4. Oil and gas
Edge use cases
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Introduction
Edge computing as a Service improves economics for the oil and gas industry
Bringing applications to the data reduces costs, increases margins, and enhances safety
Technology is the cornerstone of the oil and gas industry; however, as new emerging technologies are incorporated, more data is generated and managing enormous volumes of data becomes an impediment to efficient operations. This situation has led many organizations to use the cloud as a repository; but while the cloud offers some advantages in terms of data storage, it does not help with critical real-time decision-making. Companies need faster data access than the cloud can provide, and that means massive amounts of vital operational data must move from the cloud to the edge.
The volatility of the oil and gas industry is a constant challenge, and managing the highs and lows is a balancing act that no company in the industry has truly mastered.
Unfortunately, investors are not interested in the challenges. They are interested in performance. And they judge companies and make investment decisions based on an organization’s profitability and safety records.
The world’s most valuable resource is no longer oil, but data. -- The Economist
The constantly changing playing field makes it more difficult for oil and gas companies to achieve consistent financial and safety goals, and this cyclicality is not likely to change. To be competitive, companies need to navigate the recurring highs and lows to better mitigate investment uncertainty.
Improved data management is at the heart of the solution.
The reality of data overload
In recent years, oil and gas (O&G) companies have been encouraged to rethink data storage. The scale of data growth is the motivator. The volume of data generated from O&G operations is growing at an astronomical rate, and this has led many organizations to move away from storing data centrally to storing data in the cloud.
In short, the speed and volume of data generation and capture has created a new business model. Today, there are vast data lakes holding the full range of operational information from personnel data to production results, and it is no longer practical to store these data locally. The problem is that sending this enormous flow of data to the cloud places potentially useful information out of reach.
In addition to impeding access, cloud storage can be time consuming. A typical rig can have 30,000 sensors that gather data 24 hours per day, seven days a week. Depending on how data is processed on the asset, a single day’s worth of data can take as many as 12 days to reach the cloud.
In an industry where real-time decisions are vital to operational safety and productivity, this model does not make sense. The time it takes to query the cloud to get insight from the massive jumble of data stored there precludes rapid decision-making, which makes using cloud storage not only impractical but potentially counterproductive.
The ability to extract actionable intelligence from real-time data can deliver gains across the board, but storing data in the cloud is an impediment, not an expedient.
It is clear that companies need a better way to access essential data to realize improved performance.
The value of data democratization
What is needed is technology democratization, a way to rapidly make technology more accessible to more people, providing easy access to technical and business expertise. This requires simplification.
Apple accomplished this in a progression that took users from DOS to Macintosh, Walkman to iPod, home movie to iMovie, and cell phone to smartphone. Amazon’s AWS has a similar story, with a transition from the broadly implemented client-side server to the cloud. The fact that AWS grew its offerings by more than 75 times in the span of a single decade underscores the value of this approach.
For businesses, Salesforce did something comparable with a practical business application that revolutionized customer relations, moving from the paper files stored on a Rolodex to CRM and eventually to the connected customer.
Edge Computing can change access to data in an equally impactful way, potentially transforming the way companies store, access, and utilize information.
The building blocks of a better solution
Edge Computing is foundational to improving access to data because it provides opportunities across the upstream value chain. Using edge technology helps companies harness data from critical equipment and processes, quickly add smart capabilities, gain operational insight, and improve reliability to improve performance and safety.
In simple terms, Edge Computing provides a way to collect and process data at the farthest point of a network by using local data storage to cut the lag time that is experienced when data is moved back and forth from the cloud. This approach allows data to be managed without the need for massive bandwidth.
Edge-as-a-Service computing platforms do not need IT specialists on site for support. They can be managed remotely and can use software from any vendor, which simplifies software deployment and lowers the cost of ownership. With this approach, it is possible to monitor and control critical equipment without dealing with data transfer delays, and as operations change and more data feeds are introduced, the system can be easily scaled.
Edge capabilities improve access to Industry 4.0 capabilities and deliver improved reliability to remote and low-staffed assets that are high value and mission critical.
The value of the edge is that it provides remote, onshore and offshore assets with small crews greater access to operational data to improve operations and accelerate innovation.
