Nigeria’s quest for a cleaner energy future has received a major boost thanks to the emerging role of Artificial Intelligence (AI) in hydrogen and carbon storage.
According to Moses Falowo, a Hydrogen and Carbon Storage Researcher at Kansas State University, USA, AI is transforming the energy geosciences, offering revolutionary tools to tackle the urgent challenges of hydrogen and carbon storage.
In an interview with our correspondent, Falowo explained that AI, through its subset machine learning (ML), enables geoscientists to identify optimal underground storage sites with unprecedented precision and speed.
He noted that this technology has the potential to enhance safety and efficiency in clean energy solutions, particularly in Nigeria, which has abundant natural gas reserves.
Falowo said, “Artificial Intelligence (AI) is rapidly transforming energy geosciences, offering revolutionary tools to tackle the urgent challenges of hydrogen and carbon storage. AI, a broad field of computer science, involves creating machines that can perform tasks that typically require human intelligence.
These tasks include learning, problem-solving, and decision-making. An important subset of AI is machine learning (ML), where algorithms learn from data without explicit programming. Within ML, a powerful subfield is deep learning (DL), which uses artificial neural networks with multiple layers to analyze complex data representations.
This enables geoscientists dealing with hydrogen and carbon storage to identify optimal underground storage sites with unprecedented precision and speed, enhancing safety and efficiency in clean energy solutions through the processing of large geological datasets. This undoubtedly makes this application outperform the traditional methods in terms of computational run time.Nigeria has abundant natural gas reserves, and it stands to gain significantly from these advancements. The integration of AI into the energy space including hydrogen and carbon storage offers a pathway for Nigeria to harness its vast natural gas reserves for hydrogen production. It also allows Nigeria to implement effective carbon storage solutions to mitigate greenhouse gas emissions and combat climate change. This approach aligns with Nigeria’s commitment to reducing gas flaring and diversifying its energy mix, as outlined in its Nationally Determined Contributions (NDCs) under the Paris Agreement.
To capitalize on these opportunities, it is now very important to invest in AI research and development, supporting initiatives that explore the application of AI in energy geosciences, specifically for hydrogen and carbon storage. Fostering collaboration between government, academia, and industry is also essential to facilitate the development and deployment of these technologies. Developing policy frameworks that create an enabling environment for the adoption of AI-driven solutions in the energy sector, including regulations and incentives, is also very important.
The world has begun adopting this technology. For instance, researchers at Los Alamos National Laboratory (LANL) in New Mexico, United States, have employed machine learning models to optimize underground hydrogen storage operations, significantly boosting hydrogen recovery and storage efficiency. These advancements directly support hydrogen’s role as a key renewable energy carrier.
The Hydrogen Council projects that hydrogen could meet up to 20% of global energy demand by 2050, contributing to a global market worth $2.5 trillion. Importantly, AI’s contribution is equally impactful in carbon capture and storage (CCS), which is a critical tool for climate mitigation. The U.S. Department of Energy’s (DOE) Science-Informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) initiative has used this technology, AI, to produce real-time 3D seismic images.
This allows geologists to monitor underground CO₂ movements instantaneously, enhancing environmental safety by rapidly identifying and mitigating potential leaks. For example, Norway’s Sleipner field, the world’s first offshore CCS project, has securely stored approximately one million tonnes of CO₂ per year since 1996. This field provides comprehensive and extensive datasets for training AI models, enabling continuous improvement in the predictability and reliability of future carbon storage projects.
These AI advancements also promise substantial economic benefits. A recent U.S. hydrogen roadmap forecasts a $750 billion annual hydrogen market by 2050, which will generate 3.4 million new jobs in clean energy sectors. AI-driven efficiency improvements in site selection, monitoring, and operational management will reduce costs, attract investment, and encourage rapid expansion of hydrogen infrastructure.
In the carbon storage domain, AI-enhanced reliability and safety assurance will enhance industry and public confidence, accelerating adoption rates essential for meeting climate targets. Environmentally, the synergy between AI and geologic storage technology provides tangible climate benefits.
With the International Energy Agency projecting the necessity to capture and store 6.2 gigatonnes of CO₂ annually by 2050, AI significantly accelerates the identification, approval, and operational stages of CCS projects.
This acceleration not only helps meet ambitious climate goals but also supports broader economic resilience by safeguarding energy supplies and reducing reliance on fossil fuels”
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