IoT in Oil and Gas Operations: Ensuring Safety and Efficiency
The oil and gas industry is one of the biggest and most lucrative in the world. In the US alone, revenues hit $211 billion in 2021 while global profits climbed from an average of $1.5 trillion in a few prior years to hit $4 trillion in 2022 alone.
Although this can be attributed to an increase in demand and oil prices, the incorporation of the Internet of Things (IoT) has also played a very crucial role. IoT can improve operational efficiency, which in turn reduces costs and translates to an increase in profits.
The deployment of IoT in oil and gas operations involves the use of an interconnected network of equipment and smart devices to collect production data in real-time. The data is then analyzed by use of big data analytics tools to make decisions that impact workflows. The goal is to optimize production processes, reduce wastage, and improve cost efficiency.
Keep reading to understand why IoT is crucial for the oil and gas industry, and how it is specifically applied to achieve efficient production outputs.
Why IoT is important for the oil and gas industry
Oil and gas production faces specific challenges in its upstream, midstream, and downstream processes. Upstream challenges manifest by way of inefficiencies in oil exploration and production. The need for expensive tools and a lack of infrastructure monitoring leaves companies vulnerable to uncontrollable costs. Companies are unaware of maintenance-related failures most of the time, and costs can reach as high as $300,000 for every pump failure.
Midstream challenges exist when there are inconsistencies in transportation processes. Fluctuations in demand demand, temperature, and moisture requirements, are some of the causes. Downstream challenges exist in the form of difficulties in managing sludge and toxic waste.
With IoT technology, oil and gas companies get insight into these frequently-changing upstream, midstream, and downstream requirements. Think of it as a real-time, remote solution that provides a comprehensive view of production processes. From supply pipelines and pipeline risks to environmental impact and regulatory compliance, IoT brings everything together.
Although most of the collated IoT data may often remain unused, taking active steps in IoT utilization opens a huge cost reduction opportunity.
New to IoT apps? This IoT development guide offers a great place to start.
Common applications of IoT in the oil and gas industry
So, how can oil and gas companies utilize IoT streamline operations? IoT application development is central to the deployment of this technology. You definitely need an app that coordinates the various activities that can be driven by IoT.
For more on outsourcing your IoT app development, please have a look at these latest trends in IoT development outsourcing.
Here are the most common applications;
A widespread use of IoT in oil exploration is the use of wireless sensors and machine learning (ML) algorithms to facilitate seismic oil exploration. Seismic oil exploration involves the use of sound waves generated from sources like dynamites to understand the properties of the earth's subsurface.
Although seismic exploration has been around for around 100 years, IoT makes it an even more effective oil exploration technique. Through ML algorithms and real-time analysis, IoT allows companies to understand unique subsurface properties and geographical formations, and hence, make more specific use of seismic waves.
Thanks to IoT ,the earth’s subsurface properties can be understood with more context and, through comparative analysis, the site selection process becomes more accurate.
Another IoT application in oil exploration is virtual rig monitoring. Here, sensors provide real-time data for low-cost rig health analysis and more effective rig management..
With oil and gas processing, IoT proves useful when it comes to refinery management. Some oil and gas companies are deploying sensors on equipment and processes to gather real-time data. Sensors can be installed not only on individual equipment or machinery but also at various points within the refining process to monitor specific parameters.
For example, in a refining process, sensors can be strategically placed along pipelines to measure pressure, flow rates, or temperature. Sensors can also be installed at critical process points to measure specific chemical compositions or reactant concentrations.
With this deployment, refineries can then collect real-time data about the various stages of the refining process. This data helps operators monitor the process and make informed decisions that ensure that the refining operations are running optimally. It also aids in detecting potential issues or anomalies in the process, and this facilitates quick corrective actions.
3. Asset management
The health of oil and gas assets determines the overall efficiency of oil production processes. To harness optimal value, IoT sensors can be planted on critical assets like pipelines, storage tankers, pumps, drilling equipment, and other physical equipment. They help monitor pressure levels, find leakages, measure resource utilization, and determine productivity.
With this, companies can remotely track asset health with more accurate context and engage in optimal enterprise asset management without building costs.
4. Logistics & supply chain management
IoT helps logistics managers deal with supply chain risks better by providing real-time information on bottlenecks and inefficiencies.
Through the analysis of the different supply chain stages, IoT permits more granular insight into supply chain challenges. This allows managers to come up with strategies to unify demand and transportation requirements.
IoT also allows logistics managers to remotely track/manage shipments and inventory, engage in smart logistics billing. This leads to logistical efficiency and a reduction in supply chain losses.
5. Site monitoring
With site monitoring, IoT is most especially useful in facilitating risk management within upstream processes. It’s in upstream processes where companies lose millions of dollars in Non-Productive Time (NPT). This has been shown by this study published in the Springer’s Journal of Petroleum Exploration and Production.
For instance, by utilizing big data on rig output, it’s easy to understand rig productivity from the comfort of remote offices. ML models provide better contextual analysis and introduce robust efficiencies into risk control.
6. Hazard management and employee safety
Without advanced technology like IoT, it’s normal for employees to stay on exploration sites or close to processing equipment to monitor asset health. This exposes them to the risks that come with hazardous work conditions. But IoT makes it possible to monitor hazardous equipment and processes remotely.
What’s more, where employees have to be present at processing or exploration sites, real-time data collection and ML-powered analysis offer easy hazard identification. This helps to kickstart disaster prevention activities faster. On-site employees can be alerted on time whenever there are dangerous developments.
