In recent years, Artificial Intelligence (AI) has been revolutionizing numerous industries around the world, and the energy sector, specifically the gas industry, is no exception. The integration of AI in the energy industry is transforming the way energy is produced, distributed, and consumed. Multiple energy companies have taken important steps to leverage the recent advancements in AI, with the aim of improving operational efficiency. According to S&P Global Commodity Insights, integrating AI technologies has the ability to produce performance improvements for the energy sector in the range of 10% to 25%.
Notably, the exploration and production sector has undergone a profound transformation as a result of AI integration. With regard to exploration, AI technologies, with its capabilities of analysing huge amounts of geology and geophysical data, play an increasingly significant role in areas such as seismic acquisition, processing, and interpretation. As a result, of the success ratio in exploration is higher and costs lower.
With regard to production, AI data analytics have been integrated into drilling operations through AI-driven predictive models that analyse geological data, drilling parameters and environmental conditions, to trigger a warning in case of potential risk or hazard. This has led to an elevated level of safety measures, a reduction in drilling problems and eventually a decrease in the overall drilling costs. Additionally, in the oil and gas production activities, the use of machine learning tools has transformed the way reservoir modelling and simulation are performed, leading to a better optimization of field development and an increase in the ultimate hydrocarbon recovery.
Furthermore, the application of AI technologies can assist energy companies in improving operational performance across the full supply chain, including the upstream, midstream and downstream sectors. For example, by analysing historical maintenance data, downtime data, equipment age, and sensors data, AI can help forecast the time when operators need to interfere with preventive maintenance. This can produce a significant reduction in downtime and maintenance cost. Furthermore, in the power generation sector, integrating AI technologies in the Demand Response Management (DRM) is a critical measure for the optimization of power consumption and the stabilization of the power grids, while ensuring the proper balance between supply and demand during peak loads.
AI technologies may also play a key role in advancing the decarbonisation of the gas industry, in support of the climate change mitigation. In this regard, AI improves the analysis of the massive amounts of data on methane and CO2 emissions, while correlating data received from satellites with data recorded by land-based sensors, to establish multi-scale monitoring and reporting systems. Moreover, AI technologies are well-placed to accelerate the decarbonisation of the power sector, which is the major gas consuming sector, with opportunities arising for optimising generation, transmission and distribution infrastructure.
Another application of AI in the industry is its usage in energy trading. AI models have the ability to proactively process extensive amounts of market dynamics data in terms of supply, demand and prices. This enables traders to make educated trading decisions, with higher chances of profitability and more accurate assessments of market volatility and uncertainties.
GECF is proactively engaged in the promotion of AI technologies in the energy sector in line with the GECF Long-Term Strategy, specifically strategic goal #3 “Advance modern technologies in the natural gas industry”. Notably, the 2nd GECF Workshop on AI in the Oil and Gas Industry took place on 12 June 2024. One of the key takeaways was that AI presents a wealth of opportunities for the industry, from enhancing exploration and production efficiency, to optimising supply chains and enabling predictive maintenance. As this technology continues to evolve, it is imperative that robust governance frameworks are established to ensure AI's ethical and responsible development and deployment.
In the meantime, the active deployment of AI technologies across numerous industries relies on the establishment of data centers. This involves extensive data processing and storage, which has another critical impact on the energy industry. The rising number of established data centers, combined with their high electricity intensity, has caused a sharp increase in electricity demand. It is worth noting that electricity demand from AI-related data centers is increasing at a much faster rate compared to that from non-AI data centers. According to IEA, data centres, cryptocurrencies, and artificial intelligence consumed 460 TWh of electricity worldwide in 2022, almost 2% of total global electricity demand.
Data centers require reliable and dispatchable electricity supply to ensure higher computational power, guarantee cooling efficiency and avoid costly downtimes. However, non-hydro renewable energy sources, such as wind and solar, are notable for intermittency, which poses a challenge for data centers. In this regard, natural gas as an environmentally-friendly, affordable, reliable, flexible, versatile and abundant energy source has a huge potential to meet the growing electricity demand from data centers. Offering a stable and scalable power source, natural gas plants can quickly ramp up electricity output to meet fluctuating electricity demand.
The data center development is not confined to any single region, but is distributed worldwide. However, further extensive expansion of data center infrastructure in Europe and Asia may be hampered by limitations such as high electricity tariffs and a shortage of electricity, which may be overcome with additions of gas-fired electricity generation. In Asia, specifically in the leading countries of China and India, whose electricity mix is dominated by coal, there are significant incentives to increase gas-fired electricity generation and promote coal-to-gas switching.
In this context, the GECF member countries, possessing abundant natural gas resources, are thus well-positioned to contribute to the expansion of both AI-related and non-AI data centers. Firstly, these countries are capable of stepping-up gas supply (in the form of both pipeline gas and LNG) to energy import-dependent countries in such regions as Europe and Asia, which may need natural gas to increase their dispatchable electricity output for a smooth performance of data centers. Secondly, these countries have the potential to strengthen their positions as emerging growth points for the global data center industry. As of today, all GECF member countries have data centers on their territories. That is based on their own technological advancement in digital transformation, which is ably supported by their competitiveness in terms of electricity tariffs. Most of them are among the countries with the lowest electricity tariffs, as a consequence of their extensive gas-fired electricity generation. That has already encouraged various transnational companies to move their data centers to the GECF member countries, and this trend is expected to ramp up in the short and medium term.