Dynamic risk-based safety analysis of permanent well plugging and abandonment operations

Ahmed Babaleye, Mahdi Khorasanchi, Rafet Emek Kurt

Research output: Contribution to conferencePosterpeer-review


Well plugging and abandonment, P&A is the first operation to be addressed after a decision has been made to cease production during the decommissioning phase of oil and gas installations. Well P&A operation can be very costly with associated number of uncertainties. The operation is time-dependent as the physical and design parameters can change rapidly. Many of the present risk analysis of Well P&A operations have focused on planned risks based on expert judgement but not on evolving risks during the various stages of the operation. The present work is aimed at demonstrating the application of a dynamic risk approach in conducting a probabilistic risk analysis of well P&A. The dynamic risk analysis is based on analysing failure scenarios using Bow-tie, BT and mapping the BT model onto a Bayesian Network, BN. The BT model has proven to be an effective quantitative risk analysis tool but falls short to handle conditional probabilities and probability updating, both of which, are within the capability of the BN. Through sensitivity analysis, the BN takes into account probability adapting using accident precursor data and updating the probability data when knowledge of the risks associated with the well P&A operation increases.
Original languageEnglish
Publication statusPublished - 15 Nov 2017
EventSPE ICoTA 23rd European Well Intervention Conference - Icota Europe - AECC, Aberdeen, United Kingdom
Duration: 15 Nov 201716 Nov 2017


ConferenceSPE ICoTA 23rd European Well Intervention Conference - Icota Europe
Abbreviated titleSPE ICoTA
Country/TerritoryUnited Kingdom
Internet address


  • decommissioning
  • experience Learning
  • Bayesian network
  • dynamic safety assessment
  • Well P&A


Dive into the research topics of 'Dynamic risk-based safety analysis of permanent well plugging and abandonment operations'. Together they form a unique fingerprint.

Cite this