Energy transition outlook 2019, oil and gas

DNV GL’s crystal ball sees oil demand peaking in the mid 2020s as gas takes over as the world’s main energy source. A peek into the digital future of oil and gas sees further de-manning supported by robotics and AI. 3D printing, drilling automation, wired drill pipe and wearables will also come to the mainstream. Maybe!

DNV GL’s Energy transition in oil and gas is a spin-out of its global 2019 Energy Transition Outlook (ETO), a comprehensive 296-page report on the global energy transition out to 2050. The shorter (96 page ETO oil and gas (ETOO&G) edition uses the same data and DNV GL’s ‘system dynamics feedback model’, implemented with ISEE Systems’ Stella modelling tool. DNV GL is forecasting oil demand to peak in the mid-2020s, at which time the world’s largest source of energy will be natural gas. While DNV GL’s production forecasts are model based, the chapter (in the shorter ETOO&G) on the digital transformation of the oil and gas industry is more of an editorial.

ETOO&G envisages the impact of digital in de-manning, enabling new lower-carbon concepts, such as subsea, rather than fixed, platforms and by enabling new manufacturing solutions, such as additive manufacturing. Much of DNV’s digital forecasting for oil and gas is spun into a green, lower carbon scenario.

De-manning will involve inspections by autonomous robotics supported by advanced sensors and machine vision. Embedded memory and communications systems will report live status from remote locations to a central onshore hub. Other digital goodies to come include subsea Wifi and the subsea IoT and all-electric topsides, taking power from offshore renewable sources. The autonomous supply vessels concept is ‘rapidly moving closer to reality’.

Advances in standardization (it would be good to know what these will be!), and the reuse of elements of past asset designs, will help to simplify requirements and improve the efficiency of the design process. 3D design will replace 2D and construction will become more automated and integrated. Advanced modelling tools will run scenarios to derive optimum manufacturing solutions that consume less material. Possibly leveraging technology from DNV GL’s own Additive Manufacturing Technology Centre of Excellence in Singapore. Wearables will provide high-speed access to remote experts worldwide. Virtual and augmented-reality training will improve inspection and maintenance activities. Data analytics will ‘continue to optimize subsurface mapping of the optimum drilling locations, indicating how and where to steer the drill bit and suggesting the best way to stimulate the reservoir’. Greater gains will come through wider deployment of smart drill pipe that report downhole conditions via fast, reliable telemetry. Robotic drilling systems that respond to downhole data ‘are on the way’ and will increase the safety and efficiency of drilling operations.

What key technology will underpin the oil and gas digital transformation? You guessed it, the cloud. On-site computing and storage is shifting to become fully cloud-based based. Industry platforms will enable collaboration, such as sharing data and tools/apps. Breaking down traditional functional silos is vital. The most powerful impact on projects and operations come when leading subject-matter expertise is combined with data analytics, information management and real-time control to optimize operations and maintain safety. DNV opines that there is significant potential for the industry to share data across projects and operations, using cloud-based data platforms such as its own Veracity. And of course, AI and machine learning will ‘supplement’ human interpretation. ML will focus on high probability, low-consequence scenarios, of which there are many in the oil and gas sector. Finally, digital twins will enable communication between different types of models. Supply-chain companies will incorporate and test their designs directly into a digital twin master. Here again, DNV GL is working on a ‘virtual offshore platform’ that will provide up-to-date information throughout the asset’s lifecycle for multiple purposes including asset health monitoring risk barrier management, spare parts and performance analytics. Elements of the digital model will be used to produce physical components, using advanced manufacturing techniques (as above) located at the physical asset.

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