Predictive maintenance has been broadly used in the oil and gas industry over the past 20 years. The volatile oil market is one of the key reasons for the increased use of predictive maintenance. This is because companies are looking to reduce costs associated with unplanned downtime.
How does predictive maintenance work? The predictive maintenance system monitors the equipment in real-time with various condition monitoring sensors such as vibration, temperature, sound and voltage. Based on historical trends identified, the system can accurately predict the likelihood of a machinery malfunctioning. As such, the system will alert the machine operator to send a repair technician before any catastrophic machinery failure happens.
Hence, predictive maintenance can help companies to optimize their maintenance schedules, drive efficiency and lower operational costs. Moreover, according to the IEA’s 2018 gas market report, the global demand for gas is anticipated to rise by an average of 1.6% per year, reaching over 4 trillion cubic metres (tcm) by 2022. The higher demand for gas means the usage of more oil rigs. With the inevitable wear and tear on the equipment, a smarter approach towards maintenance strategies is needed. As such, there will be a greater need for predictive maintenance.
Why is predictive maintenance important?
Predictive maintenance allows you to fix your machines before it fails, preventing an expensive sudden equipment failure. Through predictive maintenance, you can monitor your machine health and diagnose potential issues remotely. Furthermore, it may also have a severe domino effect on energy supply if oil and gas equipment break down for a prolonged period of time, bringing catastrophic implications. Therefore, predictive maintenance comes in as a useful friend for companies in the oil and gas industry.
Following are the three reasons why we think the oil and gas industry needs to look into predictive maintenance.
1. Reduce cost
Not only is periodic scheduled maintenance costly, but it is also not foolproof in preventing unplanned downtime. Research shows that a mere 3.65 days of unplanned downtime can cost an oil and gas company $5.037 million, and on average, an offshore oil and gas company experiences about 27 days of unplanned downtime each year. This means that a company will potentially lose around $38 million due to unplanned downtime. That is a huge loss to any organisation, and any reduction in this loss can bring a huge boost to a company’s bottom line.
According to the U.S. Department of Energy, predictive maintenance helps to save between 8% to 12% over preventative maintenance. It also helps companies to save over 30% to 40% relative to reactive maintenance. Clearly, predictive maintenance is the most cost-effective maintenance strategy as compared to preventative and reactive maintenance strategies.
This is because the predictive maintenance deployment aids companies in early detection of machine faults and allows companies to arrange for maintenance works in advance. As such, unplanned downtime will be minimized whilst reducing the need to perform excessive scheduled maintenance, thus lowering associated operating costs.
2. Drive efficiency
On top of reducing costs, the insights gathered from predictive maintenance allow decision-makers to plan maintenance activities without affecting regular operations. Moreover, the system allows the companies to streamline maintenance activities as they just need to fix the right problem at the right time. Concurrently, this also helps companies to manage the spare parts efficiently.
According to McKinsey, the oil and gas equipment runs at just 77% of its full output capacity on average. This shortcoming in the oil and gas industry reflects about 10 million barrels a day or $200 billion in annual revenue. This is apparent as industry giants such as ExxonMobil, Shell and BP are using predictive maintenance to save costs and optimize their equipment performance.
“What’s more, McKinsey’s study found that predictive maintenance could minimize unplanned downtime by 30% to 50% and improve the machine’s useful life by 20% to 40%.”
Therefore, to stay competitive, it is crucial for oil and gas companies to implement predictive maintenance to improve the equipment’s productivity and output capacity.
3. Ensure safety
42% of the offshore infrastructure such as development, exploration and drilling equipment are over 15 years old on average. The aging infrastructure is dangerous in terms of unanticipated failure and may cause accidents to happen. A publication indicates that there have been several oil and gas exploration accidents, with 481 hospitalizations and 166 amputations occurring between January 2015 and February 2017. All these can be potentially minimised if companies are better aware of the performance of their current infrastructure and equipment.
Therefore, it is vital for oil and gas companies to prevent the occurrence of such incidents and to provide their employees with a safer working environment. With predictive maintenance, the workers will be able to pinpoint the exact problem. The system also enables the workers to evaluate if it is safe to get in and fix the problem.
Where to apply predictive maintenance in the oil and gas industry?
The upstream section is the process of exploring and extracting oil and gas via a network of wells and pumps. In the case of any inefficiencies attributable to unplanned downtime, oil and gas production rate and revenue would also be impacted. Operators can therefore use predictive maintenance to monitor the productivity of the equipment and components during operation in real-time.
If there is an emerging problem, the system would provide the operator with early warning alerts. This allows the operator to schedule maintenance activity that would not have too much impact on production, which would then optimize production planning.
The midstream section consists of transporting and storing oil and gas. Pipeline, barge, tanker, truck or rail are commonly used to transport the oil and gas. The oil and gas are stored either in storage tanks or underground facilities.
Hence, it is crucial to monitor the transportation and storage facilities to detect oil leakages. For example, acoustic sensors can be used to identify sound variations produced, which could signal liquid or gas leakage. This helps operators to optimize their transport and storage management and perform risk evaluation of the pipelines.
The downstream section is the process of refining, distilling and distributing the oil and gas to end-users. It is very important and common to maintain the pumps and compressors for the equipment in units such as oil distillation, diesel hydrotreating, etc. This is because any unplanned downstream failure would affect oil and gas trading.
Just in the U.S. alone, oil and gas refiners lose over $6.6 billion a year due to unplanned downtime. Therefore, operators should leverage predictive maintenance to ensure that the equipment is working well, and fix issues before a failure occurs to prevent losses.
Towards the future
It is a tough environment for companies in the oil and gas industry due to the volatile oil market and costly maintenance when things go wrong. With predictive maintenance, companies can have greater control of equipment health and prevent expensive unplanned downtime. In addition, a proper predictive maintenance program would make for a more effective maintenance schedule and improve maintenance budget planning.
Here at Groundup.ai, we have extensive expertise in the field of artificial intelligence (AI) and predictive analytics. These technologies are highly capable of supporting oil and gas companies with the implementations of predictive maintenance for equipment. Come and have a chat with us to find out more details.