Development of a Norwegian open-source plug-and-abandonment database with applications
Journal article, Peer reviewed
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Original versionSPE Economics & Management. 2017, 9 (1), 27-31. 10.2118/180027-PA
An estimated 3,000 oil wells need to be plugged and abandoned on the Norwegian Continental Shelf (NCS), with approximately 150 new wells being drilled each year. The petroleum industry estimates the total plugging costs to be almost 900 billion Norwegian kroner (NOK), and that the work will take up to 40 years to complete. Because of the current tax regulations in Norway, the state indirectly pays 78% of the costs (approximately 700 billion NOK). It is therefore vital to reduce expenses by targeted research and development (R&D) of new technology, and to ensure better planning of plug-and-abandonment (P&A) operations in and between licenses. The current study aims to gather available data relevant for Norwegian P&A operations in an open-source database, and to develop and use a P&A planning software that serves as a decision-support tool for various problems operators face. The software can be used to generate planning schedules, identify bottlenecks in P&A operations, and analyze potential efficiency gains from technology improvements and cooperative plugging campaigns. We will use a cross-disciplinary approach that combines the fields of operations research with technological expertise. In this paper, we present the outline of the database and the current status of available data for P&A operations on the NCS, as well as a short literature review. Available data are categorized according to the different choices that need to be made within a single P&A operation, with regard to both technological aspects and the existing regulatory framework. We also discuss the type of analysis the P&A planning software is envisioned to perform. Industry, government, and ordinary tax payers will all benefit from knowledge sharing, optimized planning, and more targeted R&D efforts on this topic. The results from this study will be used to identify important cost drivers and to draw up a roadmap for future P&A-related R&D.