Digital Twins in the Oil and Gas Industry

By Kranthi Kumar Buddha, acuvate

A digital twin is a virtual copy of the physical on-field asset, such as pumps, compressors, turbines, and pipelines.

For the concept of digital twins to work, it is vital to have updated, real-time operational data around assets. While cloud computing, advanced analytics, and AI have brought about significant transformation in the industry, a digital twin is of no use without access to a centralized data repository that contains all asset-related information.

Building a digital twin is an algorithmic process. For starters, a 3D model is created and then tagged with all necessary information, such as layout, geometry, schematics, engineering, and design information that has been collected from disparate sources. This common data set is shared across various departments, including engineering, procurement, and operations. As the digital asset is updated automatically with all current operational and maintenance data, an operator can easily search the data tag and bring up the latest work information on asset health and performance. Failures or production outages at this stage are addressed early, thus ensuring preventative rather than reactive maintenance, prolonging asset life, and decreasing maintenance costs in the process.

1. Oil field monitoring and predictive maintenance

As discussed above, by identifying issues beforehand, digital twins help in predictive asset maintenance, thus reducing unplanned downtimes and optimizing the cost of maintenance.

Predictive analytics leverages digital twins to monitor on-field equipment performance and create unique asset signatures that include information such as ambient and operational conditions and past loading. Real-time data is then compared to these models to identify any deviations in patterns and early-warning notifications, preventing major breakdowns and ensuring reliability in operations.

2. Modeling real-life drilling scenarios to determine equipment feasibility

Digital twins help model real-life drilling scenarios to determine the feasibility of equipment. By watching out for potential issues and problems, operators can enhance equipment efficiency and reduce well construction costs. Digital twins also enhance geothermal drilling activities and reduce overall well construction time while augmenting scheduled rig moves, well services, etc.

3. Conducting dynamic simulations to arrive at optimal production workflows

Digital simulations help enhance “run-the-simulation” processes, helping workflow designers identify where and how things should go before they are physically deployed.

Data simulations and analytics, integrated within digital twins, examine current workflows, help in pre-deployment planning and workflow analysis, and provide workable alternatives to production processes when problems arise.

4. Optimization of production through digital twins

Digital twins help optimize oil and gas production by providing data insights across five different stages, namely:

Organization and execution of the computerized maintenance management system (CMMS)

Improvement in asset reliability

Manage information configuration

Optimize operational insights

Lifelong asset maintenance and management (evergreen digital twins)

5. Data integration for intelligent asset management

Intelligent asset management involves getting data from multiple data sources, including SCADA, remote sensing, subsurface surveillance data, etc., thus involving the integration between internal and external systems and back-office operations.

Physical asset management through digital twins, therefore, not only requires real-time maintenance but measuring asset performance under various “whatif” scenarios. Moreover, it minimizes the cost associated with traveling to and from the field to

Rockwell partnered with Microsoft’s IoT services to proactively manage its oil and gas assets. Rockwell uses the IoT platform to monitor the variable speed motors of its pumps from its command center in Ohio. The company can then proactively identify issues in real-time, saving up to $300,000 of production per day a malfunctioning pump could otherwise cost.

6. Maintaining tacit enterprise knowledge using digital twins.

The average age of employees in the O&G industry is 56 years, and they will be eligible for retirement in the next decade, thus threatening the industry with a critical skills shortage.

By maintaining a centralized repository of asset information, the concept of digital twins helps achieve operational efficiency and reduce the cost of operations by eliminating the need for hiring costly personnel.

7. Increased workplace safety

Smart wearable IoT devices such as smart watches, biometric vests, and Bluetooth tags help monitor workforce activities, track operator location, create awareness of workforce fatigue, and get access to critical information on the plant floor.