The oil and gas industry pulls in a massive $4.3 trillion in revenue as of 2023. AI in oil and gas is a vital technology that keeps this enormous operation running smoothly. Most companies in this sector – over 92% – are already investing in artificial intelligence or plan to do so soon.

This widespread adoption has pushed the AI market in oil and gas toward significant growth. Experts project an increase from $3.14 billion in 2024 to $5.7 billion by 2029. Companies see impressive results already, with AI integration reducing operational costs by up to 20%. Shell’s experience shows how predictive maintenance helps cut unplanned downtime by 20% and slashes maintenance costs by 15%.

This piece will show how AI transforms equipment maintenance in the oil and gas industry. You’ll learn why it has become essential to prevent failures that can get pricey.

The True Cost of Equipment Failures in Oil and Gas

Equipment failures in oil and gas operations devastate finances industry-wide. A single hour of downtime now costs oil and gas facilities nearly $500,000. This amount has more than doubled from what it was two years ago.

Annual Industry Losses from Unplanned Downtime

Equipment failures have pushed financial losses to new heights. Fortune Global 500 industrial organizations lose about $1.5 trillion each year due to unplanned downtime. These losses make up 11% of their yearly turnover. Oil and gas facilities now face yearly losses of $149 million from unplanned downtime. This represents a dramatic 76% increase over the last several years.

Short interruptions can get pricey. Just 1% downtime (3.65 days) leads to annual losses of over $5 million. Upstream companies face an average of 27 days of unplanned downtime yearly. This results in costs reaching $38 million.

Hidden Costs Beyond Equipment Repair

Equipment failures affect businesses way beyond the reach of immediate repair costs. These hidden costs include:*Workers and operations sitting idle, leading to lost productivity

Spills and leaks causing environmental damage

Penalties from regulators and legal issues

Disrupted supply chains affecting downstream customers

Damaged brand reputation and lost customer trust

Supply chain disruptions hit oil and gas operations hard. These facilities produce raw materials that many industries need. Equipment failures trigger heavy contractual penalties. Early-stage producers face the worst financial fallout as these penalties cascade down the supply chain.

The Norilsk diesel oil spill in Russia (May 2020) shows these far-reaching effects. An equipment failure caused 17,500 tons of diesel oil to pollute nearby rivers. This led to massive environmental damage and cleanup costs.

Companies now realize that traditional time-based maintenance doesn’t cut it anymore. They spend up to 20% of their operational budgets on unplanned maintenance. Rising downtime costs and this big spending show why predictive maintenance is vital to prevent catastrophic failures in the oil and gas industry.

Building the AI-Powered Early Warning System

AI-powered early warning systems in oil and gas operations now depend on advanced sensor networks and data processing frameworks. These systems analyze operational conditions without stopping. They can detect equipment failures hours or even days before they happen.

Required Sensor Infrastructure

A complete sensor network serves as the foundation for predictive maintenance systems. Smart sensors must be embedded throughout oil and gas sites to track critical parameters. These sensors monitor several equipment conditions:

Temperature fluctuations and hotspots

Vibration patterns and acoustic signals

Pressure variations and fluid levels

Rotational speed measurements

Equipment voltage fluctuations

Data Collection Framework

The data collection process works through a two-stage historian system. The offshore historian stores immediate operational data to ensure quick access for urgent analysis. This information then moves to an onshore historian for complete review and long-term storage.

A dedicated data pipeline moves the collected information to cloud environments regularly. The system also combines event-based data from Computerized Maintenance Management Systems (CMMS) and daily progress reports to boost predictive model accuracy.

Real-time Monitoring Setup

The monitoring system analyzes data streams immediately and spots subtle anomalies that could signal developing problems. Computer vision technologies get into equipment conditions through video feeds and add another layer of monitoring capability.

Condition-based monitoring helps the system watch over critical equipment like drilling rigs and pipelines. The system triggers maintenance alerts when readings show a performance decline. This proactive approach prevents equipment failures. Some systems can send warnings up to one full hour before potential breakdowns.

