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Welcome to the official blog of the International Society of Automation (ISA).

This blog covers numerous topics on industrial automation such as operations & management, continuous & batch processing, connectivity, manufacturing & machine control, and Industry 4.0.

The material and information contained on this website is for general information purposes only. ISA blog posts may be authored by ISA staff and guest authors from the automation community. Views and opinions expressed by a guest author are solely their own, and do not necessarily represent those of ISA. Posts made by guest authors have been subject to peer review.

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AI in Oil: Unleashing a New Era of Efficiency and Innovation

Many business leaders are rapidly exploring options for using artificial intelligence (AI) to improve productivity, reduce errors, manage costs and more. Applications of AI in oil industry processes are becoming more prominent, and you can expect to see even more soon. People typically rely on this technology to elevate efficiency and pursue innovative methods.

Maximize Offshore Oil Results

Extracting offshore oil can be dangerous and complicated, with those involved facing safety threats associated with remote areas, inclement weather, strong currents and other variables. However, one multinational oil and gas company aims to swing the conditions in its favor using AI. If executives have reliable oil reservoir data, they can better decide how many employees to send to each site and when.

This solution centers on advanced algorithms that process massive quantities of seismic data, allowing workers to find new oil sources. Representatives also said this approach can create subsurface images with fewer scans, resulting in less disruption to deep sea life. Most notably, explorations formerly taking nine months now happen in nine days or less.

Resolve Queries Faster

Relying on AI in oil industry processes is about identifying the best ways to capitalize on humans’ expertise and giving employees enough time in their workdays to focus on the tasks that add the most value to the business.

Executives can relieve customer service team burdens by supplementing team members’ efforts with conversational AI chatbots. This is an increasingly popular option, but it has some limitations. Some tools occasionally offer seemingly accurate but non-factual responses. However, one way to prevent that outcome is to program the chatbot only to recognize and answer specific questions. Customer service representatives can then handle the more complicated situations.

In one example, leaders from a Norwegian oil exploration and development company wanted an internal chatbot for approximately 2,000 employees to use similar to a search engine that would give results specific to their workplace’s documents and policies.

Initially, an administrative assistant team handled queries about supply chain management, training requirements, human resources and other necessities. However, they quickly became overwhelmed by the request volume and the repetitive nature of some questions. Answering them took them away from other duties comprising their primary responsibilities.

The chatbot could handle almost all questions, saving dozens of hours per week. Using these tools in the oil industry is not yet widespread, but these resources can pay off when strategically deployed to meet identified needs.

Improve Maintenance Measures

Sudden equipment downtime can be extremely costly, posing additional risks to workers and the environment. However, applying AI in oil industry maintenance procedures provides extra visibility, allowing people to detect and respond to abnormalities before production stoppages happen.

Oil industry professionals use various pieces of specialty equipment in their operations. Positive displacement pumps offer affordable construction and design, with functionality suited to upstream tasks. Some pumps in this category also use gears for fluid transfer.

One American oil and gas company uses artificial intelligence to reduce unplanned events stemming from inadequate maintenance. The business has AI-equipped cameras that recognize corrosion on subsea and topside offshore assets. The company is also working on a data-driven cloud initiative that will allow it to capitalize on growing amounts of information that could enhance maintenance and other necessities.

Another business has generated $5 million in funding for its submarine-inspired robots. These machines check oil and gas industry tanks with phased array ultrasonic testing technology. This approach captures 18,000 scans per square foot. Artificial intelligence enables robots to conduct autonomous testing, affecting aspects such as guidance plans and a dynamic control system.

Such investments should keep oil industry operations safer and more profitable. When leaders know about maintenance issues sooner, they have more time to buy replacement assets, order spare parts, contact technicians or engage in other actions to prevent severe disruptions or accidents.

Enable Accurate Reporting

Oil companies must satisfy regulations by meeting or exceeding emissions control requirements. However, researchers believe parties largely underestimate methane measurements until an AI project provides more accuracy.

A group developed an AI-powered hyperspectral imaging tool used to analyze overhead scans of an area. This approach uses 432 channels, with pictures taken at up to 2,500-nanometer intervals. Artificial intelligence can assess all captured data, differentiating between hydrocarbon plumes and other emissions. As of June 2023, the researchers had data from approximately 4,000 sites. Tests show this method is about 94% accurate, across both dry and densely vegetated properties.

The team currently relies on airplanes to capture the data, which can track emissions as small as about 50 kilograms per hour. However, they hope to eventually scale up to a satellite-based approach. That change could show emissions leaks across larger areas, including those previously undetected.

One project participant mentioned oil rig emissions off the coast of Mexico that emitted more than 7,600 kilograms of methane per hour for six months before detection. However, this option for using AI in oil industry operations could eliminate or drastically reduce such oversights. Positive outcomes benefit parties within and outside of oil companies.

Artificial intelligence excels at finding patterns and other insights in huge quantities of data. Another investigation from a different team involved using AI to study more than 560,000 satellite radar images gathered across five years. The results showed the sites, severity and probable reasons for oil pollution.

The group focused on oil slicks, which are typically challenging to study since they appear in microscopic layers on the ocean’s surface, constantly moved and broken apart. However, AI allowed the researchers to monitor oil slicks in challenging environments and gain useful insights.

It’s Time to Use AI in Oil Industry Operations

These are only some of the many successful ways to apply artificial intelligence to the oil industry. When decision-makers commit to fostering innovative workplaces and investing in advanced technologies to enhance on and offsite processes, they can anticipate measurable results.

However, the best plans include specific goals and dedicated paths to achieving them. Getting good outcomes involves using new platforms, changing work procedures, running employee training programs and tracking key metrics. Creating and sticking to a comprehensive technology adoption plan helps people stay motivated and see what’s working.


Emily Newton
Emily Newton
Emily Newton is the Editor-in-Chief of Revolutionized, an online magazine celebrating advances in science and technology.

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