Next step for the digital oilfield
Oil and gas companies have done an excellent job of incorporating technology into their equipment and processes. In fact, oil and gas companies have been at the forefront of implementing a strong data collection infrastructure for years. The digital oilfield was born out of that push. This transformation is about harnessing technology to create a more efficient and profitable operation, but bold corporate objectives are not fully being met. Oil and gas companies continue to struggle properly harnessing the data they are collecting. They have the sensors in place, and data is coming in, but production efficiency still is not where it should be. While data is being stored in huge lakes, it has not been properly utilised to work toward solving tangible problems.
Today, oil and gas companies are transitioning from worrying about collecting data toward trying to figure out how to use it to accomplish business objectives. How does a business harness the data it is collecting to make a well more efficient and reduce its downtime? This is where artificial intelligence (AI) and predictive and prescriptive analytics come in.
Analytics, more specifically predictive and prescriptive analytics, are the answer to utilising the massive amounts of data being collected and underused. Analytics software, such as the AnalyticsOS™ (AOS) platform offered by Lone Star Analysis, takes data inputs, environmental conditions and human judgement and uses them to accurately predict future operating conditions. The software uses cause and effect logic, evaluates system aspects and monitors system production efficiency to provide performance predictions and prescribe preventative actions that should be taken. Optimising production and reducing downtime are direct results of implementing these solutions and can ensure oil wells are increasingly more productive overall.
Unmanned underwater vehicles in the offshore space
Unmanned underwater vehicles (UUVs) are becoming increasingly important and useful in the maintenance and repair of offshore wells. As the industry moves away from tethered UUVs, increased connectivity range and battery life enables them to dive deeper for longer, and their ability to spot and fix problems or potential equipment issues also increases. With this increased UUV uptime and productivity, there needs to be an increase in autonomy from drone operators for some tasks. This autonomy is vital in enabling the operators to focus on experience-based assessments while the UUV continues its search for additional issues. The technology for increasingly self-reliant UUVs is still developing, but the potential is enormous from an efficiency standpoint. UUV autonomy is fuelled by AI and analytics software. It allows for maximum efficiency since operators do not have to constantly monitor the drone to identify issues manually, and can hyper-focus their attention toward issues that humans are uniquely qualified to address. Currently, many UUVs are manually operated by an onsite professional, but as technology evolves, these vessels will increase in value as they move toward greater automation.
One huge problem with the status quo is the time and cost required for humans to be on site for inspection, service and equipment repair, especially in the offshore environment. In direct costs, flying a UUV operator onsite incurs thousands of dollars in hard costs. Indirectly, each hour a rig is offline waiting for personnel or repairs, tens of thousands of dollars are lost. This is where the marriage of AI, analytics and connectivity is changing the game. Oceaneering has partnered with Lone Star and others to remedy the high costs of onsite personnel and streamline the use of UUVs for maintenance and repair. The objective is to eliminate the need for onsite UUV operators and to provide real-time access, command and control, and prescriptive analytics remotely.
One enabling technology at the project’s core is Satellite Agnostic Intelligent Link (SAIL) technology. SAIL technology uses automatic beam switching to ensure UUVs never lose connection and can stay productive while below the surface. Most importantly, UUVs are able to remain in constant contact with their offsite operators, maintaining a seamless camera feed throughout the process. This technology was tested, proven and demonstrated to potential customers at the NASA Neutral Buoyancy Lab (NBL) in Houston in fall 2018. As one of only two such deepwater research labs in the world, NBL offers a unique environment to perform live tests of UUVs.
Figure 1. Oceaneering and Lone Star Analysis demo SAIL technology on UUVs at the NASA Neutral Buoyancy Lab.
The other side of this technology solution is the AI and analytics driving the UUV’s intelligence. As previously mentioned, the amount of data coming from UUVs is ripe for utilisation and can be used for a host of AI applications. This means that a UUV can smartly navigate to the higher risk areas on a well on its own to find and remedy potential issues. The offsite UUV operator can then focus on important decisions that affect safety or items that require immediate repair while the UUV smartly searches for more potential problems. The human operator and AI-enabled UUV play off each other’s strengths to multiply their overall productivity. UUVs can also automatically alert operators and technicians when they are experiencing a component fault. Employing this approach across networks of wells and oil field assets has significant benefits for reduced downtime and enhanced efficiency across the board.
Improved logistics – in terms of both people and equipment – is one of the key outcomes to target. Aligning the transportation of operators, maintainers and parts with the real-time needs of the rig is a massive boon. This means inspections and maintenance can happen quicker, more predictably and at a much lower cost. The quality of life for these specially trained operators also increases with less travel to remote oilfields and a quantified future schedule to plan around.
Philosophically, automation and removing people from well sites is a contentious issue for some in the industry. While this approach may seem to prioritise cheaper alternatives such as UUVs that harness technology, it can also be argued that it ultimately makes the oil patch more cost-effective and allows specialised workers to focus on tasks that require greater care and expertise than a UUV can provide. Using this technology will also make wells more efficient and productive, meaning oil companies have a more attractive cost structure to explore additional wells in the future. It’s likely that the implementation of this technology will help make the industry more resilient to volatile oil and gas markets, stabilising jobs during downturns and allowing for much faster expansion during growth cycles.
This is part one of a two-part article. Part two will be available shortly.
Written by Eric Haney, Lone Star Analysis.
Read the article online at: https://www.oilfieldtechnology.com/digital-oilfield/26062019/a-new-age-part-one/
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