Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)

Software for Modeling Oilfield Surface Equipment Mode

Authors
S. Iakov Korovin, Maxim G. Tkachenko
Corresponding Author
S. Iakov Korovin
Available Online March 2018.
DOI
https://doi.org/10.2991/acaai-18.2018.34How to use a DOI?
Keywords
Digital oilfield; neural networks; modeling; oil production.
Abstract

In the paper we describe a software developed to simulate the complexes of the surface infrastructure of oil and gas fields. The created software is based on methods and algorithms proposed by the team of authors for constructing models of surface equipment for hydrocarbon deposits. The proposed approaches apply neural network k models of field components, trained on the basis of data from real production sites based on telemetry control data. The interaction between the components of the model is carried out on the basis of modeling the transfer of various types of energy between the components that make up the structure of the model.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
Series
Advances in Intelligent Systems Research
Publication Date
March 2018
ISBN
978-94-6252-483-5
ISSN
1951-6851
DOI
https://doi.org/10.2991/acaai-18.2018.34How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - S. Iakov Korovin
AU  - Maxim G. Tkachenko
PY  - 2018/03
DA  - 2018/03
TI  - Software for Modeling Oilfield Surface Equipment Mode
BT  - Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
PB  - Atlantis Press
SP  - 147
EP  - 149
SN  - 1951-6851
UR  - https://doi.org/10.2991/acaai-18.2018.34
DO  - https://doi.org/10.2991/acaai-18.2018.34
ID  - Korovin2018/03
ER  -