Machine learning algorithms process big amounts of sensor data to create detailed models of equipment health. These models are remarkably accurate – reaching up to 92% in predicting potential failures. The AI system spots irregularities that human operators might miss by analyzing operational patterns continuously. This allows timely interventions before small issues become major failures.

Implementing Predictive Maintenance with AI

Oil and gas facilities need to pay close attention to data quality and system architecture for predictive maintenance to work. Studies show that poor data quality causes 80% of AI project failures in industrial settings.

Data Quality Requirements

Quality data is the lifeblood of predictive maintenance systems. Oil and gas companies must meet specific criteria for AI implementation. Raw sensor data needs proper cleaning and preprocessing. This includes normalizing and standardizing measurements across different sensors.

Data validation processes must verify the integrity of these data sources:

Sensor readings from equipment

Maintenance logs and historical records

Operational data from legacy systems

Environmental condition measurements

Yes, it is essential to have strong data quality management. This helps prevent AI “hallucinations” – incorrect or misleading predictions that happen when models train on poor quality data.

Machine Learning Model Selection

We selected machine learning algorithms based on the specific failure modes under monitoring. Decision trees and random forests work best at spotting clear patterns in equipment behavior. Neural networks handle complex, non-linear relationships in operational data more effectively.

Historical data is split into two parts to train these models. The split typically uses 70-80% for training and 20-30% for testing. Notwithstanding that, the model’s performance needs constant evaluation. Metrics like accuracy, precision, and recall ensure reliable predictions.

Integration with Existing Systems

The integration phase creates major challenges due to aging infrastructure and legacy systems in oil and gas facilities. AI implementations often hit roadblocks with data silos and incompatible formats across operational technologies.

Trailblazing solutions include data integration platforms and middleware that connect modern AI systems with existing infrastructure. Research indicates that oil and gas companies invest heavily to ensure uninterrupted communication between predictive maintenance systems and legacy equipment.

Performance monitoring plays a significant role after implementation. The system needs regular recalibration as new failure data comes in. This ensures AI models adapt to changing operational conditions. Such ongoing optimization helps companies cut maintenance costs by up to 40% by preventing unplanned downtime.

Real-World Success Stories and ROI

Oil and gas giants have seen amazing returns after adding AI to their maintenance operations. Their success stories show how predictive maintenance systems work in the real world.

Shell’s 40% Reduction in Downtime

Shell’s experience with AI focuses on equipment monitoring and maintenance optimization. Their system processes over 20 billion rows of data weekly from more than 3 million data streams. The company keeps track of more than 10,000 equipment pieces using AI-powered predictive maintenance. This generates over 15 million predictions each day.

The results speak for themselves:

40% reduction in equipment failure-related incidents

20% decrease in maintenance costs, saving about $2 billion each year

35% reduction in unplanned downtime, which led to a 5% boost in operational uptime

Shell’s Netherlands refinery’s AI system spotted 65 control valves that needed repair. Traditional methods had missed these issues. This early detection stopped potential hydrocarbon breakthroughs downstream and ended up avoiding production losses and environmental risks.

BP’s $10M Annual Savings

BP has cut costs significantly through its AI projects. The company put $5 million into Belmont Technology’s AI platform “Sandy.” This platform aims to cut data collection, interpretation, and simulation time by 90%.

The investment paid off well as BP grew its AI capabilities worldwide. Their digital platform looks at live data to optimize energy asset performance. This created big savings through better flexibility and improved renewable generation management.

BP looks beyond just saving money with AI. They bought AI-driven energy optimization company Open Energi. Their Dynamic Demand 2.0 platform uses artificial intelligence to cut electricity costs. The system analyzes and optimizes assets while reducing energy use during expensive peak periods.

These AI solutions help BP keep electricity grids stable and make use of low-carbon energy resources. Their AI-optimized energy asset network now handles over 80MW of total capacity. This shows how predictive maintenance and broader operational improvements work together to deliver great returns on investment.

Overcoming Implementation Challenges

AI systems in oil and gas operations come with unique challenges that we just need to think over and plan carefully. The benefits are huge, but companies must tackle several critical aspects for successful deployment.

