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6 Ways AI is Transforming the Oil and Gas Industry

Oil and Gas Refinery Worker with updated AI technology

It can be said that every industry can benefit from artificial intelligence and while that may be true, the oil and gas industry may stand to benefit the most. Oil and gas is one of the most lucrative industries, it's also one of the most dangerous. Artificial Intelligence optimizes business operations, productivity, and safety. Here are six ways AI is solving various challenges of the oil and gas industry.

1. Defect Detection and Enhance Quality Assurance

One of the challenges in the oil and gas industry is identifying improper threading in pipelines or defects in error-prone mechanisms. Defects found at the end of the production line from upstream issues cost factory and budget resources. For example, if the defected oil pipeline or machine is installed into production, this could result in severe damages. These losses are comparatively far higher than the cost of AI adoption. 

Deploying a computer-vision based system can verify the quality of production and provide deep insights of defects in analytics. AI powered Defect Detection solutions are cost-effective and is extremely economical in comparison to the prevailing processes.

2. Ensure Safety and Security Standards

Oil and gas plants operate in extremely critical environments and the risk of injury is much higher than traditional manufacturing environments. Employees in oil plants work under different temperatures, are sometimes exposed to toxic fumes and must be aware of many moving mechanisms. Not following proper safety protocols can result in injury and financial penalties. One such incident happened in the California based Tesoro Martinez Refinery plant, where a sulfuric acid spill burned two employees. Describing the incident, Tesoro officials stated this could have been prevented if the employees were following proper safety standards.

Companies are obliged to adhere to safety standards enforced by law. Not adhering to these standards result in hefty fines.  Even though there is a ton of data to monitor safety issues, it is still a largely manual processes, such as manually monitoring camera feeds or physical safety sweeps, to make sure measures are effective. Current solutions only ensure employees are wearing Personal Protection Equipment (PPE) at the point of entry into the plant, not throughout the workday.  

An AI-powered computer-vision solution can monitor the work site to ensure workers are following safety procedures without any deviations. The camera data is fed into an AI algorithm which will then be analyzed to send alerts and proactive recommendations. AI solutions can alert management even for the smallest deviations in compliance. 

3. Reduce Production and Maintenance Cost

The annual cost of corrosion in the oil and gas production industry is estimated to be $1.372 billion."                    

- International Journal of Industrial Chemistry, Springer

 

Oil or gas extracted using oil rigs is stored in a central repository and then distributed across pipelines. Due to various temperatures and environmental conditions, oil and gas components often face material degradation and corrosion. Corrosion can cause component deformation, which results in faded threading or can weaken the pipeline itself. Not handling this problem can result in catastrophic damages halting the entire production process. This is one of the biggest concerns of the industry and companies employ corrosion engineers to monitor and handle the health of components to avoid corrosion activities.

Consider the Macondo Incident also known as the BP Oil Spill. On April 20, 2010, 4.9 million barrels of oil was spilled and $850 million was spent by the US government on clean-up efforts. This was considered one of the biggest oil and gas incidents. Post-analysis research reports stated that incorrect maintenance function was one of the main causes of the incident. Part of the maintenance requirements included checking equipment conditions. Also, it was uncovered that the emergency system was disconnected and not working

AI solutions can prevent incidents like this from occurring. AI and IoT technologies can detect signs of corrosion by analyzing various parameters using knowledge graphs and predictive intelligence to approximate the corrosion occurrence probability and raise alerts to pipeline operators. This way companies can be proactive in handling the corrosion risks and moreover, based on knowledge graph analysis, study various machinery downtimes and predict time to carry out maintenance activity. This way, companies plan and adjust for downtime.

AI Detects and Oil Rig Operator Wearing Personal Protective Equipment

4. Make Better Decisions with Analytics

Oil and gas businesses deal with lots of data coming from manufacturing processes but due to a lack of proper analytics tools, they’re unable to capitalize on the massive data resting in data silos. Companies can employ data engineers to manually analyze data to draw insights, but this is a limited option in time and cost furthermore, no amount of data engineers can possibly get to all the data that’s produced in a single day of operations.

Big Data powered AI applications derive intelligence and meaning out of the plethora of operational data. Artificial intelligence can be used to gather information into segments and uncover patterns or inconsistencies to make predictions out of the large data sets.  

AI algorithms study various data streams from various sensors and machinery of different plants or entire Geoscience data and extract real-time analytics to generate intelligent suggestions based on business needs. These deep insights enable geoscientists to have better visibility of the overall processes and operations, thereby enabling them to make better strategic decisions. This leads to improved operations efficiency, cost reduction and even reduces the risk of failure.

5. Add Assistance with Voice Chatbots

Field operators benefit from chatbots and virtual agents and adding a voice-enable component allows operators to take chatbots with them in the field.  The following is a list of uses-cases for field-worker voice assistants. 

  • Operators need to keep their hands free as they are often moving from one place to another. Voice-enabled chatbots can assist operators with questions and status reports all with hands-free voice commands.
  • Chatbots are an excellent source of information and pull real-time data, handle tasks such as calling for help and can provide relevant instructions from an internal knowledgebase.
  • Maintaining an intelligent chatbot creates a central place for historic data. Get new-hires up to speed faster with a chatbot. Compared to other industries, employee transition in oil and gas is the biggest challenge for the company.

In all the above cases, operators can have additional assistance to make decisions and have real time access to critical data. Operators facing a machine failure can ask a chatbot how to fix it or any question for that matter.  

6. Uncover New Insights In Oil and Gas Exploration

As the US energy sector continues to grow, the U.S. Energy Information Administration (EIA) predicts that US domestic crude oil production will surpass 11 million barrels per day by 2050.

This clearly states the need to increase exploration activities. Though this policy and target give a massive boost to the industry, critical factor continues to cause concern in the industry as the process of oil and gas exploration is very expensive and exhaustive. Hydrocarbon exploration is important to get a complete picture of what is in the earth's surface. The traditional process of exploration geophysics isn't precise and is very costly.

To make this process easier and gather precise data, adopting autonomous AI-powered robots for exploration is a great solution. Top oil and gas companies are using drones to gather seismic images while image processing algorithms extract information. Based on these analysis, explorations are carried out. This process minimizes human risk and ensures accurate data.

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Topics: Artificial Intelligence, AI

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