not only parameterize complex input fields, but more importantly realistic inputs based in fractal distributions. The heterogeneous aperture distributions are replaced by the upscaled tensors and the requirement of locally fine grids is removed thus reducing the computational cost. The model provides sufficient accuracy for capturing the anisotropy of the fracture with a speed-up of at-least 800-folds for highly heterogeneous aperture.

Original language	English
Title of host publication	Proceedings of the 83^rd EAGE Conference and Exhibition
Volume	4
Publisher	European Association of Geoscientists and Engineers
Publication date	2022
Pages	2964-2968
ISBN (Electronic)	978-171385931-4
DOIs	https://doi.org/10.3997/2214-4609.202210810
Publication status	Published - 2022
Event	83^rd EAGE Annual Conference & Exhibition - IFEMA, Madrid, Spain Duration: 6 Jun 2022 → 9 Jun 2022 Conference number: 83 https://eage.eventsair.com/eageannual2022/

Conference

Conference	83^rd EAGE Annual Conference & Exhibition
Number	83
Location	IFEMA
Country/Territory	Spain
City	Madrid
Period	06/06/2022 → 09/06/2022
Internet address	https://eage.eventsair.com/eageannual2022/

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Role of micro cracks in flow ans deformation
Ferreira, C. A. S. (PhD Student), M. Nick, H. (Main Supervisor), Hajiabadi, M. R. (Supervisor), Berre, I. (Examiner) & Roubinet, D. (Examiner)
01/10/2020 → 13/03/2025
Project: PhD

Cite this

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title = "A Data-Driven Method for Permeability Estimation of Rough Fractures",

abstract = "The work presented here is novel in the application of the image-to-image translation concept for scaling-up highly heterogeneous aperture distributions of fractures in a porous medium. We show that this framework can not only parameterize complex input fields, but more importantly realistic inputs based in fractal distributions. The heterogeneous aperture distributions are replaced by the upscaled tensors and the requirement of locally fine grids is removed thus reducing the computational cost. The model provides sufficient accuracy for capturing the anisotropy of the fracture with a speed-up of at-least 800-folds for highly heterogeneous aperture.",

author = "Ferreira, \{C. A.S.\} and T. Kadeethum and N. Bouklas and Nick, \{H. M.\}",

note = "Publisher Copyright: Copyright{\textcopyright} (2022) by the European Association of Geoscientists \& Engineers (EAGE). All rights reserved.; 83<sup>rd</sup> EAGE Annual Conference \& Exhibition ; Conference date: 06-06-2022 Through 09-06-2022",

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language = "English",

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Ferreira, CAS, Kadeethum, T, Bouklas, N & Nick, HM 2022, A Data-Driven Method for Permeability Estimation of Rough Fractures. in Proceedings of the 83^rd EAGE Conference and Exhibition . vol. 4, European Association of Geoscientists and Engineers, pp. 2964-2968, 83^rd EAGE Annual Conference & Exhibition, Madrid, Spain, 06/06/2022. https://doi.org/10.3997/2214-4609.202210810

A Data-Driven Method for Permeability Estimation of Rough Fractures. / Ferreira, C. A.S.; Kadeethum, T.; Bouklas, N. et al.
Proceedings of the 83^rd EAGE Conference and Exhibition . Vol. 4 European Association of Geoscientists and Engineers, 2022. p. 2964-2968.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AB - The work presented here is novel in the application of the image-to-image translation concept for scaling-up highly heterogeneous aperture distributions of fractures in a porous medium. We show that this framework can not only parameterize complex input fields, but more importantly realistic inputs based in fractal distributions. The heterogeneous aperture distributions are replaced by the upscaled tensors and the requirement of locally fine grids is removed thus reducing the computational cost. The model provides sufficient accuracy for capturing the anisotropy of the fracture with a speed-up of at-least 800-folds for highly heterogeneous aperture.

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Y2 - 6 June 2022 through 9 June 2022

ER -

A Data-Driven Method for Permeability Estimation of Rough Fractures

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Role of micro cracks in flow ans deformation

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