Over the past 200 years, since the days of the Industrial Revolution, we have experienced several waves of innovation, which have had a profound effect on our everyday lives. Today, across the oil and gas industry, we are on the cusp of a new transformative era, with the potential to radically change the way we do business and interact not just with the physical world, but also with the world of analytics.
In the latter part of the 18th and early part of the 19th centuries, the Industrial Revolution represented the first wave of advancement, with innovation and technology primarily applied to agriculture, manufacturing, and energy production. It delivered a period of unprecedented growth and changed people’s lives significantly.
The second wave took place at the end of the 20th century, at a much faster rate—over a period of approximately 50 years—and was characterized by the emergence of the Internet. With fewer than 300 computers connected in 1981, that earliest manifestation is unrecognizable to today’s, where connectivity is almost ubiquitous and the Internet is responsible for providing billions of people with instant access to massive amounts of information, changing the way we shop, socialize, and execute much of our business.
Today, we are experiencing a third wave, the emergence of the “industrial Internet,” a place in which the physical and analytical worlds collide. The industrial world is being digitized and reshaped by “big data,” opening up new and unprecedented levels of productivity. Data coupled with expertise-driven knowledge are important to a company’s ability to achieve improved outcomes.
Essentially a convergence of machines and intelligent data, the industrial Internet is enabled by advanced computing, data analytics, low-cost sensing, and new levels of connectivity, all permitted by the Internet. It is a deep meshing of the digital world with the world of equipment and machines; one that, by 2020, will see an estimated 50 billion devices connected and communicating, not only with their owners, but also with each other. This revolution holds the potential to bring about a profound and significant transformation of global industry and, in turn, changes to many aspects of daily life, including the way we work.
A large proportion of the devices connected to the Internet now are smartphones, tablets, and computers. In the future, almost all technically active devices will be connected to the Internet, limited not just to a range of consumer devices such as TVs or refrigerators, but also including a broad range of industrial equipment, such as gas turbines, wind turbines, and the full range of subsea systems.
The much discussed “digital oil field,” “e-field,” or “i-field” will be represented by applications in the wider industrial Internet revolution, delivering benefits from an individual application to fleet level, but also more widely at the enterprise level. Initially, it will be possible to monitor the performance and efficiency of individual assets, but in the future, we expect to see analytics and subsequent learning being applied across an entire fleet of assets, each optimizing its own performance relative to others, with all assets aligned to goals set at the field or system level.
These goals may be associated with key value drivers such as improved safety, enhanced recovery, reliability, or efficiency, but in all likelihood, they will be a mix that will ultimately improve return on investment. More quality data, combined with smart analytics and the broad experience of the original equipment manufacturer, can deliver large immediate gains, but also perhaps less obvious small incremental gains that, when applied on a greater scale, will provide significant value.
There are a number of areas where the industrial Internet could affect offshore, subsea, and wider business operations by turning data into actionable information.
Health, Safety, and Environment
Improved safety and reduced risk are critical goals that are subject to continuous review in the quest for advancement. The industrial Internet can provide improvements in a number of ways, primarily through the ability of high-speed communications and smart analytics, coupled with more sensors, to give an improved view of real-time operations. This means that those responsible for operating subsea equipment will have to have a higher level of system awareness and make important safety-critical decisions earlier. Data may relate to normal operating parameters such as pressure, temperature, and flow rate, but can also include data streams from sensors designed to provide insight into areas such as wellhead fatigue damage or flowline wall-thickness reduction.
The Naxys A10 is a prime example of a technology that facilitates such improvements. The independent subsea-monitoring system uses acoustic and electric leak-detection technology, coupled with advanced monitoring algorithms to identify the possibility of both liquid and gas leaks in subsea equipment before a failure. Early detection can allow for enhanced monitoring, based on improved knowledge.
Once you have a benchmark view of a system and have built a legacy database, it then becomes possible, based on both the data and knowledge of the original design, to infer how the condition of a system might change over time, improving the ability to reduce the probability of failure, while also mitigating risk.
Meanwhile, if the data relating to operations, maintenance, and intervention can be made available faster and to a much broader audience, it could result in the ability to deliver technical expertise and operational support globally, empowering teams at the well or work site, and thereby improving the rigor and experience applied to important decisions and interventions in a timely fashion.
