By Safiyah Alghamdi and Sharefah Alsultan
SPE-KSA T&PP Team Members
“Can we train machines?”—a question that is considered to be obvious now— was a perplexing dilemma in the 1950s, reflecting the profound advancements in machine learning and artificial intelligence today. These technologies are now crucial, possibly indispensable facilitators of the ongoing energy transition. This query, proposed by Dr. Thamer Alsulaimani, a Lead Reservoir Engineer at Saudi Aramco, framed the opener of the second NMO session, successfully organized by the SPE-KSA Technical and Professional Programs committee. Held on April 30th, this thought-provoking session titled “AI for Net-Zero” brought together industry-leading experts who delved deep into the integration of AI within the energy sector.
The session was moderated by Halah Alasmari, a Senior Geophysicist at Saudi Aramco, and enriched by esteemed speakers from diverse backgrounds including Ibrahim Albaloud, CEO of Fathom.io, Dr. Stephanie Lee, Digital Sustainability Champion at SLB and Dr. Thamer Alsulaimani, Lead Reservoir Engineer at Saudi Aramco. Shedding light on the results of a survey conducted by the NMO team prior to the event (see the full results report below), the session commenced with significant insights about the public perception of AI’s role in achieving net zero emissions. Key findings indicated that 63% of respondents view AI as vital for reaching these environmental goals, particularly in reducing emissions. A notable concern identified was the “lack of expertise,” highlighting a gap in the current digital transformation efforts within the industry. Mr. Albaloud acknowledged these challenges and emphasized the need for increased collaboration between the industry, research and development sectors, and digital service providers to build the needed skills. Dr. Lee discussed the recent efforts at SLB in fostering partnerships and employing AI through Digital Sustainability Platforms, which provide detailed emissions data. This approach underscores a significant shift towards integrating digital tools internally and with clients to foster sustainability.
Dr. Alsulaimani discussed the boundless opportunities AI presents in transforming the industry—enhancing efficiency, minimizing downtime, improving well performance, and aiding in reservoir management decision-making. These benefits underscore AI’s significant market value within the energy sector. To fully harness this potential, Mr. Albaloud suggested that oil and gas companies should focus on developing a data-centric infrastructure. All panelists concurred that robust data infrastructure, coherent governance, and continual acquisition of digital assets are crucial for integrating AI effectively within the industry. Dr. Alsulaimani further highlighted the “Cost of No Action”—the expenses energy companies incur by not adopting AI technologies, which could otherwise propel sustainability goals and solidify energy security. Dr. Lee added that the industry’s extensive data collection could only be fully leveraged through AI, which offers deeper insights into such vast datasets.
Ultimately, the adoption of AI in the rapidly evolving oil and gas sector comes with several pressing concerns, including data security, privacy, and management. Mr. Albaloud reiterated the importance of governance to address these issues and projected that upcoming encryption technologies would likely mitigate many of these concerns. Dr. Lee pinpointed another critical aspect—the potential loss of the human element with mass AI deployment. She emphasized the importance of identifying areas where the human intuition and interaction are irreplaceable.
The discussion concluded with reiterating ways to maximize AI’s potential in aiding the energy transition. The consensus was that training the workforce and establishing a solid foundation in data management—with effective data aggregation, consistent recording, and elimination of bias—are essential. The dialogue was sealed with an agreement that AI is at the forefront of driving the energy transition and is pivotal in achieving net zero goals, affirming its role as a key player in this transformative era.
Anticipating Impact: Insights from the Pre-Event Pulse Survey
Findings from the 400 survey responses indicate that 43% of respondents have intermediate knowledge in Artificial Intelligence (AI) and its application in oil and gas, while 42% consider themselves beginners, and 15% are advanced. On the other hand, 50% of respondents have an intermediate level of knowledge in sustainability in the oil and gas field, while 19% are beginners, and 21% have advanced knowledge.
When asked about the role of AI in achieving net zero emissions in the energy sector, 63% of respondents believe it to be a vital source, and 56% think machine learning is the AI technology with the highest potential in reducing emissions.
Of the 400 surveyed, 40% believe energy efficiency optimization to have the highest utilization rate of AI, while the rest of the respondents, in fifths, believe that each of carbon capture, renewable energy, and emissions monitoring will have the highest rate of applications in AI.
Lastly, respondents were asked what they think is the biggest challenge in implementing AI solutions to achieve net zero emissions in the oil and gas industry. 36% believe it to be due to lack of expertise, while 29% think it is linked to lack of data, and 15% assume that regulatory barriers are the cause, and a third believe it is due to high implementation cost.
