Digital twins in the Oil & Gas industry
The article introduces the complex cost and need for asset and visibility in oil & gas operations before introducing the idea of preventative maintenance and digital twins.
The article very briefly outlines seven use case studies.
- Oil field monitoring and predictive maintenance
- Modeling real-life drilling scenarios to determine equipment feasibility
- Conducting dynamic simulations to arrive at optimal production workflows
- Optimization of production through digital twins
- Data integration for intelligent asset management
- Maintaining tacit enterprise knowledge using digital twins
- Increased workplace safety
Like many articles on digital twin benefits, the opinion concludes with non-quantified ROI benefits.
The use cases of digital twins in the oil and gas industry offer several benefits as follows:
- Increased yield
- Reduced unplanned downtime
- Improve workforce efficiency
- Real-time monitoring
- Improved decision-making
- Discover additional avenues for profit-making and uplift
Why it’s relevant to Nextspace
Despite its brevity this article is interesting for Nextspace as a quick checklist of potential goals to select as your early MVP wins.
Therefore, some points to note:
- Predictive maintenance. Requires on-field performance and operational condition data, as well as analytics to establish parameters and identify deviations.
- Real-life drills. Imagined in the article as requiring augmentation (AR / VR) but can be done with mobile alerts or other system integrations.
- Dynamic simulations. Requires process digitization, workflow analysis and data simulations and analytics.
- Optimizing production. Requires five step process requiring organizational buy-in and data maturity.
- Intelligent asset management. Requires integration of internal and external systems and data, real-time data flow in the digital twin and the ability to conduct “what-if” scenarios.
- Tacit (or institutional) knowledge. Requires access to and buy-in from system experts.
- Workplace safety. Requires new hardware such as IoT wearables and cameras.
Digital twins are a journey.
You cannot achieve all use cases at once so each journey must be structured according to the specific customer’s business objectives, issues and context.
