Development of a Probabilistic Framework for Risk-Based Well Decommissioning Design

Abstract

Summary In the next decades, tens of thousands of well plugging and abandonment (P&A) operations are expected to be executed worldwide. Decommissioning activities in the North Sea alone are forecasted to require 2,624 wells to be plugged and abandoned during the 10-year period starting from 2019 (Oil&Gas_UK 2019). This increase in decommissioning activity level and the associated high costs of permanent P&A operations require new, fit-for-purpose, P&A design tools and operational technologies to ensure safe and cost-effective decommissioning of hydrocarbon production wells. This paper introduces a novel modeling framework to support risk-based evaluation of well P&A designs using a fluid-flow simulation methodology combined with probabilistic estimation techniques. The developed well-centric modeling framework covers the full range of North Sea P&A well designs and allows for quantification of the long-term (thousands of years) evolution of hydrocarbon movement in the plugged and abandoned well. The framework is complemented by an in-house visualization tool for identification of the dominant hydrocarbon flow-paths. Monte Carlo methods are used to account for uncertainties in the modeling inputs, allowing for robust comparison of various P&A design options, which can be ranked on the basis of hydrocarbon leakage risks. The proposed framework is able to model transient conditions within the well P&A system, allowing for the development of new key performance indicators (e.g., time until hydrocarbons reach surface and changes in hydrocarbon saturation within the P&A well). Such key performance indicators are not commonly used, because most published work in this area relies on steady-state P&A models. The developed framework was used in the assessment of several P&A design cases. The results obtained, which are presented in this paper, demonstrate its value for supporting risk-based decision-making by allowing for quantitative comparison of the expected performance of multiple P&A design options for given well/reservoir conditions. The framework can be used for identifying cost-effective, fit-for-purpose P&A designs, for example by optimizing the number, location, and length of wellbore barriers and evaluating the effectiveness of annular cement sheath remedial operations. Additionally, this framework can be used as a sensitivity analysis tool to identify the critical parameters that have the greatest impact on the modeled leakage risks, to guide data acquisition plans and model refinement steps aimed at reducing the uncertainties in key model parameters.