- Exception-based field management
- Predictive maintenance
- Flow assurance
- Artificial lift optimization
- Surveillance for safety and theft prevention
- Field worker support and safety
- Emissions monitoring
- Logistics and asset optimization
- Well construction and operational performance
How edge as a service works
Edge-as-a-Service (EaaS) takes Edge Computing to the next level, giving companies a way to capture the benefits of Edge technology and eliminating the costs associated with conventional on-site technology.
When traditional field systems fail, an engineer is dispatched to troubleshoot the problem and restore service. This normally includes the cost of last-minute airfare, a rental car and hotel and a per diem allowance. Once the technician reaches the site, it takes about a day to merge and update the data- base. If all goes well, the technician spends approximately 2.5 days to resolve a single issue at a cost of around $2,800. Every time a problem arises, the owner incurs a similar cost. Remote provisioning and management using EaaS reduces downtime, delivering value to the bottom line.
The easiest way to understand EaaS is to think of it as an “unserver.” It is an infinitely scalable solution that allows for on-site data crunching without a big data closet. Instead of storing a massive volume of data in the cloud, EaaS provides immediate access to essential data and sends the rest of the data to the cloud for storage.
EaaS is a cloud-like infrastructure that is:
- Set up and ready to use in minutes
- Available 24/7 (with a battery backup included in the system)
- Infinitely scalable
- Predictably priced
- Cost-free to upgrade.
- No hardware or software to buy or maintain
- Technology agnostic
- Platform flexible
- Minimal installation
- Rapid deployment
- Powered by patented technology
- Future-proofed against obsolescence
- No specialized training
Transitioning to EaaS pays off
In recent years, oil and gas (O&G) companies have been encouraged to rethink data storage. The scale of data growth is the motivator. The volume of data generated from O&G operations is growing at an astronomical rate, and this has led many organizations to move away from storing data centrally to storing data in the cloud.
In short, the speed and volume of data generation and capture has created a new business model. Today, there are vast data lakes holding the full range of operational information from personnel data to production results, and it is no longer practical to store these data locally. The problem is that sending this enormous flow of data to the cloud places potentially useful information out of reach.
In addition to impeding access, cloud storage can be time consuming. A typical rig can have 30,000 sensors that gather data 24 hours per day, seven days a week. Depending on how data is processed on the asset, a single day’s worth of data can take as many as 12 days to reach the cloud.
In an industry where real-time decisions are vital to operational safety and productivity, this model does not make sense. The time it takes to query the cloud to get insight from the massive jumble of data stored there precludes rapid decision-making, which makes using cloud storage not only impractical but potentially counterproductive.
The ability to extract actionable intelligence from real-time data can deliver gains across the board, but storing data in the cloud is an impediment, not an expedient.
It is clear that companies need a better way to access essential data to realize improved performance.
75% of organizations don’t expect to achieve the full potential of their IoT due to a lackof data science specialists. -- Gartner
Companies that have implemented this approach have been able to reduce the field head count by 80%, allowing them to lower costs and at the same time improve safety and mitigate risk while also identifying which service providers and contractors were responsible for the majority of incidents and downtime.
Flow assurance is an aspect of midstream operations that also can benefit from EaaS. Locally avail- able data can be analyzed to identify the reasons for flow disruptions to better manage line maintenance. Knowing whether flow issues are the result of contaminants, waxes, hydrates, or equipment issues allows for specific maintenance services to be secured. And in an environment that is not conducive to bringing new pipelines online, the ability to maintain optimal flow puts companies in control of their assets and enables insights that make it possible to add customers to existing lines for increased throughput and revenue.
For companies implementing digital twin technology, using EaaS to gather operational data improves models by providing accurate, quality, timely information to be used. Using current, clean, filtered, processed data eliminates the garbage in/garbage out conundrum and allows companies to derive the best value from the twin.
EaaS also makes it easier to track key performance indicators for ESG because it improves the ability to monitor and manage emissions. Gathering flare data, for example, not only provides insights into greenhouse gas emissions, but it also lays the foundation for artificial intelligence (AI) and machine learning (ML) to be implemented to measurably improve environmental stewardship. More importantly, it allows these gains to be achieved without human intervention.
87% of utility executives believe technology democratization is becoming critical in their ability to ignite innovation across their organization. -- Accenture
Edge computing is mission critical
While the cloud clearly has value as a vast storage space, it cannot enable the day-to-day operational and safety improvements that EaaS makes possible. Edge Computing delivers value across the board because it puts more data and more power in the hands of decision-makers to improve safety and economics in oil and gas operations.