Organizational Over Technology: Why Digital Twin Adoption in Oil and Gas Stalls—A Review and the Case for Mechanism Design

A literature review of ten peer-reviewed articles published between 2018 and 2025 examines the adoption of digital twins in the oil and gas sector. According to Meza et al. [1], 68% of the implementations are digital shadows, which involve one-way data flow, 18% are digital models, and only 14% are actual digital twins with bidirectional feedback. Wanasinghe et al. [2] noted that 88% of the published work comes from the industry, with 95% related to the supply chain and 5% from operators, while 12% of the studies are from academic institutions. Furthermore, only 7% of the research involves collaboration between industry and academia (Meza et al. [1]). The lack of standardization and data silos are identified as the major obstacles in six studies each. Pandi [3] highlights a persistent "broken chain" in data transfer that has persisted for more than two decades, emphasizing that errors in 10% of engineering work can significantly impact 90% of costs. Only three papers present specific quantitative outcomes: Shen et al. [4] reported a 5.41% increase in efficiency across 35 oil wells, while LeBlanc [5] modeled a net present value of $211 million over 27 years. These findings suggest that the main limitation is organizational rather than technological. Theoretical frameworks, especially those developed by Professor Jun Cai on incentive-compatible mechanisms for distributed systems, provide a foundational approach for tackling governance issues. Future studies should focus on applying these mechanism design concepts within the specific institutional environment of digital twins in the oil and gas industry.