Dataset for estimating occurrence probability of causations for plugged, abandoned and decommissioned oil and gas wells

Ahmed Babaleye; Rafet Emek Kurt; Faisal Khan

doi:10.1016/j.dib.2020.105988

Dataset for estimating occurrence probability of causations for plugged, abandoned and decommissioned oil and gas wells

Data Brief. 2020 Jul 5:31:105988. doi: 10.1016/j.dib.2020.105988. eCollection 2020 Aug.

Authors

Ahmed Babaleye¹, Rafet Emek Kurt¹, Faisal Khan²

Affiliations

¹ Department of Naval Architecture, Ocean and Marine Engineering, University of Strathclyde, Glasgow, United Kingdom.
² Centre for Risk, Integrity and Safety Engineering (C-RISE), Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL A1B 3X5, Canada.

Abstract

This article contains the dataset on the failure frequencies of the barrier and mechanical plugs in place within the hydrocarbon-containing wellbore during plugging and abandonment operation. The interpretation and application of this data can be found in the research article ("https://doi.org/10.1016/j.psep.2019.09.015" Babaleye et al., 2019). These datasets were collected through a comprehensive hazard identification technique workshop involving 10 engineers and academics with considerable years of field experience. The data were collected based on how likely it is for each causation to occur and these likelihoods are ranked from 1 to 10. The process is experience-driven and is complemented by a 1-10 rating of the duration of leak of hydrocarbon before remediation, should the leak reach the mudline. The ranked data was a representative of raw failure data (failure rate or mean time to failure (MTTF)) for each causation and are coded in MATLAB using gamma distribution based on hierarchical Bayesian analysis. The dataset offers unique opportunity for reuse due to its accessibility and discreteness.

Keywords: Decommissioning; Failure analysis; Hierarchical Bayesian model; Well plugging and abandonment.