Data Security Concerns

Oil and gas companies face their biggest problem in cybersecurity as they connect AI systems with critical infrastructure. AI systems’ interconnected nature creates weak spots that bad actors might exploit. Companies must build strong security measures to keep sensitive operational data safe.

Key security challenges include:

Data pipeline attacks can harm the whole data collection and training process

Model control attacks where malware can mess with decision-making processes

Supply chain weak points through third-party software components

Companies alleviate these risks with detailed security protocols. They run regular security checks, encrypt sensitive data, and watch system access closely. They also stay compliant with industry rules while protecting data privacy.

Staff Training Requirements

The lack of experts who know both AI and oil and gas operations creates a tough challenge. Right now, 29% of executives say their core team’s knowledge gap is what holds back AI implementation.

A good training program has:

Technical training for specific AI tools and applications

Knowledge of oil and gas processes

Cybersecurity awareness and best practices

Data quality management protocols

We focused on improving existing employees’ skills through mutually beneficial alliances with educational institutions. This helps fill the talent gap while keeping industry knowledge intact. The companies also create training programs to help staff understand what AI can and cannot do.

Budget Allocation Strategy

AI implementation needs smart budget planning because of its high costs. The original expenses include software, hardware, training programs, and maintenance. Companies must get a full picture of the costs and benefits to back these investments.

A smooth budget allocation covers:

1. Infrastructure Investment

Sensor deployment and maintenance

Data storage and processing capabilities

Security system implementation

2. Operational Costs

Staff training and development

System maintenance and updates

Data quality management

3. Risk Management

Cybersecurity measures

Compliance requirements

Contingency planning

Companies can make their budgets work better with live analytics that shows accurate projections based on past and current data. This helps them prepare for different maintenance scenarios and adjust their budgets.

The implementation works best when companies watch their budget performance and get automatic alerts if spending goes over set limits. Budget plans need to stay flexible to handle new challenges and opportunities in AI implementation.

Conclusion

AI-powered predictive maintenance is revolutionizing how the oil and gas industry handles equipment failures. Companies now detect potential breakdowns days in advance through sensor networks and machine learning algorithms. This technology helps reduce the $1.5 trillion yearly losses caused by unexpected downtime.

Industry leaders have already proven the remarkable benefits. Shell reported 40% fewer equipment failures, while BP saves $10 million every year. These results come from well-planned implementation strategies that focus on quality data collection, proper model selection and system integration.

The oil and gas sector keeps moving toward AI-driven maintenance solutions despite concerns about cybersecurity, staff training and budgets. Companies that tackle these challenges while keeping strong security measures and detailed training programs can prevent expensive failures before they hurt operations.

This move to predictive maintenance is changing oil and gas operations fundamentally. A single hour of prevented downtime saves up to $500,000. Companies that use these solutions as sensor technology and AI capabilities improve will gain competitive edges and protect their assets and environment better.

By: Energies Media Staff / February 8, 2025.

A group of EU member states that have the largest natural gas storage capacity have held informal discussions about a potential easing of the binding filling targets after 2025, officials have told Bloom-berg.

In the wake of the 2022 Russian invasion of Ukraine and the halt to Russian pipeline gas supply to most EU countries, the European Commission adopted a target for EU natural gas storage levels to be 90% full by November 1 of each year, ahead of the winter. There are also intermediate targets for February 1, May 1, July 1, and September 1, 2025, as the EU looks to be prepared for the winter gas demand with nearly full storage sites.

However, policymakers in a group of EU countries, including Germany, Italy, and the Netherlands, are concerned that the high forward gas prices for the summer months would make it unprofitable for gas companies and marketers to store gas.

Federico Boschi, chief of the energy department at Italy’s Ministry of Environment and Energy, told Bloomberg that Italy would consider requests from other EU member states, including Germany. Italy could support easing of the targets, Boschi added.

Pieter ten Bruggencate, spokesperson for the Dutch energy ministry, told Bloomberg that the Netherlands would back an ambition rather than a target for gas storage.

France, Germany, and the Czech Republic are also in the group of countries that have discussed easing of the targets, according to ten Bruggencate.

