AI-assisted Oceanic Anoxic Events (OAEs) identification and prediction: A case from the Late Cretaceous OAE-2

S. Allam; I. Ferreira; B. Fahmi; S. Yusmananto; A. Koeshidayatullah

AI-assisted Oceanic Anoxic Events (OAEs) identification and prediction: A case from the Late Cretaceous OAE-2

S. Allam
, I. Ferreira
, B. Fahmi
, S. Yusmananto
, A. Koeshidayatullah

Department of Geosciences

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

Abstract

The prediction of OAEs by using AI/ML techniques. The proposed work focuses on OAE-2 as it is well-reported at many locations all over the world. Different machine-learning algorithms were applied to predict the occurrence of OAE-2 using a geochemical dataset. This work aims to discover new OAEs as they may be potential source rock.

Original language	English
Title of host publication	84th EAGE Annual Conference and Exhibition
Publisher	European Association of Geoscientists and Engineers, EAGE
Pages	2439-2443
Number of pages	5
ISBN (Electronic)	9781713884156
State	Published - 2023
Event	84th EAGE Annual Conference and Exhibition - Vienna, Austria Duration: 5 Jun 2023 → 8 Jun 2023

Publication series

Name	84th EAGE Annual Conference and Exhibition
Volume	4

Conference

Conference	84th EAGE Annual Conference and Exhibition
Country/Territory	Austria
City	Vienna
Period	5/06/23 → 8/06/23

Bibliographical note

Publisher Copyright:
© 2023 84th EAGE Annual Conference and Exhibition. All rights reserved.

ASJC Scopus subject areas

Geochemistry and Petrology
Geology
Geophysics
Geotechnical Engineering and Engineering Geology

Cite this

Allam, S., Ferreira, I., Fahmi, B., Yusmananto, S., & Koeshidayatullah, A. (2023). AI-assisted Oceanic Anoxic Events (OAEs) identification and prediction: A case from the Late Cretaceous OAE-2. In 84th EAGE Annual Conference and Exhibition (pp. 2439-2443). (84th EAGE Annual Conference and Exhibition; Vol. 4). European Association of Geoscientists and Engineers, EAGE.

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title = "AI-assisted Oceanic Anoxic Events (OAEs) identification and prediction: A case from the Late Cretaceous OAE-2",

abstract = "The prediction of OAEs by using AI/ML techniques. The proposed work focuses on OAE-2 as it is well-reported at many locations all over the world. Different machine-learning algorithms were applied to predict the occurrence of OAE-2 using a geochemical dataset. This work aims to discover new OAEs as they may be potential source rock.",

author = "S. Allam and I. Ferreira and B. Fahmi and S. Yusmananto and A. Koeshidayatullah",

note = "Publisher Copyright: {\textcopyright} 2023 84th EAGE Annual Conference and Exhibition. All rights reserved.; 84th EAGE Annual Conference and Exhibition ; Conference date: 05-06-2023 Through 08-06-2023",

year = "2023",

language = "English",

series = "84th EAGE Annual Conference and Exhibition",

publisher = "European Association of Geoscientists and Engineers, EAGE",

pages = "2439--2443",

booktitle = "84th EAGE Annual Conference and Exhibition",

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Allam, S, Ferreira, I, Fahmi, B, Yusmananto, S & Koeshidayatullah, A 2023, AI-assisted Oceanic Anoxic Events (OAEs) identification and prediction: A case from the Late Cretaceous OAE-2. in 84th EAGE Annual Conference and Exhibition. 84th EAGE Annual Conference and Exhibition, vol. 4, European Association of Geoscientists and Engineers, EAGE, pp. 2439-2443, 84th EAGE Annual Conference and Exhibition, Vienna, Austria, 5/06/23.

AI-assisted Oceanic Anoxic Events (OAEs) identification and prediction: A case from the Late Cretaceous OAE-2. / Allam, S.; Ferreira, I.; Fahmi, B. et al.
84th EAGE Annual Conference and Exhibition. European Association of Geoscientists and Engineers, EAGE, 2023. p. 2439-2443 (84th EAGE Annual Conference and Exhibition; Vol. 4).

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

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T2 - 84th EAGE Annual Conference and Exhibition

AU - Allam, S.

AU - Ferreira, I.

AU - Fahmi, B.

AU - Yusmananto, S.

AU - Koeshidayatullah, A.

PY - 2023

Y1 - 2023

N2 - The prediction of OAEs by using AI/ML techniques. The proposed work focuses on OAE-2 as it is well-reported at many locations all over the world. Different machine-learning algorithms were applied to predict the occurrence of OAE-2 using a geochemical dataset. This work aims to discover new OAEs as they may be potential source rock.

AB - The prediction of OAEs by using AI/ML techniques. The proposed work focuses on OAE-2 as it is well-reported at many locations all over the world. Different machine-learning algorithms were applied to predict the occurrence of OAE-2 using a geochemical dataset. This work aims to discover new OAEs as they may be potential source rock.

UR - https://www.scopus.com/pages/publications/85195814125

M3 - Conference contribution

AN - SCOPUS:85195814125

T3 - 84th EAGE Annual Conference and Exhibition

SP - 2439

EP - 2443

BT - 84th EAGE Annual Conference and Exhibition

PB - European Association of Geoscientists and Engineers, EAGE

Y2 - 5 June 2023 through 8 June 2023

ER -

AI-assisted Oceanic Anoxic Events (OAEs) identification and prediction: A case from the Late Cretaceous OAE-2

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

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Cite this