A Cyber-Physical System for Semi-autonomous Oil & Gas Drilling Operations

Yazan Mualla 1 Amro Najjar 2 Olivier Boissier 3, 4, 5, 6 Stéphane Galland 7 Igor Tchappi Haman 7 Robin Vanet 3, 8
1 Le2i - Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508]
2 Umeå University
3 Mines Saint-Étienne MSE - École des Mines de Saint-Étienne
4 LHC - Laboratoire Hubert Curien [Saint Etienne]
5 FAYOL-ENSMSE - Institut Henri Fayol
6 FAYOL-ENSMSE - Département Informatique et systèmes intelligents
7 UBFC - Université Bourgogne Franche-Comté [COMUE]
8 Ecole d'ingenieurs Telecom Saint Etienne
Abstract : In Oil&Gas drilling operations and after reaching deep drilled depths, high temperature increases significantly enough to damage the down-hole drilling tools, and the existing mitigation process is insufficient. In this paper, we propose a Cyber-Physical System (CPS) where agents are used to represent the collaborating entities in Oil\&Gas fields both up-hole and down-hole. With the proposed CPS, down-hole tools respond to high temperature autonomously with a decentralized collective voting based on the tools' internal decision model while waiting for the cooling performed up-hole by the field engineer. This decision model, driven by the tools' specifications, aims to withstand high temperature. The proposed CPS is implemented using a multiagent simulation environment, and the results show that it mitigates high temperature properly with both the voting and the cooling mechanisms.
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Conference papers
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https://hal-emse.ccsd.cnrs.fr/emse-02070569
Contributor : Florent Breuil <>
Submitted on : Monday, March 18, 2019 - 10:13:19 AM
Last modification on : Monday, January 13, 2020 - 5:46:07 PM

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  • HAL Id : emse-02070569, version 1

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EMSE | FAYOL-ENSMSE | ISCOD-ENSMSE | CNRS | UNIV-BM | UNIV-BOURGOGNE | LE2I | UNIV-BM-THESE | TDS-MACS | UNIV-ST-ETIENNE | INSTITUT-TELECOM | IOGS | PARISTECH | UNIV-PARIS-SACLAY | UNIV-HESAM | UDL

Citation

Yazan Mualla, Amro Najjar, Olivier Boissier, Stéphane Galland, Igor Tchappi Haman, et al.. A Cyber-Physical System for Semi-autonomous Oil & Gas Drilling Operations. The Third IEEE International Conference on Robotic Computing, Feb 2019, Naples, Italy. pp.1-6. ⟨emse-02070569⟩

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