Meanwhile, the European Union is considering extending the binding natural gas storage targets for EU member states for at least another year after the current goals expire at the end of 2025, EU diplomats told Reuters at the end of last month.

Ahead of this winter, EU gas storage was around 95% by the deadline of 1 November.

However, colder winter weather – unlike the previous two milder winters – and periods of low wind speeds in most of northwest Europe have been draining EU storage sites at their fastest pace in eight years.

By Tsvetana Paraskova for Oilprice.com / Feb 05, 2025

Saudi oil giant Aramco’s Chief Executive Amin Nasser said on Tuesday he sees the oil market as healthy and expects an additional 1.3 million barrels per day of demand this year.

Speaking to Reuters on the sidelines of the World Economic Forum in Davos, Nasser was responding to a question on the impact of U.S. President Donald Trump’s energy decisions, which could increase U.S. hydrocarbon output.

Oil demand this year will approach 106 million barrels per day after averaging about 104.6 million barrels per day in 2024, he said.

“We still think the market is healthy … last year we averaged around 104.6 million barrels (per day), this year, we’re expecting an additional demand of about 1.3 million barrels … so there is growth in the market,” he said.

Asked about U.S. sanctions on Russian crude tankers, he said the situation was still at an early stage.

“If you look at the impacted barrels, you’re talking about more than 2 million barrels,” he said. “We will wait and see how would that translate into tightness in the market, it is still in the early stage.”

Asked if China and India have sought additional oil volumes from Saudi Arabia on the back of the sanctions, Nasser said Aramco is bound by the levels the kingdom’s energy ministry allows it to pump. Saudi Arabia has been pumping at about three quarters of its output capacity, as part of agreements with OPEC+ to support the market.

“The kingdom and the Ministry of Energy is always looking at balancing the market. They take that into account when they give us the target of how much we should put in the market,” he said.

Aramco is working with MidOcean, an LNG firm in which it took a 51% stake, and “looking at expanding our position globally in LNG,” without giving details, Nasser said.

By Marwa Rashad, Reuters / January 21, 2025

Shell’s green hydrogen factory: a solar panel on a petrol pump – De Correspondent

ow a modest construction site on the windy Tweede Maasvlakte, soon Shell’s very latest factory. Under the sway of wind turbine blades, the oil and gas giant is building a place where, starting in 2026, sixty thousand kilos of ‘green hydrogen’ will be produced every day: Holland Hydrogen 1. ^*

Ben van Beurden, then CEO of Shell, at the announcement in 2022, said :

We are building the factory of the future

But the factory, which Shell sees as a ‘ new chapter in the energy transition’, ^* in reality hardly yields any gain for the climate. This becomes clear when we calculate the CO2 footprint of Shell’s products, with and without the green hydrogen from the new factory.

That sustainable energy experts ^* and even an environmental organization like Greenpeace ^* nevertheless see the factory as a good move, shows how complex the energy transition is in practice. Shell is the only one, they say, that can build such a factory at the moment. And that exposes a broader problem: we have become dependent on fossil companies, in the task of getting rid of fossil fuels.

Green hydrogen is the future

Hydrogen: the tiniest atom of all, perhaps best known for its presence in water (as the ‘H’ in ‘H2O’). Hydrogen is by far the most abundant element in the universe, and you could consider it the most fundamental building block of the universe. It’s not for nothing that hydrogen has atomic number 1. ^*

Unlike fossil fuels, pure hydrogen is not extracted from natural sources or pumped from the ground. Pure hydrogen, a colorless and odorless gas, is made in a factory. This can be done simply by electrifying water to separate the H’s and O’s – and voilà, pure hydrogen gas.

Like natural gas, hydrogen is flammable. ^* When hydrogen gas is burned, no CO2 is released, only water. This property makes it an alternative to fossil fuels.

When a hydrogen plant runs on renewable electricity from wind turbines or solar panels, the hydrogen produced has a zero CO2 footprint, is climate neutral and can be called ‘green hydrogen’.

A gas that you can produce and burn without CO2 emissions: that sounds ideal within the context of the energy transition.

