Internet of Things (IoT) in the Oil and Gas Industry - 4 Specific Use Cases

The Internet of Things (IoT) revolution emerged around the turn of the century, first coined by Kevin Ashton as part of an RFID tracking project. Today IoT accounts for around $40 billion of market value, with roughly a quarter of businesses using IoT products. Asset-heavy industries such as oil and gas have particularly profited from the IoT boom.

How? There are many benefits to implementing industrial IoT in the oil and gas industry, including real-time monitoring, automation of manual tasks, and compliance with regulatory standards. Ultimately, oil and gas companies can expect an extremely positive ROI after the initial investment, thanks to a combination of reduced downtime, prevention of production loss, and increased productivity. 

Here are some of those IoT use cases and their benefits: 

  • Real-time production back allocation

  • ALS predictive production issues

  • Hydrocarbon emissions or leak detection

  • Gathering network flow assurance

1. Real-time production back allocation

Knowing what each well is producing, and how it is producing, is critical to maintaining production, as well as planning well interventions when necessary. Typically, an individual well measurement is costly, so the industry standard is to perform a backward distribution of production from the final custody transfer meter to the producing wells, using the latest available well test information and a mass balance of daily production averages. 

However, in addition to being cost-intensive, this process can easily introduce errors in the estimation of the production per well, risking the dynamic information of the process. 

It’s better to perform dynamic modeling of the production system using physical models parametrically adjusted with machine learning techniques. Based on these models, you can perform a real-time mass, energy, and momentum balance to obtain production per well in real time and the pseudo-dynamic behavior of the production. 

Essentially, this means that any events and perturbations in the process are captured. Once this model is built, it can be used to optimize artificial lift systems in real time, find flow assurance problems in real time, and generate predictive recommendations for well intervention. 

2. Artificial lift system predictive production issues

Maintaining artificial lift systems at optimum performance is not easy due to changing reservoir and surface conditions. Additionally, the high number of wells the operator has to service forces them to prioritize the most productive wells over the less productive ones when allocating limited operating resources. In general, the industry has adopted the ad hoc 80-20 rule to service the 20% of the most productive wells that deliver 80% of the production. 

This leaves significant improvements to be had in the remaining 80% of wells if automated systems were in place to monitor them without requiring additional resources. A 12% improvement in these wells would mean almost a 10% improvement in asset production. 


It’s possible to predict operational problems in real time by applying machine learning and real-time simulation techniques to the data that operators currently have in their SCADA systems about their operations in real time. Once you can predict an event, you can also generate automatic notifications to operators for just-in-time intervention. Now your operations that were reactive and consumed too many resources before become the exception, and it is possible to service the entire well with the same resources.

3. Hydrocarbon emissions or leak detection

Oil and gas field operations involve working in areas with a potential risk of hazardous atmospheres, such as H2S levels, which can be fatal to humans. In addition, new environmental regulations regarding the measurement and mitigation of methane emissions are creating new challenges for operators to comply with these regulations with the least possible impact on the profitability of the business. 

Technologies such as the industrial internet of things (IIoT), when combined with purpose-built sensors, provide real-time monitoring of operations and alerts about unwanted emissions, unsafe atmospheres, or exceeding methane emission limits under current regulations. Connecting the IoT H2S or C2 sensors directly to the cloud is a highly effective solution that has no impact on the operator's control infrastructure or IT safety. The cherry on top are the low operational costs typically involved with such a solution.

4. Monitor storage tank levels to prevent spills and leaks

Sand plugging, hydrocarbon precipitation, hydrate formation, or back pressure due to slugging, among others, can create havoc on surface production transportation networks. And no one wants that, especially considering how complex these systems are and the implications of production losses.  

Knowing the real-time pressure profile at every point in the transportation network, as well as the pseudo-three-phase composition, allows you to predict undesirable events and act proactively to mitigate or eliminate production loss. 

Real-time SCADA data together with machine learning techniques applied to physical models with parametric tuning enables the generation of virtual three-phase flow and pressure measurement—at any point of the above-ground production network—making it possible to generate automatic alerts in case of any flow assurance event.

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The ROI of Implementing IoT in the Oil and Gas Industry

If you ask the average person working in an industrial field how expensive IoT is, they’d probably answer that it’s high. While costs have decreased significantly in recent years, thanks to out-of-the-box solutions, the investment remains a significant factor in the decision to implement one of the use cases mentioned above. 

However, the ROI of those same investments almost always overshadows any original investment, in our experience. By using IoT technology, oil and gas companies can streamline their operations, reduce costs, and increase productivity—all of which provide positive ROI in the long term. Time and time again, the benefits vastly outweigh the detractions. 

For personalized consultation on how you can reap the benefits of the internet of things in the oil and gas industry, let’s start a conversation


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