Leveraging Artificial Intelligence to Solve Oil and Gas Emissions Challenges

As efforts to combat the climate crisis continue and GCC countries build momentum towards a net-zero carbon emissions future, the top priority for oil and gas companies has never been more important.

From a regional perspective, the oil and gas industry accounts for 9% of the entire oil and gas industry’s greenhouse gas emissions through direct upstream, midstream and downstream (Scope 1), indirect energy (Scope 2) and other indirect emissions (Scope 3) %.

The transition to low-carbon alternative energy sources alone will not be enough to ensure the emissions reductions needed, and a permanent solution to the problem will need to be coupled with an impactful technology unlike any other - artificial intelligence (AI) Combine.

While the net-zero route comes with immediate time constraints, oil and gas companies can adopt a technology-led approach with optimism. After all, the broader GCC is building a lot of momentum following recent groundbreaking actions and announcements.

Saudi Arabia is one of the countries leading the charge on decarbonization, primarily through the Saudi and Middle East Green Initiative, which aims to reduce carbon emissions by 60%, in part using clean hydrogen technology.

Similarly, the UAE recently confirmed plans to invest $163 billion in clean and renewable energy over the next 30 years as part of the country’s 2050 Net Zero strategic plan.

However, for these scenarios to occur as envisaged and for the sustainability framework to finally fulfill its potential, oil and gas companies must first be able to make an impactful contribution.

Addressing Emissions

While businesses can reduce scope 1 and scope 2 emissions through operational and energy efficiency programs, scope 3 emissions from transport, consumption and disposal must also be reduced, which requires optimization and Visibility.

Crucially, most businesses have not yet set out targets to accomplish this, or lack the understanding needed to succeed – ultimately failing to communicate, commit to or deliver on climate requirements.

To advance decarbonization, optimize operations and take advantage of full visibility into the scope of direct and indirect emissions, oil and gas players must embed digitalization and embrace enabling analytics into their organizational culture, processes and practices.

Together with artificial intelligence and machine learning (ML), these tools can enable companies to identify emission sources, thereby reducing energy consumption and optimizing operational energy efficiency. However, companies are tasked with identifying strong emission drivers and uncovering emission reduction initiatives across their entire operations. Methane is a particular area where there are difficulties when it comes to measuring, monitoring and reducing emissions – and AI could drive considerable progress.

AI TO CLIMATE RESCUE

As the foundation of the emissions reduction journey, AI helps incorporate disparate data sources and apply advanced algorithms to predict emissions, reduce levels and monitor success . Integration enables companies to leverage the technology to establish emissions baselines across all three scopes, pursue the most valuable emission reduction initiatives, and have a high degree of assurance about potential impacts.

However, in addition to the critical nature of reducing Scope 1 and 2 emissions, Scope 3 emissions can account for more than 90% of a company’s total greenhouse gas emissions. Additionally, developing a comprehensive Scope 3 emissions baseline and working with suppliers and customers to reduce greenhouse gas emissions is a complex analytical challenge.

Across the oil and gas supply chain, emissions have historically been difficult to measure without set industry standards and competitive benchmarks, while data quality is often substandard and companies lack the capabilities and resources needed to meet Scope 3 footprint requirements. .

Therefore, given the increasing mandatory pressure to drive solutions that are required to succeed is critical, companies must adhere to three emission reduction value chain considerations to drive their decarbonization efforts:

• Baseline: Enterprises should ensure that baselines address operational processes and assets across the entire value chain, including suppliers, customers, production forecasts, production expiration information, and growth opportunities.
• Reduction: Although financial viability is rarely in question, emissions reduction efforts should focus on win-win situations, including increasing production and expected asset life, and taking steps that are economically sustainable and Initiatives that can be deployed at scale.
• Governance and Change Management: The integration of digital emission reduction tools with the overall data architecture is critical for accurate production and financial data visibility and successful decarbonization. In turn, changes in organizational culture and new ways of working can speed up decision-making and simplify greenhouse gas reduction.

As emissions reduction requirements intensify, oil and gas companies must adopt artificial intelligence tools and technologies to enhance relevant strategies and meet their obligations. In the process, newfound capabilities will enhance the collective process of establishing emissions baselines, optimizing operations and accurate reporting, promoting valuable climate change outcomes.

Emission reduction will eventually become an indispensable competitive advantage, and technology will play an important role in a win-win outcome for the relevant players and the planet.

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