Smarter Questions, Faster Insights: Evolving Energy Sector Operations with IoT
With the emergence of IoT and big data, energy companies now have powerful insights to help them meet consumer needs and streamline operations. As IoT usage becomes more mainstream, it’s helping us not only surface new possibilities and answers: it’s also helping us ask smarter questions.
Energy companies are using predictive maintenance to better manage assets and optimize performance, which not only improves safety and increases profitability, but also allows them to gain a competitive edge. And as IoT adoption skyrockets, so does its financial impact on our global economy: In a study by BIS Research, the global influence of IoT in the oil and gas sector is expected to reach $39 billion by 2023, rising at a compound annual growth rate (CAGR) of 24.17 percent from 2018 to 2024. According to McKinsey, the total potential economic impact of IoT across the global economy could top $11 trillion by 2025. Additionally, Oxford Economics predicts the industry-wide adoption of IoT technology could increase global gross domestic product (GDP) by as much as 0.8 percent, or over $800 billion during the next decade. IoT is set to make its mark on a global scale and transform the way companies operate—and the energy sector is no exception.
How will IoT continue to drive innovation in the energy sector?
Over the next decade, IoT is expected to be the single most powerful driving force in the evolution of the oil and gas sector.
Today, leading companies are using sensor-driven technology to reduce non-productive time in field operations and improve the lifetime value of machinery and other assets. Even the smallest oil companies are evolving and optimizing their use of sensor-driven technology—and they should, if they plan to remain profitable in the age of IoT.
Although sensors might sound like a modern innovation, they aren’t new to the oil and gas industry. In fact, the use of sensors traces back to the early 1920s when borehole sensors were first deployed. Later, in the 1970s, magnetic steering tools emerged, bringing dramatic improvements that are still seen in modern directional drilling tools.
Sensor-Driven Solutions & Software Innovation
Aside from borehole drilling, there are countless other sensor-driven solutions that oil and gas companies are employing today. Sensors that measure and detect vibrations, flames, gas leaks—as well as multispectral sensors and cameras—are commonly used along with drones, satellites and other remote sensors to maximize operational efficiency and streamline maintenance activities. Additionally, more advanced sensor platforms are driven by artificial intelligence (AI) to identify drilling spots with little to no manual input, which dramatically reduces operating costs.
Here are other examples of IoT innovation in the energy sector:
Flame and Gas Hazard Detection
The latest generation of flame and gas detection sensors reduce potential exposure to hazardous gases, extreme temperatures and other dangerous environmental conditions that threaten equipment performance and the safety of personnel. A well-designed flame and gas detection program protects facilities and personnel as well as the environment and surrounding communities.
Vibration Sensors
Unusual vibrations in oil field machinery engines can cause machines to age more rapidly and increase the cost of repairing and maintaining them. Although vibration-based leak detection technology is still evolving, it’s becoming a popular and cost-effective solution for identifying pipeline leaks and detecting product theft on installed pipelines that lack fiber optic cables.
Gas Leak Detection Cameras
The last decade has unleashed new technologies to detect and measure the leakage of natural gas, including optical and infrared detectors, flame ionization detectors, Method 21 “sniffers” and others. These devices can be fixed, portable or even drone-mounted to monitor potential leakage in remote or harsh areas. Optical gas imaging uses ultra-sensitive infrared cameras to detect small emissions of industrial gases. Now, regulatory agencies are advocating these modern methods over more traditional methods of emissions reduction, which are inefficient and costly.
Multispectral and Hyperspectral Sensors/Cameras
Unlike standard visual sensors—which collect red, green and blue wavelengths of light—multispectral sensors can easily detect wavelengths that fall outside the visible spectrum, like near-infrared radiation (NIR), short-wave infrared radiation (SWIR) and others. When coupled with satellite, drone and other remote platforms, multispectral and hyperspectral sensors can detect new oil reserves, leakages and other safety hazards across large areas at just a fraction of the cost.
