Integration and data maturity are key in this thriving industry
Current data trends show that U.S. energy sector prospects across most of its industries are positive for the coming years.
Global energy consumption will increase through 2050, according to U.S. Energy Information Administration projections. The United States has emerged as a liquefied natural gas (LNG) powerhouse, having exported more than any other country in 2023. And renewables are growing in popularity, in part because of government incentives such as those offered in the Inflation Reduction Act.
Amid these favorable circumstances, Grant Thornton Technology Modernization Principal Will Whatton discussed future-focused energy industry trends during a panel discussion at the Energy Council’s New York Energy Capital Assembly this spring. Whatton discussed topics such as data strategy, maturity and AI; technology optimization in operations and the back office; and the impact that a surge in data center construction will have on the industry.
Here’s a summary of the panel’s observations.
Departmental system integration is essential
Until recently, many energy companies’ functions could operate well in silos. In oil and gas, for example, operations, geology and the back office all might operate independently on different systems without much need for investment in full automation and integration. In some cases, acquired companies were even permitted to operate as standalone entities post-merger.
“Historically, the focus in energy was to optimize each of the individual functions separately. Now the industry needs to work better as a whole across all the different functional areas to drive data visibility and insights across the entire organization,” Whatton said.
By integrating systems across the enterprise, Whatton said, energy companies can find substantial opportunities to create efficiency. For example, having shared IT platforms across the company can simplify tech support while helping functions work together more seamlessly.
To illustrate this at a micro level, one panelist in the discussion described how an oil and gas company had worked to optimize pressure and output for each of its wells individually. But the sum of all the optimized parts wasn’t leading to maximum total output.
When company leaders looked at the concurrency of the pipeline and how multiple wells were related to one another, they realized that they weren’t maximizing their total output because the wells were competing with one another from an operational standpoint.
“As you integrate systems across the entire organization, the cost savings created by optimization can be staggeringly high.”
By viewing output of all the wells together, the company was able to stagger pressure and production between the wells, increasing production by about 20% and decreasing costs by about 50%.
“That’s an example of the benefits of full integration on a small scale,” Whatton said. “As you integrate systems across the entire organization, the cost savings created by optimization can be staggeringly high. And as organizations are looking to increase data visibility and automation with partners, vendors and customers externally, those internal abilities are translating to real external competitive advantages and, ultimately, to market share and value.”
One key to successful system integration is creating a comprehensive data strategy. Energy companies that work to develop consistent, reliable and useful data across all enterprise functions experience the greatest rewards from integration.
One of those rewards is more opportunities to reap the benefits of using artificial intelligence (AI). Grant Thornton's CFO survey for the second quarter of 2024 showed that 94% of finance leaders said their organization is either using or developing use cases for generative AI. But the outputs of AI are only as useful as the data that’s fed into the models.
Meanwhile, Whatton said, energy companies that take advantage of AI and other advanced technology also need to prepare to spend more on cybersecurity as their technology-related risks escalate.
Time for back-office systems optimization
As oil and gas reserves decline, the next optimization frontier for many oil and gas companies is their back-office systems.
Over the last 10 years, Whatton said, energy companies have placed an overwhelming emphasis on optimizing their operations in the field. Understandably, oil and gas companies tend to extract first from their most productive wells, then when those reserves are depleted, companies typically shift operations to less productive wells. To get the most out of these less productive wells, energy companies already have invested in field operations optimization.
AI, machine learning and natural language processing have been incorporated into wells, pipelines, field devices, field techniques and field services. Now that modern technology is in place in the field, energy companies see the back office as the next place they can improve by upgrading technology there.
“Using AI to drive more efficient HR, accounting and tax operations can help oil and gas companies continue to drive improvement now that their field operations are optimized,” Whatton said.
Data strategy is key to ESG disclosures
Although the SEC has put its recent ESG disclosure rules on hold in response to numerous lawsuits, many companies in all industries have begun their compliance journey, anticipating that the rules will eventually take effect.
For energy companies, the greenhouse gas emissions disclosure requirement is one of the most pressing issues related to ESG disclosures. This is another area where effective data quality procedures are foundational for a company to generate accurate disclosure data.
“If you don’t have a solid data strategy backing your reporting, you’re creating compliance risks that could cause you harm if a regulator questions how you arrived at the information you described in your ESG reporting,” Whatton said.
Developing strong, repeatable data procedures and controls at the outset also can reduce the long-term costs of ESG reporting.
Data centers present a revenue opportunity
The substantial energy needs of data centers is creating new opportunities for energy companies to drive revenue.
AI and blockchain are emerging technologies that require huge amounts of computing power and increased energy consumption to run. Whatton said it’s expected that LNG will provide much of the energy for these data centers, which may benefit from the cost effectiveness of being located close to the resource’s extraction point.
“There’s a huge opportunity for revenue and margin for the industry related to the substantial power needs of data centers.”
Dallas-Fort Worth and Austin-San Antonio are listed as two of the key markets to watch in the data center chapter of commercial real estate services and investment company CBRE’s U.S. Market Outlook for 2024.
The anticipated surge in power needs holds promise across the energy industry, from upstream and midstream oil and gas companies to oilfield services to transmission infrastructure companies and power and utilities. Renewables also will see some opportunities; Meta and Google have plans to use solar power to operate new data centers in Mesa, Ariz.
“There’s a huge opportunity for revenue and margins for the energy industry related to the substantial power needs of data centers,” Whatton said. “Moreover, energy companies are in the unique position to get an earlier predictive view on this to forecast and optimize their own power consumption to reduce costs. At the same time, energy companies are going to be the economic engine that powers data center growth. That leads to an opportunity for increased revenue and margins.”
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