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Halliburton Collaborates With SDAIA to Use Data Science and AI to Enhance Sustainability, Subsurface Predictions in the Energy Sector

Halliburton Company announced that it has signed a Memorandum of Understanding (MoU) with the Saudi Data and Artificial Intelligence Authority (SDAIA) to address national and global energy challenges with to create data science and artificial intelligence (AI) applications and solutions.

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Through the Artificial Intelligence Center for Energy (AICE), which is a joint center between Ministry of Energy and SDAIA, the collaboration agreement pairs AICE’s significant efforts and resources in the data and AI space with Halliburton’s cloud-first AI and machine learning exploration and production tools along with its solutions that support more sustainable upstream operations. The two groups will share technologies and co-develop innovative solutions to aid in sustainability and subsurface prediction efforts for the oil and gas sector.

“This partnership is part of our efforts to promote advanced technologies in the energy field; our aim is to address hydrogen, hydrocarbons and new energy verticals through data & AI applications and solutions for the country and global market, support expertise exchange, and contribute to building national AI capabilities and competencies in the energy sector, which is among the priority sectors,” said Dr. Majid Altuwaijri, the CEO of SDAIA’s National Center for AI.

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“This agreement allows us to use AI to drive the energy transition in hydrocarbons as well as accelerate the development of new energy verticals such as CCUS,” Eng. Ahmed Al-Zahrani, the Saudi Arabia Ministry of Energy’s Assistant Minister for Development and Excellence, said.

“We are excited to collaborate with SDAIA to use data science and AI to enhance the ways we explore for, develop and produce hydrocarbons,” said Scott Regimbald, vice president, Saudi Arabia and Bahrain. “Our joint efforts will address national and global energy challenges through data and AI applications that will enhance subsurface predictions and create more sustainable solutions for the energy sector.”

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