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Automated operational states detection for drilling systems control in critical conditions

Automated operational states detection for drilling systems control in critical conditions
Automated operational states detection for drilling systems control in critical conditions
Critical events in industrial drilling should be overcome by engineers while they maintain safety and achieve their targeted operational drilling plans. Geophysical drilling requires maximum awareness of critical situations such as “Kicks”, “Fluid loss” and “Stuck pipe”. These may compromise safety and potentially halt operations with the need of staff rapid evacuations from rigs. In this paper, a robust method for the detection of operational states is proposed. Specifically, Echo State Networks (ESNs) were benchmarked and tested rigorously despite the challenging unbalanced datasets used for training. Nevertheless, these challenges were overcome and led to acceptable ESNs performances.
978-2-87419-081-0
Veres, Galina
3c2a37d2-3904-43ce-b0cf-006f62b87337
Sabeur, Zoheir
74b55ff0-94cc-4624-84d5-bb816a7c9be6
Veres, Galina
3c2a37d2-3904-43ce-b0cf-006f62b87337
Sabeur, Zoheir
74b55ff0-94cc-4624-84d5-bb816a7c9be6

Veres, Galina and Sabeur, Zoheir (2013) Automated operational states detection for drilling systems control in critical conditions. At ESANN 2013 ESANN 2013, Belgium. 24 - 26 Apr 2013. 6 pp.

Record type: Conference or Workshop Item (Paper)

Abstract

Critical events in industrial drilling should be overcome by engineers while they maintain safety and achieve their targeted operational drilling plans. Geophysical drilling requires maximum awareness of critical situations such as “Kicks”, “Fluid loss” and “Stuck pipe”. These may compromise safety and potentially halt operations with the need of staff rapid evacuations from rigs. In this paper, a robust method for the detection of operational states is proposed. Specifically, Echo State Networks (ESNs) were benchmarked and tested rigorously despite the challenging unbalanced datasets used for training. Nevertheless, these challenges were overcome and led to acceptable ESNs performances.

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More information

Published date: 24 April 2013
Venue - Dates: ESANN 2013, Belgium, 2013-04-24 - 2013-04-26
Organisations: IT Innovation

Identifiers

Local EPrints ID: 354193
URI: https://eprints.soton.ac.uk/id/eprint/354193
ISBN: 978-2-87419-081-0
PURE UUID: d8ec1c5e-d4fc-4692-bed7-206fc3fd137b
ORCID for Zoheir Sabeur: ORCID iD orcid.org/0000-0003-4325-4871

Catalogue record

Date deposited: 29 Jul 2013 15:57
Last modified: 06 Jun 2018 12:34

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