Using IoT and Energy Data Analytics to Connect Stakeholders
The companies that are at the forefront of IoT innovation are using the technology beyond its obvious use cases; they’re using IoT to connect various stakeholders and create production networks. For example, the process of extracting oil and moving it could have hundreds (or even thousands) of stakeholders, including:
- Those directly responsible for the extraction in the field
- Those who own the land
- Those making various machinery
- Those making parts for the machinery
- Those servicing the machinery
- Those delivering parts for the machinery
- Those involved in transporting, refining, selling, trading, etc.
The trucks, pipelines and cargo ships that are involved comprise a larger network of workers, clients and companies who are invested in better extraction and production—and IoT is the glue that can bind them together.
Consider this example: If sensors indicate a temperature fault on extraction machinery, those sensors are not only responsible for alerting machines, but also indirect stakeholders. Using artificial intelligence, personnel with related service contracts or similar experience can be notified and take action. From there, response times and actions can be collected and added to the knowledge base to prevent similar issues in the future.
Data related to specific machinery and processes can even be aggregated across companies to improve the accuracy of performance indicators in different environments. This kind of collaborative, predictive analytics and AI-driven response is happening today in other industries—like telecommunications, healthcare and industrial equipment manufacturing—and there’s no sign of it slowing down.
The Road Ahead for IoT
Over the last 15 years, IoT has propelled the oil and gas sector into a new era of innovation and growth—but here’s the bottom line: While companies are using sensors to collect data, they still struggle to produce actionable insights through unified energy data analytics. But with the right software, coupled with comprehensive sensor data, companies can unlock both historical and real-time performance insights—like Overall Equipment Effectiveness (OEE), Mean Time Between Failures (MTBF) and Energy Efficiency (EE)—to drive decision-making. So where is the oil and gas sector heading? It’s heading toward the development of automated platforms that are driven by cost-effective, accurate and secure technologies.
By boosting their energy data analytics capabilities, companies can improve the monitoring of oil and gas extraction, pipelines, wellheads and refineries. For example, oil and gas extraction are typically done in remote and harsh environments, like the middle of the ocean or a desert. This makes basic activities—like monitoring temperature, pressure, flow rates, and levels—extremely difficult. Sensors can indeed collect this data without human intervention; however, the real challenge is transmitting that data to the appropriate systems in a scalable way, given the limitations of cellular and wireless networks. But with the right analytics and real-time information, adjustments can often be made before failures occur. The same can be said for collecting data from cargo ships or measuring crude composition for better procurement planning.
Advanced energy data analytics also enable companies to maintain regulatory and legal compliance from an environmental, health and safety standpoint. For instance, wells produce hexane and other VOX gases that are subject to leakage, posing danger to individuals and the environment. Some fields, typically in mountainous areas, even have trace amounts of radioactive materials (e.g. radon gas and other decay products from natural uranium deposits below the surface) that can cause detriment if left undetected.
But the future of IoT in the energy sector goes far beyond identifying and fixing a failing part. It’s about harnessing the power of data and automation to transform the way we produce energy and steer us toward more innovative thinking and problem-solving approaches. Instead of asking, “How do we react more quickly to system or machinery failures?” the questions may be “How do we prevent future failures?” or “When will a machine become too unreliable to keep maintaining?”
As the use cases for IoT and energy data analytics continue to evolve, one thing is certain: Those who adopt IoT too late in the game will be at a competitive disadvantage. More forward-thinking players in the energy arena will reap financial benefits by learning how to use real-time data to maximize operational efficiency and make better, faster decisions.
New Questions, New Opportunities
From connected drills and intelligent gas pumps to sophisticated thermostats, IoT is a launchpad for new opportunities and more efficient operations. To fully embrace IoT and modern technologies, companies need to improve hardware integration and reimagine the way software is architected and employed. This means re-architecting infrastructure, underlying code and software development practices to innovate more rapidly.
When it comes to energy sector transformation, it’s no doubt that IoT and energy data analytics are key players—but what does this mean for your business? Download our white paper, “Energy Sector Transformation with Advanced Analytics and IoT,” to learn how energy companies are adopting modern technologies to solve their most pressing challenges—and how you can, too.
