Artificial Intelligence in Oil and Gas Industry - Benefits & Use cases

Running an oil and gas industry is full of highs and lows as the companies are constantly juggling with increasing costs, keeping workers safe in hazardous conditions, and making data-driven decisions with fewer resources.

Traditionally, analysing geological datasets was a challenging task, but now Artificial Intelligence and Machine Learning make it possible by digitizing the entire value chain processes.

For some teams, it's predicting equipment failures before they occur through predictive analytics, while in other areas, it has become a helping hand in the oil exploration field. For oil and gas engineers, it has become a digital mentor to do their jobs better and faster. 

In this blog, let's learn more about what potential AI offers in the oil and gas industry, its benefits, and what challenges it creates. 

Top 8 use cases of AI in the oil and gas industry 

Here are the few applications of how oil and gas companies can use AI for - 

1. Forecast demand for oil and gas products 

Initially, it was challenging for oil and gas companies to forecast future demand and decide the right prices for products. 

Bad part? Traditional forecasting methods don't give a true picture of external factors such as geopolitical events and the impact of the same on your pricing strategy. 

Integration of AI in the oil and gas industry provides you with real-time insights about market demand, geopolitical factors, market trends, weather patterns, etc.  

Through AI-powered demand forecasting, oil and gas companies can ensure that there is neither underutilization nor overutilization of resources. They can make better pricing decisions. 

By understanding production and consumption trends, businesses can save their costs and manage their inventory. They can align their logistics and supply chain activities accordingly. 

2. Predictive maintenance 

The oil and gas industry heavily relies on tools, machines, and vehicles, and everything comes with data, and predictive analytics can be a game changer.  

In the oil and gas sector, predictive analytics is about looking at historical data of equipment through sensors such as pumps, pipelines, or vehicles. If one piece fails, then it would cost companies a million dollars.  

Through artificial intelligence, operators can identify equipment failures in real-time before they affect the production process or cause costly downtimes. 

Companies will do smarter budgeting when data tells them -  

• How often is it likely to break down?  
• What parts fail, and when do they need replacement?  

Oil and gas teams will no longer be at risk when they know what equipment needs upgradation. This way, they can reduce their risks and optimize their processes.  

For instance – GE oil and gas (now Baker Hughes) uses the Predix AI platform for monitoring equipment health. Operators can get real-time insights about equipment failure, such as voltage imbalance.   

It will ensure that power grids will run smoothly, especially at peak times, and optimize the equipment performance.  

3. Oil exploration  

Initially, geologists relied on oil exploration technologies such as seismography and geological mapping to find the location of gas reserves and choose the best drilling spots faster. 

Now, artificial intelligence enhances these traditional methods by helping companies accurately identify suitable drilling locations and reduce drilling risks. 

Shell company is the largest oil and gas company in the world.  

It uses AI-powered drilling systems to help operators understand the drilling environment and identify drill wells that can produce hydrocarbons. Thus, they can use their resources more optimally. 

4. Safety and Risk management  

The oil, gas, and petrochemical industries are prone to more health hazards for human workers as these are the most dangerous industries in the world. Long hours and harsh conditions can result in human errors. 

One way to protect the safety of workers is through simulations that are possible through sensor-based applications. 

Automation can be a game changer in that by replacing repetitive, demanding tasks with machines. Robotic systems can perform tasks safely without requiring humans. Automated sensors and cameras can be used to identify cracks in pipelines.  

These AI-powered sensors can alert gas operators about gas leaks, equipment failures, etc., before they become safety issues. 

When transporting oil and gas products, AI tools even suggest the best traffic route by analysing weather conditions and traffic. This lowers the risk of transporting such hazardous substances. 

5. Robotic process automation  

Robotic process automation involves using robots to perform rule-based repetitive tasks.  

RPA technology brings transformation in the oil and gas industry, where machines will help humans perform their tasks, such as checking equipment and handling paperwork, whether in the back office, oil fields, or during shipping. 

As the oil and gas industry faces labor shortages and the constant pressure of adopting sustainable alternatives, automation can completely transform such a sector.  

Robotic process automation can help oil and gas companies in various ways -  

The oil and gas industry depends on equipment and tools, there comes the need for human personnel to constantly watch things like temperature pressures, tank levels, and compression failures, which can happen anytime. 

• The presence of smart sensors, alarms, and drones can do 24*7 monitoring to ensure that there are no errors and onsite operations are running smoothly.  
• Field operators spend 25% of their total time on their main activities, as most of their time is lost on maintenance and repairs. With automation in field operations, workers' productivity has increased by more than 40%.  
• Wireless networks, fiber connections and cameras, and virtual enhancements can spot equipment issues faster, especially in hard-to-see areas. Such virtually enhanced technologies reduce the cost of maintenance by 10-15%. 
• Since robots can work 24/7, they can take up the routine data entry work and free up finance staff to focus on value addition and strategic activities. 

6. ESG (Environmental, Social, and Governance) & Sustainability 

The oil and gas industry is under pressure how to reduce environmental impact and become more sustainable and achieve green energy goals. AI models tell how many clean energy credits a company needs to stay compliant with environmental rules. 

The system calculates -  

• Emissions based on how much energy a company uses and what they produce  
• Recommends carbon offset purchases to stay compliant with environmental rules  
• Tracks compliances across different jurisdictions. 

Companies like BP and Microsoft use artificial intelligence to monitor their carbon footprints and achieve their sustainability goals.  

They use GHG Protocol APIs and AI engines to track their carbon emissions and see how many credits they need.  