Maximizing Production and Minimizing Downtime
Production efficiency and the availability of subsea and offshore equipment often attracts the attention of a number of varied stakeholders, from the operating company to licensing authorities, who all benefit from their optimization. System reliability directly affects the balance sheet, while continuous monitoring of system status, coupled with analytical performance modeling, provides the ability to differentiate between failure modes, clearly identifying and making a distinction between critical and noncritical failures.
A simple example could be our understanding of the difference between a sensor failure and a more critical equipment failure, while more complex models could relate to flowing and hydrate-formation conditions, and chemical injection or hydrate-management procedures.
Capital Efficiency
Previously, we have detailed how we can improve asset integrity; reduce risk to personnel, equipment, and the environment; improve reliability and availability; and reduce potential operating expenses and the amount of required maintenance.
The industrial Internet also allows the efficient sharing of best demonstrated practice and experience, meaning that local teams need no longer manage planned maintenance in isolation. Instead, they can learn from the best in the business, minimizing cost and employing the correct experience to ensure overruns on maintenance or the need for intervention are reduced. Both today and in future this capability for leveraging input from the most experienced people has been shown to be particularly important, especially when considering current constraints within the labor market.
Lessons learned from one project can be transferred to another, with teams liberating capital for other opportunities. The industrial Internet can deliver more predictable project execution, thereby reducing capital and operating expenditures and improving production efficiency.
Foundations of Knowledge
A key characteristic of the industrial Internet is the analysis of large volumes of data with regard to communication, asset performance, and business operations. This brings with it the need for a new generation of cross-discipline talent, an evolution that is likely to see our future workforces trained in traditional engineering disciplines, such as mechanical and electrical, while also being equipped with new digital engineering expertise.
Roles are expected to range from data scientists, equipped to create analytics platforms and algorithms, to software and cybersecurity specialists, employed to ensure that such large data sets are managed securely. In order to leverage the full potential of predictive analytics, it is not simply enough to produce increasing quantities of ever more comprehensive data. We also need to ensure that the people are in place to understand how to use these data including, for example, which conclusions can be drawn and how to connect cause and effect. The strategic insights gleaned from such analysis will be key to operational success.
Developing and future roles are expected to include:
- Next-generation engineers—who can handle a variety of cross-functional roles that blend traditional engineering disciplines such as mechanical engineering with information- and computing-science competencies.
- Data scientists—responsible for creating analytics platforms and algorithms; software and cyber-security engineers required for statistics, data engineering, pattern recognition and learning, advanced computing, uncertainty modeling, data management, and visualization.
- User interface experts—who specialize in the industrial design field of human-machine interaction, to effectively blend the hardware and software components.
- Visionary leaders—required to both craft and promote the industrial Internet, its values, and the possible applications. These visionaries will need to work hard to sustain investments through the natural peaks and troughs of our industry to build the culture and talent on which the success of the industrial Internet depends.
The oil and gas industry will have to explore a number of avenues with regard to resourcing the industry’s evolution and educating the next generation, including those in the early years of their schooling, sharing with them the benefits and opportunities offered by our sector. Collaboration between organizations and universities will also be important in developing and formalizing the knowledge required to ensure a future pipeline of data talent. Helping schools in the development of curricula with a particular focus on science, technology, engineering, and mathematics (STEM), subjects, and the integration of academic staff into our industry are likely to be among the approaches considered to ensure the needs of our industry do not outpace the educational system.
It is also important to look at providing more specialized training for those wishing to develop their careers in the fields of data management and advanced analytics. These people are likely to have a tendency to be largely self-driven but, as the industrial Internet grows, we foresee the need to invest more in order to help support the future skills and expertise required and to ensure that careers at the forefront of technology within the energy sector remain an attractive prospect.
Conclusion
Huge opportunities exist for the application of advanced technology under the umbrella of the industrial Internet. These technologies can make a real difference in terms of risk management, output, and capital efficiency. This can be achieved through the deployment of hardware, but also through an enhanced ability to make faster, more informed, data-driven decisions. What is clear is that the industrial Internet can deliver significant advantage to the upstream oil and gas industry if we think carefully now about investing in the communication, skills, and technology required to fully realize the opportunity.