Industry is eyeing green hydrogen. Particularly in sectors where it is difficult to replace fossil fuels such as coal or oil with electricity, green hydrogen is seen as the way to become CO2-free. Think of the steel industry, ^* the production of artificial fertilizer ^* or trucks that have to travel long distances. ^*

Another often-mentioned application of hydrogen: it can serve as a backup for the energy system, ^* necessary in a future with only green electricity. You can burn it – just like natural gas – in power stations to generate electricity during periods when the sun is not shining and the wind is not blowing

Shell’s Holland Hydrogen 1 plant, which will be connected to wind turbines in the North Sea, ^* will be Europe’s largest green hydrogen plant upon completion.

Expectations are high. Rotterdam wants to become the green hydrogen hub of Europe. ^* The hydrogen pipeline from Holland Hydrogen 1 will be expanded in the coming decades to a network that not only covers the Netherlands, but is also connected to the rest of the continent via Belgium and Germany. ^* The EU sees green hydrogen as a ‘key component’ of its transition strategy and wants it to cover no less than 10 percent of the total energy requirement in 2050. That share is currently almost zero. ^*

You could say that Shell is doing well with Holland Hydrogen 1 in promoting the energy transition and combating climate change.

From green to gray

But the green sheen quickly disappears when you follow the route of the (now partly constructed) underground gas pipe – the pipe through which the future green hydrogen will leave the factory and travel to its destination

By: hydrogen-central. January 18, 2025

Funds will go to the construction of green marine fuel storage facilities and new bunkering vessels by 2030

First project involves constructing additional liquid cargo storage facilities at Hyundai Oil Terminal in Ulsan. The port has been designated by the government as a hub for supplying greener marine fuels

SOUTH Korea is launching a green marine fuel infrastructure fund to support the development of environmentally friendly fuel facilities and bunkering vessels.

The fund, co-established by the Ministry of Oceans and Fisheries and the Korea Ocean Business Corporation (KOBC), will invest a total of Won1trn ($680m) by 2030, according to a government statement.

Of the total, Won600bn will be allocated for building port storage facilities for LNG, methanol, and ammonia, while Won400bn is earmarked for constructing four bunkering vessels.

The initiative is designed to meet growing demand for green fuels from South Korea-flagged vessels and ensure reliable fuel supplies for foreign ships calling at domestic ports.

The fund’s first project will involve the construction of additional liquid cargo storage facilities at Hyundai Oil Terminal in Ulsan, at a total cost of Won240bn. Of this, Won130bn will be provided by the fund, with the goal of stabilising methanol fuel demand for both domestic and international vessels.

Hyundai Oil Terminal, which began operations in 2012, features dock facilities for vessels up to 50,000 dwt and approximately 280,000 kilolitres of storage capacity on an 86,821 m² landfill site. Initially established by HD Hyundai Oilbank, the terminal became an independent company after the refiner sold its majority stake in 2021.

The fund’s second project will focus on the construction of the Yeosu Myodo LNG hub terminal, with a total budget of Won1.4trn. The terminal will be built on 270,000 m² of reclaimed land and will include a 100,000 tonne pier, three LNG storage tanks, transportation pipelines, and other facilities. Completion is expected by the end of 2027.

An MoF official told Lloyd’s List the fund was a follow-up to the ministry’s 2023 policy announcement. At the time, the government outlined plans to provide 10%-30% subsidies for the construction of environmentally friendly bunkering vessels and to encourage private investment in green marine fuels through KOBC’s financial backing and guarantees.

The port of Ulsan has been designated as a hub for supplying environmentally friendly marine fuels, as part of the government’s broader strategy to enhance the global competitiveness of South Korea’s ports.

A signing ceremony for the fund’s investment will be held on January 14, with participation from major stakeholders, including Korea Development Bank, Kyobo Life Insurance, Woori Asset Management, MoF, KOBC, and Hyundai Oil Terminal.

The MoF said in a statement: “The ability to supply environmentally friendly marine fuel determines the competitiveness of ports. We will continue to gain competitive advantage through the management of the fund.”

