A data-driven probabilistic model for well integrity management: case study and model calibration for the Danish sector of North Sea

Miraglia, Simona (2020) A data-driven probabilistic model for well integrity management: case study and model calibration for the Danish sector of North Sea. Journal of Structural Integrity and Maintenance, 5 (2). pp. 142-153. ISSN 2470-5322

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Official URL: http://dx.doi.org/10.1080/24705314.2020.1746013

Abstract

The correct functioning of well completion in oil and gas facilities is eminently important to assure continuity of production operations together with an adequate safety level. To enhance the performance of production wells and reduce maintenance expenditures, a paradigm shift from corrective maintenance to proactive risk based maintenance is necessary. The feasibility of fully probabilistic risk-based inspection planning approach for oil wells has been investigated as pilot study carried out at Danish Hydrocarbon Research and Technology Centre (DHRTC). After establishing a baseline for the system taxonomy, failure modes and their dependencies on deterioration mechanisms, a data collection and analysis lead to the calibration of a corrosion probabilistic model, based on pit size measured from tubing inspections. This manuscript presents the results of the feasibility study, the calibration of a bespoke corrosion model for wells in the Danish sector of North Sea, the reliability analysis and the identification of a threshold value for the pit penetration to be compared with current oil & gas (O&G) regulations. The model is further used to compare expected maintenance costs for corrective maintenance and condition-based maintenance. Results show how the condition-based maintenance policy results in lower maintenance costs and potential extension of well lifetime.

Item Type: Journal Article
Keywords: Ageing of oil & gas production tubing, corrosion, corrective vs condition-based maintenance policy, life cycle costs
Faculty: Faculty of Science & Engineering
SWORD Depositor: Symplectic User
Depositing User: Symplectic User
Date Deposited: 04 Jun 2020 13:09
Last Modified: 09 Sep 2021 18:53
URI: https://arro.anglia.ac.uk/id/eprint/705599

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