Manufacturers and producers are rethinking longstanding business practices to take advantage of rapidly advancing technologies—especially where downward price pressures have forced this rethinking. At CERAWeek 2018, Emerson’s Arshad Matin joined a panel discussion, Digitalization and Oil & Gas: What’s next? IHS Markit’s Judson Jacobs moderated the panel and was also joined by leaders from Shell, PETRONAS, Accenture and Maana. Here was the panel’s focus:
While it’s clear from industry announcements that oil and gas is fully embracing a more digitalized approach to its business, it’s less clear what this means in practical terms. Which segments of the oil and gas value chain are most ripe for digital disruption? Are digital and automation technologies raising performance and enabling new operating models? What is the role of partnerships in both developing solutions and ensuring organizational uptake? How is digitalization improving the bottom line?
Judson opened by noting many technologies are involved in digitalization including artificial intelligence, machine learning, the Industrial Internet of Things, the cloud and analytics. He asked the panel to bring their perspectives to where the potential for value for oil & gas producers. The focus needs to be on value and not novelty.
The stress of low oil prices over the last several years has forced oil & gas companies to rethink everything from work processes in exploration through custody transfer down the supply chain.
Arshad focused his remarks around the subsurface. It must be right to make the value work across the rest of the supply chain. The island of subsurface knowledge can be integrated to connect with knowledge at the well surface to better optimize the flow from the reservoir and maximize its life. The more these islands of data sets can be brought together, the better the picture of what can be done to operate the wells over their lives.
An effective digital transformation involves getting the culture right, getting all players to use the common systems and tools, and making sure the changes in fact simplify and streamline instead of adding complexity.
Arshad explained that machine learning should be physics based. The physics-based models are being injected with machine learning and surface data. Many of the tasks have been automated to make the reservoir models more accurate and more detailed. There is real risk of the industry spending lots of money building platforms. The value really comes from applications solving specific problems, not in the platform itself. Applying analytics and physical models can apply value quickly, building platforms take a long time with the value coming in later.
The path to digitalization begins in the planning phase in greenfield projects to build the digital twin along with the physical production site. Often project teams are separate from operational teams and decisions made are specific to the project, which is just a blink of the eye is the lifespan of the operating facility. The decisions should be made with the entire lifecycle in mind to operate with the highest level of safety, efficiency and reliability possible.
You can learn more about Emerson’s Paradigm Exploration and Production software and its role in bridging the knowledge between subsurface and surface data sets to optimize oil & gas production.