By: Moyoun Jin / 13 Jan 2025

Nigerians may experience a rise in petroleum product prices in the coming days due to the increase in the cost of Brent, the global benchmark for crude. Crude oil price is a key commodity that sets the price of refined petroleum products.

Crude oil prices rise in the international market According to reports, on Sunday, January 12, 2025, Brent crude price reached $79.76 per barrel.

The increase in the commodity price from $72.88 recorded in December 2024 impacted fuel prices across Nigerian depots.

Experts have attributed the rise in price to geopolitical tensions, particularly sanctions on Russian oil exports by the US. Also, supply issues and seasonal demand fluctuations in colder regions may be responsible for the rise in crude prices.

Marketers adjust prices at depots Findings showed that several fuel depots began reporting diesel price increases on Friday, January 10, 2025, marking the beginning of a rise in fuel costs.

Experts have said the Brent crude oil price surge is a major driver, as many Nigerian depot owners depend on it to meet diesel demand.

The relationship between crude oil prices and refined products is well-established, as Brent is a global benchmark for petroleum product pricing.

With crude prices increasing, importers are likely to implement new prices to cover higher procurement and shipping costs.

The Nigerian government’s oil price benchmark in the 2025 budget projects price at $75 per barrel. According to available data, diesel price movements at the loading depot indicate that NIPCO depot, in law, increased their prices by N70 from Friday, January 10, 2025, from N1,050 to N1,120 per litre.

Punch reports that Prudent Depot increased its prices to N1,045 from N1,025 per litre. Marketers give reason for the slow distribution of fuel Energy analysts disclosed that depots were on standby to increase loading prices of refined petroleum products beginning Monday, January 13, 2025.

Meanwhile, marketers have blamed the slow pace of construction work on the East-West Road for the poor distribution of petroleum products from the Port Harcourt refinery.

The Petroleum Retail Outlet Owners Association of Nigeria (PETROAN) said the slow pace of work on the East-West Road has impacted about 60 filling stations.

Marketers and oil companies partner to build new refinery Legit.ng earlier reported that Petroleum products marketers and three oil firms inked a deal to build a 50,000 barrels per day capacity refinery, PETROAN signed the agreement with Claridge Petroleum Company Limited, Oasis Petroleum Products Limited and another company on Wednesday, January 8, 2025.

By:Pascal Oparada, Legit / January 13, 2025.

ADNOC Gas plc and its subsidiaries (“ADNOC Gas”), a world-class integrated gas processing company, announced on January 9 the awarding of three enabling contracts worth $2.1 billion for an LNG pre-conditioning plant (LPP), compression facilities and transmission pipelines to supply feedstock to the Ruwais LNG Project.

The LPP and compression facilities will be located within ADNOC Gas’ Habshan 5 plant, part of one of the world’s largest integrated gas processing complexes. The five plants of the Habshan Complex have a combined capacity to process 6.1 billion standard cubic feet of gas per day. The newly awarded transmission pipelines will connect the Habshan Complex with the Ruwais LNG facility.

The largest contract, valued at $1.24 billion for the LPP, was awarded to a consortium consisting of Engineering for the Petroleum and Process Industries (ENPPI) and Petrojet. A $514 million contract for transmission pipelines was awarded to the China Petroleum Pipeline Engineering Company, while Petrofac Emirates LLC will develop the new compression facilities under a $335 million contract. 

Fatema Al Nuaimi, Chief Executive Officer of ADNOC Gas, said: “These contract awards reaffirm ADNOC Gas’ commitment to delivering sustainable growth and maximizing shareholder value. We are investing in world-class infrastructure and innovative technologies as we expand our capacity in LNG liquefaction and strengthen our position as a global player.
 
The awards also underline our commitment to making strategic and targeted investments that enable the delivery of our most significant projects, allowing us to continue meeting our customers’ demands internationally.”

ADNOC Gas is developing the Ruwais LNG project on behalf of its largest shareholder, ADNOC. The capital expenditure (CAPEX) for the LPP, compression facilities and transmission pipelines, does not form part of the costs previously outlined by ADNOC Gas for its intended acquisition of ADNOC’s majority stake in the Ruwais LNG project once the plant becomes operational in 2028.

