Oil & Gas Digitization Ramping Up, albeit Slowly

Overview

Various industries have started to take advantage of Industrial Internet of Things (IIoT)-related technologies, such as remote monitoring, advanced analytics, and Big Data. These technologies are helping industry participants automate operations, improve production, reduce costs, and enhance safety.  Long considered slow to change, owner-operators and service companies in the oil & gas industry have also started to implement these technologies and capture the related benefits, and now we see oil & gas digitization slowly ramping up.

These advanced technologies all relate to the trend toward digitization (or “digitalization,” which is essentially the same thing), which can help industrial organizations improve and transform their business operations and processes. Advanced technologies available today are not on-ly helping the industry digitize the vast quantities of data generated, but also to turn this data into actionable insights. 

Digitization offers many potential benefits for improving efficiencies and reducing the costs associated with exploration and production. As the oil & gas industry is adjusting to a new market environment of oil prices hovering at around $50 per barrel, improving efficiency has be-come a top priority for many owner-operators. To this end, digitization brings improvement in many areas, one key among these is asset health and integrity.

Bridging the Digital Gap

A huge data gap exists in the upstream oil & gas and other process industries. Most process industries are asset intensive and generate huge amount of asset data every day. However, most end users struggle to get the most value from their data and find it difficult to manage and model the data. As end users realize that data is becoming critical in today’s competitive environment, they are looking at data analytics to gain an insight into how to best utilize this asset data. End users can take advantage of data analytics platforms to aggregate this data from disparate sources.  They can apply analytical models to predict failures of critical equipment components and use the information to prioritize maintenance activities. Data analytics along with IIoT connectivity and machine learning, are helping end users close this data gap over time and better maintain critical assets.

Digital Twin for Deeper Insight

With digitization, end users now have the ability to produce a digital replica of a particular asset, known as the “digital twin.” A digital twin is virtual representation of a physical asset or a collection of assets working together.  This can include an archive of historical and real-time data, drawings, models, bills of material, engineering and dimensional analysis, manufacturing data, and operational history that can be used as a baseline when benchmarking performance.  A digital twin enables companies to perform simulation, testing, and optimization in a virtual environment before committing actual resources. While this could help any industry save cost, it is especially useful for the oil & gas industry, which depends on large, costly, and often highly instrumented equipment; and even minor project changes can cost millions of dollars.

Assets’ digital information obtained through digital twin can also be combined with other software and technologies for deeper analysis, which could help companies gain deeper insight about asset health so that they can move from reactive to predictive maintenance strategies.  Companies can then proactively plan and maintain assets to optimize their performance and ensure asset integrity.

New Service Models

Advanced IIoT-enabled technologies offer the potential to further improve asset health and performance through new service models. Capabilities, such as remote monitoring and remote services, can help end users leverage the expertise of suppliers to help manage their assets across the entire lifecycle. These new service models are also helping end users move to consumption-based service structures.  Instead of paying for technologies and services upfront, users can pay for the capabilities and services they actually consume. In total, these technologies are helping technology suppliers and users establish a more collaborative relationship.

Recommendations

Owner-operators and suppliers alike in the oil & gas industry should embrace the positive disruptive change brought by digitization.  Automation suppliers should help their customers plan the digitization strategy to integrate legacy assets into the latest IIoT-enabled technology solutions. Automation suppliers should also help end users calculate the ROI justification needed for digitization. 

With digitization, owner-operators now have the opportunity to improve both the performance and availability of assets through remote monitoring, machine learning, analytics, and remote services.  End users should work with suppliers to implement these technologies. With changing end user requirements, suppliers also need to offer more than traditional aftermarket services.  Suppliers should work to expand their capabilities either through in-house research or through partnerships. Various companies have also come together and formed organizations such as Industrie 4.0 and the Industrial Internet Consortium to collectively research and prepare for the IIoT age. 

Struggling with issues such as the current skills shortage, end users are looking for ways to easily maintain their assets.  IIoT can also help fill this skills gap through remote monitoring and remote services.  End users can leverage the expertise of suppliers to help manage critical as-sets across the entire lifecycle. By offering these services, suppliers can enhance their overall project revenues, as well as establish a more collaborative relationship with end users.

To learn how peer organizations are leveraging the latest IIoT-enabled technologies to support their digital transformation, readers should consider attending the upcoming next ARC Industry Forum.

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Keywords: Industrial Internet of Things (IIoT), Digitization, Oil & Gas Industry, Industrie 4.0, Remote Monitoring, Analytics, Machine Learning, ARC Advisory Group.