TL;DR:
- Major oil and gas firms are embracing AI to expedite fossil fuel extraction.
- AI promises cost-efficiency and potentially increased production.
- Shell’s partnership with SparkCognition aims to reduce exploration time significantly.
- Other oil giants like TotalEnergies, BP, and ExxonMobil are also investing in AI.
- Sustainability claims of AI technology remain vague, raising skepticism.
- The adoption of AI for oil extraction poses environmental concerns.
Main AI News:
After another summer marred by extreme weather events linked to fossil fuel consumption, the world’s leading oil and gas conglomerates are strategically embracing artificial intelligence (AI) to expedite their oil and gas extraction processes.
By even the most conservative estimates of the International Energy Agency, the world stands on the precipice of an environmental catastrophe if it continues to greenlight new fossil fuel development projects. To maintain a semblance of control over global temperatures and limit the increase to a manageable 1.5˚ Celsius, the world must abstain from drilling new fossil fuel reservoirs. However, the industry giants are currently banking on AI technologies, which promise swifter and more cost-effective methods of discovering fresh reserves of oil and gas. Some researchers even suggest these algorithms could potentially amplify the quantity of fossil fuels that a company can extract from a given project.
In May, industry behemoth Shell unveiled its plans to utilize generative AI as a catalyst for oil and gas exploration. This initiative forms an integral part of the company’s overarching strategy to enhance safety, efficiency, and sustainability throughout its operations. SparkCognition, an AI solutions provider, boasts a patented machine learning algorithm that vows to deliver “potentially increased production and higher success rates.” It also claims that this technology could uncover previously untapped fossil fuel resources on the ocean floor within a mere nine days, as opposed to the customary nine months.
For each new prospective deep-sea oil and gas field, SparkCognition’s algorithm may reduce the reliance on traditional seismic images to a mere 1-3%, as disclosed by the company’s Chief Science Officer, Bruce Porter, in an interview.
Shell’s collaboration with SparkCognition represents just one instance in a series of similar partnerships. TotalEnergies, for example, claims to have embraced machine learning as early as the 1990s and has recently forged a collaborative venture with Google Cloud to cultivate deep learning applications. BP’s venture capital arm invested in an AI firm in 2019, with the expectation that its algorithm would “unlock critical data for our subsurface engineers at a much-accelerated pace.” Similarly, ExxonMobil has joined forces with IBM in an “open-sourced, AI-driven process,” purportedly reducing the time required to design new well drill plans by a remarkable two months, according to Emerj.
While SparkCognition’s Chief Science Officer has alluded to the sustainability-enhancing potential of the technology under development, the specifics remain vague. A subsequent blog post on SparkCognition’s website suggested that its generative AI could diminish “the likelihood of misplaced or wasteful drilling,” albeit without delving into further particulars. Meanwhile, Shell has confirmed its intention to sustain current oil output levels until 2030, but it remains unclear how the capital saved through technology deployment will be allocated, particularly within the renewables sector of its business.
In response to Shell’s sustainability assertions, Dr. Martin Blunt, a professor at the Department of Earth Science and Engineering at Imperial College London, expressed a skeptical view. He asserted, “The technology itself is irrelevant to sustainability. It can potentially help companies understand what’s underground, and for Shell, this will principally enable them to drill for additional oil and gas reserves.”
As the global community grapples with an urgent mandate to combat climate change, oil and gas conglomerates are employing AI as a means to supercharge their fossil fuel extraction efforts in a last-ditch effort to capitalize on their reserves before the transition to alternative energy sources becomes inevitable. The United Nations estimates that fossil fuels are responsible for a staggering 90% of carbon emissions, the primary drivers of planetary warming, and the source of widespread suffering and loss for countless individuals. Each AI-assisted foray into the pursuit of more oil jeopardizes global endeavors to maintain temperatures within the 1.5-degree threshold, representing an alarming acceleration towards an increasingly uninhabitable world. While the “digital drill” may offer operational efficiency to oil and gas companies, the potential toll on our planet and its inhabitants looms large.
Conclusion:
The adoption of AI in fossil fuel extraction signifies a strategic move by major energy companies to enhance efficiency and potentially expand their reserves. However, questions surrounding the environmental impact and the global push towards renewable energy sources cast a shadow over the industry’s long-term prospects, necessitating a balance between short-term gains and long-term sustainability in the energy market.