The three contracts will establish the key infrastructure needed to supply feedstock to the Ruwais LNG export facility. This investment is part of the $15 billion CAPEX plan through 2029, as outlined in ADNOC Gas’ recent strategy update.

When it becomes fully operational, the Ruwais LNG plant will more than double ADNOC Gas’ current LNG production capacity to more than 15 million tonnes per annum (mtpa). The export facility will feature two liquefaction trains, each with a processing capacity of 4.8 mtpa, powered by clean grid electricity—a first in the Middle East and North Africa region.

Upon completion, Ruwais LNG will be one of the lowest-carbon intensity LNG plants in the world, leveraging artificial intelligence and other advanced digital technologies to enhance safety, minimize emissions and drive efficiency.

ADNOC Gas which refers to ADNOC Gas Plc and its subsidiaries, is a world-class, large-scale integrated gas processing company operating across the gas value chain, from receipt of feedstock from ADNOC through large, long-life operations for gas processing and fractionation to the sale of products to domestic and international customers. ADNOC Gas supplies approximately 60% of the UAE’s sales gas needs and supplies end-customers in over twenty countries.

By: portnews / January 11 2025

Worker safety has come a long way in the past few decades with less than half the number of incidents and worker deaths per 100 workers in 2024 than there were in the 1970s. 

But there are innate dangers in the oil and gas sector where workers may be exposed to hazardous environments, exposure to hydrocarbon gases and vapors, heavy machinery and equipment and innately dangerous working spaces (such as high up on an oil platform).

In 2020, the U.S. Bureau of Labor Statistics recorded 44 employee deaths in the oil and gas extraction industry.

The Occupational Safety and Health Administration (OSHA) in the United States recommends that all oil and gas companies have strict policies and procedures in place to help mitigate the risk from these hazards and ensure that all workers and contractors have the appropriate levels of training and PPE to prevent injury.

READ: How Chevron and Chevron Phillips Chemical are Prioritizing Worker Safety in Remote and Hazardous Environments

Here are the top 5 key safety risks in oil and gas:

#1: Vehicle Collisions

The Center for Disease Control says that motor vehicle crashes cause almost half (over 40%) of work-related deaths in the oil and gas extraction industry. Long shifts patterns and/or long-distance travel to remote well sites may contribute to these crashes as can driver fatigue.

#2: Struck-By/ Caught-In/ Caught-Between

Oil and gas worksites have all sorts of moving vehicles and heavy equipment (such as cranes or hoists), high pressure lines, elevator bales, and others. Getting hit by or caught between falling or moving equipment causes approximately 60% of on-site work fatalities in oil and gas extraction.

#3: Explosions and Fires

By its very nature, oil and gas workers operate around explosive and flammable gases. These gases may come from many sources, according to OSHA, including production equipment, tanks, shale shakers, trucks, and wells. Workers must take extra care when performing operations such as welding in environments where explosive potential exists.

#4: Falls

Falling from a high platform such as a mast or drilling platform is another risk that workers in the oil and gas industry face. To mitigate these risks, employers must ensure that workers have appropriate training and “fall arrest” mechanisms – such as safety harnesses – must be in place when workers are at height. Some fall deaths in the industry can be attributed to incorrectly following procedures or inadequately applied safety mechanisms.

#5: Confined Spaces

Oil and gas operations include confined spaces such as storage tanks and pits. When workers enter these environments, they can be exposed to hazardous or flammable chemicals. Extra care must be made to wear protective equipment and continuously monitored if they are known to harbor potential atmospheric hazards.

Other risks include lifting heavy items, which may result in back or muscle injuries, risks of blowouts from lines or equipment under high levels of pressure, and electrical or other energy hazards.

Interested in learning more?

Join over 300 digital and operations leaders at The Connected Worker: Energy Summit, taking place March 18-20, 2025, in Houston, TX. Discover how to create a safer work environment, boost compliance, and improve efficiencies through automation. This year’s summit will focus on increasing collaboration, eliminating organizational silos, and enabling cross-functional decision-making across the asset lifecycle and supply chain.

By: Oil & Gas IQ , 08 January 2025