According to Kimberlite's research, only 3.65 days of unplanned downtime in a year can cost an oil and gas company $5.037 million. An offshore oil and gas company experiences an average of about 27 days of unplanned downtime each year, which may cause losses of $38 million. In some cases, this figure may be as high as $88 million.
In order to eliminate the risk of unexpected equipment failure and maximize the return on assets, oil and gas companies are seeking new and more effective maintenance methods. In this article, we will introduce why we need to consider predictive maintenance solutions based on the Industrial Internet of Things (IIOT).
The following are the actual benefits of the Industrial Internet of Things to the oil and gas industry:
01 Predictive and preventive maintenance
Oil and gas business activities need to be monitored regularly, because a wrong action may cause irreversible losses within a few milliseconds. Facilities equipped with remote services can meet these challenges through predictive maintenance. Machines need to be monitored regularly to assess wear and tear. Predictive maintenance can provide insight into the current status of specific equipment components and know in advance which components need to be repaired, replaced or shut down. The IoT sensor on the machine collects data and can alert the organization of equipment failures, waste of funds, loss of labor time, etc. With predictive maintenance data, it is easier to show large differences, thereby separating required activities from unnecessary activities. This is a good reflection of the profit margin-this is a reliable indicator of plan improvement and optimized execution.
02 Asset tracking and monitoring
The oil and gas industry is under constant pressure to improve safety and operating procedures, and is facing significant price fluctuations. In order to be prepared, organizations are spending more time analyzing their investments and internal operations in order to obtain a clear view where possible, and encourage the full use of assets without hindering the overall business, and conduct practical Cut or change.
Since asset management can increase productivity levels, it can significantly affect operational performance. Optimization makes asset management more predictable production. When different organizations want to transform and digitize their operations, integrating asset intelligence into one platform creates a stronger foundation, for example, being able to monitor multiple oil wells or sites simultaneously.
03 Improve data management
Some oil and gas technologies are outdated, which has prompted the industry to consider redesigning with digital technology, which will help the industry match the pace and creation of new connectivity technologies and improve data collection.
When efficient, safe, effective and appropriate practices occur, the real transformation takes place. Through networked devices, large amounts of data can be collected and accessed, and integrating this data into new technologies and processes can provide more insights and further improve processes.
04 Health and Safety
Due to unpredictable dangerous events, many accidents have occurred in the oil and gas industry. The adoption of the Internet of Things system that can realize automatic remote monitoring has greatly improved the dangerous working environment of oil drilling platforms and natural gas plants. When fewer manual operations and more automated operations are involved, the probability of occurrence of health and safety risks will be much less. The Internet of Things can increase these possibilities and provide a higher level of security for workers in the park.
Companies that use predictive maintenance in the oil and gas sector:
01 Royal Dutch Shell
Shell has been at the forefront of adopting predictive maintenance technology to improve equipment reliability and extend the overall life of its assets. The company uses artificial intelligence and machine learning in predictive maintenance to help reduce operating costs and environmental risks caused by equipment failure.
ExxonMobil uses predictive maintenance to evaluate its diverse portfolio of upstream, midstream and downstream assets. It has installed sensors in multiple facilities to capture data about the condition of the equipment and analyze the data to ensure optimal performance and detect potential failures. The company has partnered with Microsoft to use its Microsoft Azure cloud computing platform and data analysis tools to deploy predictive maintenance technology in Permian shale assets in western Texas and southeastern New Mexico.
BP has extensive experience in working with technology companies and deploying digital technologies in its global oil and gas business to maximize productivity. The company has deployed predictive maintenance technology in its upstream business, resulting in higher equipment uptime.
Chevron relies on digital technology to optimize drilling and completions, and improve the rate of oil extraction and the performance of its equipment and downstream facilities. The company runs diagnostic programs to identify failures that may cause failures and captures sensor data in the cloud. Chevron has adopted cloud-based data analysis methods to predict equipment failures at its refineries.
Rosneft is investing in the latest technology to explore uncultivated territories in the Arctic and Far East to offset the decline in production from mature Russian oil fields. The company is using predictive maintenance and other digital technologies to promote growth and sustainability. Since 2013, the company has cooperated with the multinational corporation General Electric to develop and implement IoT technologies for its liquefied natural gas (LNG) liquefaction plants, refineries and petrochemical plants.
06 Equinor, Norwegian national oil company
Equinor is implementing the digitization of its upstream business to reduce operating costs and reduce carbon footprint. In 2018, the company established an integrated operations support center in Bergen, Norway, to remotely monitor and diagnose its oil and gas assets on the continental shelf. These land support centers strengthen existing monitoring centers and speed up the decision-making process.
Equinor is implementing the digitization of its upstream business to reduce operating costs and reduce carbon footprint
Repsol is embracing digital transformation to improve productivity and equipment health. The company's maintenance costs have dropped by approximately 15%, and operating costs have been saved by $200 million annually. Repsol is using analytics, machine learning and artificial intelligence to enhance its predictive maintenance solutions and logistics optimization.
Artificial intelligence-driven predictive maintenance has become the backbone of Total's global business. The company is using this expertise to deploy predictive maintenance and other digital technologies in the cloud. It has cooperated with Google Cloud to develop and deploy artificial intelligence-driven software for geophysical data analysis and equipment monitoring.
09 ConocoPhillips ConocoPhillips
ConocoPhillips deployed predictive maintenance technology to optimize maintenance operations and reduce failures and costs. The company uses state-of-the-art technologies, such as drones and data analysis, to inspect equipment and infrastructure, and schedule maintenance activities.
Taking appropriate measures in real time through industrial IoT applications can improve the operational efficiency of the oil and gas industry. There are also various processes in the industry that require industrial IoT solutions to provide assistance, and all of these can be carried out in an ecosystem composed of upstream, midstream and downstream participants. With the Industrial Internet of Things, the global oil and gas industry can gain a competitive advantage in a short period of time and open the door to growth and expansion at the same time