In Part 2 of a two-part interview with Oil Review Middle East, Dany Rahal, SLB's head of digital for MENA, shares his insights on the transformative impact of AI and digital technologies in the oil and gas sector, AI adoption in the Middle East and the next evolution of AI
Having first worked in the Middle East in 2014, SLB’s Dany Rahal was pleasantly surprised at the progress the region has made in digital and AI adoption on his return to the region in 2022 as SLB’s head of digital for MENA.
“Back in 2014, talking about cloud to national oil companies in the Middle East was not something that could be easily discussed,” he recalls. “Today, all the global hyperscalers are in the region – Microsoft, Google, AWS. The pace of investment from corporates and governments into digital and AI specifically, is increasing. Tech companies are coming into this space in the Middle East very, very fast. Now we can compare the region, in terms of adoption, to the US and China."
Nowhere is the opportunity greater than in the oil and gas sector, where AI and machine learning are transforming operations and helping operators to address their industry challenges.
“Our customers today want to reduce cycle times, reduce risks, increase returns and improve productivity. They want to reduce and optimise costs, and reduce emissions,” Rahal says. “These are the challenges. AI and ML today are revitalising industries worldwide, not just the energy sector, and we have a great opportunity in the energy and oil and gas sector to apply these technologies to bring value. For example, in terms of accelerating field development, planning, reducing operational risks around drilling, automating mundane, repetitive tasks and enabling production uptime.”
Key role of data
Rahal notes here the key role of data as the foundation for AI and Gen AI. “You cannot have a successful AI or GenAI implementation unless you have a clean data foundation that is ready to be consumed by AI or GenAI. It’s all about the data—both current and future—which has enormous potential to generate value for the industry, if it’s managed well.
“Oil, gas and energy operators generate terabytes of data, be it large size seismic data, be it production time series data or high frequency data. And in the Middle East, we have a lot of historical data, because it is home to a lot of ageing reservoirs. And client data can be scattered, in different databases in different formats.
So it is important that this data is cleaned and is available to be consumed by AI and domain workflows. This is a big focus for us at SLB.”
Scaling AI adoption
Scaling and democratising the adoption of AI is the next step, Rahal says. “Even though everyone is talking about AI, it is still really at the proof of value stage. Today, AI is mainly a tool in the hands of experts that is creating individual pockets of value. We haven’t really scaled AI adoption and deployment to enterprise level or across all the assets in the organisation. So the next evolution is, how do you democratise access to AI? How will you reimagine work so that these tools are available to everyone in the organisation, not only to the data scientists and the experts?”
Rahal refers to his earlier comments on SLB’s focus on talent upskilling, adding that the company is facilitating adoption by embedding AI in its software. SLB’s global footprint and its partnerships with technology providers are also helping in this regard.
“From a technology perspective, having large language models (LLM’s) that are energy-specific and trained in the language of energy is critical, so that they can deliver trusted energy-specific and robust answers. This is the big challenge today. In SLB we talk about engineered AI, where we marry the AI with domain knowledge and expertise to answer questions at the level of quality our customers have come to expect from SLB. We are working today on multiple topics around specific engineered AI. For example, we have a seismic foundation model trained on seismic data, which helps geophysicists in fault identification which leads to higher quality and a lot faster turnaround. So having AI engineered specifically for the domain is key to ensure that the next evolution of AI speaks the language of energy.”
Technology innovations
Turning to SLB’s technology innovations in the AI space, and how they are helping operators in the region, he highlights the Lumi™ data and AI platform which integrates advanced AI capabilities—including generative AI—with workflows across the energy value chain, unlocking access to high-quality data across subsurface, surface, planning and operations, increasing cross-domain collaboration and providing insights to improve the quality and speed of decision making at enterprise-level.
“We are seeing a lot of success in the region in terms of customer interest and adoption, it really addresses what customers see as a foundational enabler for business transformation” he says.
SLB is at the same time augmenting their software by embedding and augmenting them with AI . For example, its Petrel™ subsurface software, which provides a full spectrum of geological workflows to solve the most complex geological and modelling challenges, has AI embedded to accelerate the work and improve the productivity of geoscientists, and there are at least 150 such examples across the organization.
“We’ve also embedded AI in our edge solutions,” Rahal notes. “So for example, in the case of chemical injection to address flow assurance issues and improve recovery, we can completely automate the chemical injection by controlling the timing and dosage. This can save on costs as well as the environmental impact.”
Rahal also highlights SLB’s Innovation Factori™ AI collaboration workspace, which aims to accelerate digital and AI adoption by bringing together SLB’s domain, data and AI experts together with customers to collaborate on developing tailored solutions addressing specific customer challenges, which can then be commercialised.
“It’s a great concept.”
He adds that the Innovation Factori™ centre in Abu Dhabi, which opened in December 2022, has had great success with customers in the UAE and throughout MENA.
Rahal concludes that he is very optimistic about the future of digital adoption within the MENA region.
“As I mentioned, most of the production is coming from ageing reservoirs. Many of the customer wells and fields are not instrumented today. Data is still sitting in silos. So the opportunity is huge in terms of the value that we can bring, going forward. I see potential for growth across all domains.”
Now the question is, how do you bring all this AI expertise and technology into the operations space?
One area which he does specifically highlight is autonomous operations whether in the drilling or production domains. “We have had great success with one of the operators in the Middle East around autonomous drilling.
“We’re also working with a major operator in the region to deploy a smart production solution that leverages AI on the edge to optimise the customer’s operations without any human intervention.
“So there are a lot of great things happening in the Middle East. I’m very excited about this, and the growth prospects are amazing.”
See Dany's views on the essential ingredients for successful digital transformation here