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SLB, TotalEnergies team up on 10-year partnership to develop scalable digital solutions

The partnership initially will focus on subsurface technology for reservoir engineering, as well as geoscience modeling and interpretation. Photo via totalenergies.com

Houston-based energy tech company SLB has forged a 10-year partnership with French energy company TotalEnergies to develop technology aimed at tackling industry challenges such as carbon capture, utilization, and sequestration (CCUS).

“Collaboration and knowledge sharing are key for our industry to continuously develop more effective ways of unlocking energy access,” Rakesh Jaggi, president of SLB’s digital and integration business, says in a news release. “With this visionary partnership, we’re combining the know-how and expertise of both companies to accelerate the delivery of new digital capabilities that will benefit the whole industry.”

The partnership initially will focus on subsurface technology for reservoir engineering, as well as geoscience modeling and interpretation. The subsurface project will feature traditional technology coupled with artificial intelligence (AI).

Namita Shah, president of TotalEnergies’ OneTech business unit, says technology developed with SLB will help the oil and gas sector reduce emissions and dive deeper into geological carbon storage. TotalEnergies’ U.S. headquarters is in Houston.

“Through this digital partnership,” Shah says, “we will develop cutting-edge next-generation software, digital applications, and new algorithms applied to geoscience.”

One day after the digital partnership was announced, SLB said TotalEnergies had awarded a contract to SLB’s OneSubsea joint venture for a 13-well oil project being developed off the shore of Angola by TotalEnergies and two partners. Financial terms weren’t disclosed.

Initial production for the estimated $6 billion deepwater Kaminho project is targeted for 2028, generating up to 70,000 barrels of oil per day. TotalEnergies holds a 40 percent stake in Kaminho.

TotalEnergies owns a number of assets in Texas, including a refinery in Port Arthur. The refinery can produce about 200,000 barrels of oil per day along with low-sulfur fuels.

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A View From HETI

Researchers have secured $3.3 million in funding to develop an AI-powered subsurface sensing system aimed at improving the safety and efficiency of underground power line installation. Photo via Getty Images

Researchers from the University of Houston — along with a Hawaiian company — have received $3.3 million in funding to explore artificial intelligence-backed subsurface sensing system for safe and efficient underground power line installation.

Houston's power lines are above ground, but studies show underground power is more reliable. Installing underground power lines is costly and disruptive, but the U.S. Department of Energy, in an effort to find a solution, has put $34 million into its new GOPHURRS program, which stands for Grid Overhaul with Proactive, High-speed Undergrounding for Reliability, Resilience, and Security. The funding has been distributed across 12 projects in 11 states.

“Modernizing our nation’s power grid is essential to building a clean energy future that lowers energy costs for working Americans and strengthens our national security,” U.S. Secretary of Energy Jennifer M. Granholm says in a DOE press release.

UH and Hawaii-based Oceanit are behind one of the funded projects, entitled “Artificial Intelligence and Unmanned Aerial Vehicle Real-Time Advanced Look-Ahead Subsurface Sensor.”

The researchers are looking a developing a subsurface sensing system for underground power line installation, potentially using machine learning, electromagnetic resistivity well logging, and drone technology to predict and sense obstacles to installation.

Jiefu Chen, associate professor of electrical and computer engineering at UH, is a key collaborator on the project, focused on electromagnetic antennas installed on UAV and HDD drilling string. He's working with Yueqin Huang, assistant professor of information science technology, who leads the geophysical signal processing and Xuqing Wu, associate professor of computer information systems, responsible for integrating machine learning.

“Advanced subsurface sensing and characterization technologies are essential for the undergrounding of power lines,” says Chen in the release. “This initiative can enhance the grid's resilience against natural hazards such as wildfires and hurricanes.”

“If proven successful, our proposed look-ahead subsurface sensing system could significantly reduce the costs of horizontal directional drilling for installing underground utilities,” Chen continues. “Promoting HDD offers environmental advantages over traditional trenching methods and enhances the power grid’s resilience.”

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