7. Digital Twins
A digital twin is simply a virtual copy of a physical object. Twin here means that the digital version looks and behaves exactly like the physical object. How is this achieved? The physical object is outfitted with sensors that capture the full operational life cycle of the physical object. The data collected by these sensors go to the digital copy in real-time. Likewise, the insights derived by analyzing the data can trigger actions that are then shared with the physical object.
So you have this digital model, looking exactly like the physical object. Thanks to the data that comes from the physical object, the digital model behaves exactly like the physical object. If it's a tanker, for instance, you have a digital copy of it. Through this digital copy, you gain up to date status of the real tanker out there, wherever it is. If the tanker starts to leak, you will know. If it stops suddenly, you will know. Of course achieving this level of operation is not that easy. But this is the representation of how IoT can be applied in the oil and gas industry through digital twins. From the site to the refineries and transit, digital twins can find elaborate use. And you can always start small.
The idea here is to develop a digital replica or “ twin” of on-site production equipment, which creates a better understanding of equipment health and facilitates real-time monitoring.
One main advantage of digital twins is the speed they bring to equipment maintenance and management. Intuitive visual simulations take data presentation a notch up, allowing asset managers to see the status of digitized equipment at a glance. Production scenarios may also be simulated to understand outcomes better and facilitate future decision-making endeavors.
IoT digital twins also bring employees close to real-time representations of production assets without having to risk working in hazardous conditions.
8. Environmental conservation through emission control
IoT aids with environmental impact assessment (EIA), a crucial requirement placed on oil and gas projects. The goal is to protect the environment and biodiversity from degradation. This particular application is powered by real-time comprehensive data collation and intuitive asset visualizations. With this, oil and gas companies can easily monitor parameters such as greenhouse emissions, leakages, and waste spikes across the entire facility.
The incorporation of IoT for oil and gas EIA also aids with meeting compliance requirements, as emission and waste control are made more efficient. In the same light, real-time emissions data can be shared with regulatory agencies to aid and hasten investigations. The same data can also be shared with customers to improve public image. It signals the company’s commitment to environmental protection.
9. Predictive maintenance
IoT can enable prediction of future equipment health statuses. This is possible through analysis of historical data that is collated through sensors over time and during different operational conditions.
For instance, data on vibration, temperature, pressure, and fluid levels are collated over time and, through ML, are used to create trend lines on equipment performance.
This strengthens the effectiveness of maintenance strategies. The consideration of expected performance trends reduces false positives and permits more immediate responses.
10. Operations efficiency
Operations basically refers to the typical routine work in a production facility, whether on site, refinery, transit, etc. So how does IoT improve this?
The automated monitoring capabilities provided by IoT sensors allow oil and gas companies to eliminate time-consuming employee reporting workloads. As a result, employees have more time on their hands to focus on creating more productive business, production, or logistics strategies.
Also, the interconnectedness that IoT brings saves time. Everything is in one place. This means decisions can be made faster. And this contributes to improved operational efficiency.
Limitations of IoT in the oil and gas industry
The most common limitations to IoT applications include:
1. Data security risks
The transmission of sensitive historical and real-time data over a network can present serious cybersecurity risks to oil and gas companies.
A hack into the IoT network will give cyber actors direct access to every piece of information about the company’s upstream, midstream, and downstream systems. This provides an easy loophole for big data theft and operational disruptions.
A study of industrial cybersecurity by Trend Micro reveals that on average, oil and gas companies experienced 6-day system outage due to cyberattacks. A majority of this is caused by malware infection from web browsing, the compromise of internet-enabled devices, exploitation of remote access, and exploitation of IoT cloud services.
2. Network Reliability
In cases where you have IoT sensors installed in remote offshore locations, they may sometimes struggle to provide genuinely "real-time" data on the equipment's status.
This is because the data transmission process over the IoT network may often be significantly affected by issues such as harsh weather or even vandalism.
3. Legacy systems and the lack of interoperability
The difficulty of integrating IoT apps, sensors, and devices with existing legacy systems is another critical challenge.
This is a considerable challenge that could perhaps explain why only 30 percent of oil and gas companies have achieved successful digital IoT transformation. The remaining 70 percent have not gone past the pilot stage!
Even with the availability of digital frameworks that facilitate IoT adoption, the integration of IoT software and hardware from different vendors may prove to be a challenge for most organizations. The key areas that present complex difficulties include unifying IoT data collation, analysis, and comprehensive production system optimization.
4. Technical skill gap
With IoT implementation in oil and gas operations relatively new and the IoT market growing fast, finding IoT professionals with up to date skills has proven challenging. For instance, this survey of 450 companies shows that the lack of in-house IoT professionals proves to be the top barrier to IoT deployment for a third of the oil and gas respondents (34%).
Other emerging challenges to IoT adoption in the oil and gas sector include:
- An overload of data that may be overwhelming for companies
- A demotivating gap between expectations and capabilities
- Lack of trust in ML decisions, especially due to the lack of ML auditing
For more challenges in the wider application of IoT, check this article that covers the typical challenges in IoT connectivity.
With the right strategy IoT promises to bring mega improvements to efficiency and safety in oil and gas operations. This is good news for companies wishing to get the most from this highly profitable industry.
With the cost of IoT devices and installation starting to reduce significantly and the technology having given the early adopters an enviable competitive advantage, it is only a matter of time before the majority of oil and gas players find it a risky position not to invest in IoT. The growth rate is also telling; the application of IoT in oil and gas operations is projected to grow by a CAGR of about 10 percent from $11.34 billion in 2022 to over $22.24 billion in 2029!