Data is sometimes described as the ‘new oil’, and the economic power of deploying big data sets is in continuing, dramatic growth with the development of sophisticated forms of artificial intelligence (AI).
‘New oil’ is also playing a powerful role in the way in which ‘old oil’ as an industry adapts to historic changes. While there is a substantial switch away from fossil fuels for transport and generating electricity, oil and gas have many more applications, for example as transition fuels and in production of plastic components, which are widely used, including in cleaner technology such as electric vehicles.
In the need to lessen environmental impact in all aspects of the oil and gas industry and boost efficiency, AI systems will be an increasingly important technology. As a sector, AI in oil and gas is expected to register a compound annual growth rate of over 10% during the period to 2027.
For Qatar, there is a historic opportunity to sustain the oil and gas industries, enable them to be more sustainable, and to diversify the economy and become a world-class centre for AI technologies. There are positive signs that this is occurring. There is a strategy to place AI at the centre of economic development set out in a policy document produced by the Ministry of Communications and Information Technology, together with Hamad Bin Khalifa University and the Qatar Computing Research Institute.
AI can help ensure dramatic improvements in the oil and gas industry in three critical areas:
Efficiency and cost savings, lower environmental impact, and enhanced employee safety.
Qatar can be a world leader in all three areas. There are applications for AI across the full range of activities in the oil and gas industry. Some of the examples are summarised below:
Exploration and production: AI has a role from the first part of exploration, powering robots that can detect oil seeps and reserves deep below the surface, including below the ocean. They can analyse semantic waves and help discover the presence of hydrocarbons with minimal effort and rapidly. AI tools improve the accuracy of mapping natural oil deposits; they can be used to forecast reservoir volumes, and incorporate data on both reserves and market trends into business modelling.
Drilling and refining: Drilling can be focused and precise. AI can identify the best drilling locations and predict drilling risks. It enables accurate daily, monthly and lifetime production forecasting, and detection of defects and anomalies.
On-field equipment and services: Exploration, extraction, production and refining are interdependent processes. If data is kept in silos this prevents optimal coordination; AI has the computational power to coordinate the whole, significantly improving overall efficiency.
All equipment used in the industry has a finite lifespan. Predictive maintenance involves using AI tools to detect when a component, such as a valve or section of pipe, is near to the end of its life, so it can be replaced or repaired before a breakdown, which would result in interrupted supply.
Digital twin technology involves building a virtual replica of an operational part. This digital asset is continually updated with operational data, including from on-site sensors, and the AI algorithms monitor performance in real time, producing early signs of asset failure. Use of this technology is more cost-effective than deploying a team of maintenance staff, moreover it operates 24/7.
In addition, automation can improve the efficiency of back office operations, as in other sectors of industry.
Logistics and transport: Specialist AI tools for logistics can help optimise the operation of the entire supply chain. AI has the computational power to ensure optimal efficiency, informed by Internet-of-Things-linked sensors and intelligent devices throughout the processes, transmitting fleet data such as vehicle performance, fuel use, and inventory.
All these operational improvements minimise environmental harm while enhancing business efficiency simultaneously. Accurately targeting places for drilling significantly reduces the disruption of traditional, more random approaches. And there are further improvements to environmental protection through the use of AI: Carbon capture systems can be enhanced, for example to determine the optimum amount of CO2 that can safely be stored in a site of porous rock. AI tools are also used to monitor and help reduce CO2 emissions in production and transport.
Qatar has a coherent plan to build an advanced AI industry, including specialist applications to boost sustainable fossil fuel production that will remain at the heart of economic development for some time to come. There are historic transitions under way in both computing technology and oil and gas. Qatar is set to be a leader in both.
The author is a Qatari banker, with many years of experience in the banking sector in senior positions.