7. Supply chain and logistics optimization  

AI optimizes supply chain and logistics processes in the oil and gas sector by predicting demand at terminals and identifying the transportation industry based on traffic, weather, inventory status, etc.  

Predictive analytics can forecast the market demand for oil and gas products through the analysis of historical data, market trends, and weather conditions.  

This way, oil and gas companies can streamline their fuel distribution, find disruptions in the supply chain, and optimize their logistics processes accordingly. This reduces transportation costs, avoids stock-outs, and improves customer satisfaction.   

This helps companies to predict disruptions in the supply chain before costly breakdowns occur. 

8. AI-powered chatbots for smooth communication  

Oil and Gas companies use AI chatbots to share updates about the transportation of gas from the hub to the destination point. 

As these companies deal with huge amounts of business operations and need continuous updates on extraction activities and equipment failure, the integration of chatbots provides transportation information without emails or messages.   

This reduces the dependency on the transportation support team by automating routine updates and helps you make faster decisions on rerouting or safety checks.  

This oil and gas chatbot is available on B2B and B2C portals and provides multilingual support in 13 languages. 

What are the advantages of using AI in the Oil and Gas Sector?  

Let's talk about what benefits AI provides to Oil and Gas companies - 

1. Take better decisions 

AI is helping oil and gas companies make better decisions as it can analyse seismic data and identify the best drilling spots. This reduces the risk of unnecessary drilling along with lower exploration costs. 

Unlike traditional methods, Generative AI can do analysis of terabytes of data (seismic surveys, well logs) and reduce the risk of exploring dry wells. 

2. Cost Savings  

AI-based technologies can predict the failure of equipment before it occurs. If there is unplanned downtime, then it results in companies losing millions of dollars.  

A study stated that companies that used integrated AI in the oil and gas production process saw a reduction in maintenance costs (fuel costs) and an improvement in operational efficiency.  

3. Saves environmental damage 

One of the major challenges that the oil and gas industry faces is harmful gases such as methane and CO2 that come into the environment.   

Generally, these gases come from pipeline leaks, and AI is used for monitoring those leaks, sending alerts to gas operators and the production team. 

To help oil and gas companies pollute less and comply with environmental regulations, Artificial intelligence helps in the process of carbon capture, utilization, and storage.   

AI stores harmful gases like CO2 before it goes out into the air. It stores it safely underground and helps companies do oil and gas operations sustainably.   

A study states that the usage of AI in the energy sector can reduce CO2 emissions by 10%, which itself is a positive change toward becoming eco-friendly on the planet.  

4. Enhances customer experience  

Oil and gas companies use AI to improve their customer experience and serve them better. Energy Magazine says that – Just like other industries, the energy sector has been planning to adopt AI to increase customer engagement. 

Why? They wanted to provide right information to customers at right time. 

By monitoring the energy usage, companies can understand the energy usage patterns and their consumption and then personalize the customer experience. 

Without even spending a dollar on marketing, companies can get a return on each experience. 

This is just the start of how artificial intelligence can take customer service to the next level. Through AI-powered bots, energy companies can provide round-the-clock support to customers and answer their most-asked queries in multiple languages in real-time.  

That's how companies in the energy sector can save their labor costs without compromising customer service.  

What challenges do oil and gas companies face when they implement AI solutions?  

Artificial Intelligence can offer significant benefits to oil and gas companies, such as reducing costs and automating the work of human staff.  

But here are a few challenges it creates, which are as given below -  

1. The usage of AI tools in the oil and gas industry leads to data quality and integration issues. This industry generates huge piles of data from multiple sources, such as sensors, equipment, and drilling operations. 

Also, the data stored is available in multiple formats and is not good enough, so it's difficult to implement AI in the oil and gas sector successfully.  

2. Currently, there's a shortage of talented software engineers and data scientists that the oil and gas industry needs. The best way is to find skilled developers who know how to implement and deploy AI solutions. 

They should have a domain knowledge in the oil and gas sector.  

3. AI implementation requires significant investment, software, and equipment. The best way is to use AI on a pilot basis and do a cost-benefit analysis to see whether investment outweighs rewards or not. 

This means it's a big hurdle on the part of smaller companies as they've limited financial resources for creating AI systems. 

4. Many oil and gas players deal with outdated infrastructure, and it's challenging to modernize them or integrate AI. 

5. Stakeholders resist to implement technologies such as AI and ML as they go with a traditional conservative approach. That's why it's important for decision-makers in the oil and gas industry to understand and communicate what value AI can bring to different stakeholders. 

6. AI can bring significant risks related to data privacy and violation. There are always complex regulatory standards involved. The oil and gas companies should conduct compliance audits regularly. 

7. Offshore conducted a survey and shared the findings that one of the major challenges oil and gas companies face is integration of AI with legacy systems.  

The results revealed that 39.29% of respondents felt integration with legacy systems was a major challenge.

How does BigOhTech can help Oil and Gas companies through AI/ML solutions?  

Just like AI is gaining momentum in other industries, it's a game changer for the energy sector as well. 

Despite the above challenges discussed in the oil and gas industry, still, many energy companies are on the front-runner side, trying to integrate AI for following tasks- 

• to streamline upstream and downstream operations,
• check equipment failure,
• optimize drilling operations, and
• create intelligent systems that can reduce downtime.

As a custom software development company, we developed an AI-driven chat platform for a national level gas exchange (IGX) to help users analyse market data for key energy trading segments. 

These include the day-ahead market, real-time market, term-ahead market, and day-ahead contingency. 

Users can do conversational queries and get insights based on historical data. Thus, they can make data-driven decisions. 

P.S. - Need help in developing such smart trading systems?