Known for its manual labor and heavy machinery, the oil and gas industry is now a hotbed for AI adoption. Don’t believe it?
I didn’t either, but here’s a twist. IBM reports indicate 44% of upstream operations (exploration and production) in the oil and gas industry currently use artificial intelligence solutions.
Artificial intelligence in energy sector is changing the game in the following ways:
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Carbon Emissions Reduction
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Demand Forecasting
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Remote Monitoring
While the comparative share of automated technologies in the oil and gas sector is relatively low, as the AI surge continues, it's about time we expect a near-universal implementation of these technologies.
In this blog, we’ll explore the revolutionary role of AI in oil and gas sector, along with its real-world applications worldwide. Let’s jump into it.
Why AI adoption in the Oil and Gas Sector?
The Asia-Pacific region is the fastest-growing market for AI in oil and gas industry, with a projected growth rate of 14% from 2024 to 2029, presenting a golden opportunity for these countries to invest in AI development services.
This AI-driven transformation proves to be worthy in:
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Cost Reduction
Predictive maintenance reduces sudden wear and tear of equipment. It monitors the supply chain to eliminate wastage with automation of routine tasks to ultimately lower logistics and labor costs.
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Energy Optimization
AI algorithms are proficient in suggesting ways to reduce energy waste. One of its efficient use cases in the oil and gas sector is learning patterns to adapt in real-time to fluctuations in demand, price, and weather.
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Automated Operations
AI-powered systems can monitor, manage, and iterate by eliminating the need for human interventions. From remote monitoring in oil and gas to performance tracking systems, these algorithms can take the burden off your shoulders.
The Role of AI in The Evolving Landscape of the Oil and Gas Sector
Still wrapping your head around the fact that AI is the next big industrial revolution in the oil and gas sector? Let’s make this easier for you to understand.
Here are the key areas where industry giants are integrating AI solutions:
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Adjusting to Price Fluctuations
We are no strangers to the price volatility in the oil and gas sector. Predictive AI models can foresee these fluctuations by analysing real-time data and historical price trends.
This mechanism helps businesses in mitigating risks and capitalising on favourable market trends to ultimately safeguard your management from taking any impulsive decisions.
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Oil Spills Detection and Response
Oil spills are detrimental to the environment and lead to financial losses and legal liabilities. Luckily, we have AI systems that can collect satellite imagery to detect and respond to oil spills.
Automated systems can verify the extent of leaks and their cleanup costs for proactive control.
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Demand Forecasting
Accurate demand forecasting calls for a 360-degree view of contextual data, which involves historical data analysis and current market trends. The ultimate goal here is to be market-ready.
Artificial intelligence in oil and gas skim through these vast sets of data for accurate demand projection to prevent overproduction and underproduction.
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Reservoir Modelling
Machine learning in oil and gas is becoming an integral part of reservoir engineering. These models are trained to be smart proxies for running complex simulations to bring down computation time.
Businesses are using these technologies to generate high-resolution reservoir models to eventually reduce the reliance on physical testing.
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Predictive Maintenance
Predictive maintenance is a prominent approach for monitoring equipment health. They can detect anomalies and equipment failures before they even happen. Sounds perfect, right?
This foresighted prevention eliminates the risk for unexpected downtime, along with preventing fatal equipment failures. A literal lifesaver, isn’t it?
A Simple 3-Step Guide To Get Started With Your AI-Driven Project in the Oil and Gas Industry
You might be overwhelmed reading all the heavy AI terms, and at the same time, scratching your head, figuring out where to begin. So let’s make it crisp, here is a short guide to get you started:
Step 1: Address One Issue at a Time
Pick an issue that you aim to resolve, an issue that can save you a hell of a lot of time and money. It could be the constant worry of making your contracts compliance-friendly, or the unexpected breakdowns of equipment.
Start on a small but powerful note. Ensure that you and your team are on the same page.
Step 2: Set Your Data Source Straight
I think by now we’re clear on the fact that AI systems run effortlessly on credible and context-based data sources.
To get smart responses, you need smart data. Make sure you are well-equipped with spreadsheets, sensor data, field notes, and proprietary reports. Don’t expect the model to miraculously cure all your issues, so before you build, identify your data source.
Step 3: Pick the Right Partner-In-Crime
Most businesses fail to pick the ‘right person’ to build their model. They either assign it to their IT team or hire oil and gas software development company without giving any context.
Neither would get you results, the ideal path is to partner up with a business that understands the core of your operational problem and guides you in bridging the technological gaps.
4 Real World AI Applications For Oil and Gas Sector
On a global level, some industry giants are creating a visionary path to overcome domain-specific challenges, drive innovation, and set new standards. Let’s get inspired:
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Saudi Aramco (Saudi Arabia)
Saudi Aramco is one of the largest oil producers in the world and is developing its own industrial large language model(LLM), coined as Metabrain. Here’s a list of areas where Aramco aims to deploy AI applications for oil and gas sector:
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Predictive analysis for equipment maintenance
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Seismic data analysis for oil exploration
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Computer vision for worker on-site safety
The Gulf countries are building smart AI solutions, and it’s not just limited to the oil and gas sector. They are integrating AI technologies to achieve intelligent urbanism. Explore how AI is revolutionizing smart cities across the GCC.
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Chevron (USA)
To overcome the manual hustle of traditional methods, Chevron leverages AI solutions to get an accurate picture of the channels suitable for oil and gas recovery and which area fits the best for carbon dioxide storage.
To keep their assets up and running, AI systems detect anomalies by scanning through sensor data, which helps their crew know the focus of attention.
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Shell (Netherlands/UK)
Shell has actively involved AI in their entire chain of oil and gas production. From machine learning in oil and gas to computer vision, deep learning to virtual assistants, their focus revolves around deploying a range of AI technologies for smoother and unbothered operations.
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Abu Dhabi National Oil Company (UAE)
ADNOC has deployed a large-scale agentic AI(EnergyAI) into its operations, developed in the UAE in collaboration with Microsoft and G42 for oil and gas software development.
EnergyAI is trained on proprietary knowledge and performs complex tasks from seismic analysis to geological modeling in real-time.
One thing worth noticing is the impressive participation of the Gulf region in bringing AI technologies to benefit its citizens. This rise is felt across industries. Check out the transformative power of AI across Gulf businesses.
AI-Driven Transformation in The Oil and Gas Sector: How Infutrix Can Help?
As we stand at the face of this profound transformation driven by artificial intelligence in oil and gas sector. No matter which use case suits your business model, optimizing oil exploration, streamlining pipeline operations, or building predictive maintenance systems.
At Infutrix, we specialize in delivering the best oil and gas software development solutions with AI-powered innovations tailored to the evolving needs of businesses regardless of the industry.
