Digital transformation in oil and gas industry
In the extraction industry, there is an intensive introduction of digital technologies at all stages of production – from geological exploration to the sale of final products. This is most noticeable in the oil and gas industry, where digitalization is regarded as the main way to increase the competitiveness and profitability of a business.
Commercial oil production from boreholes began in the middle of the 19th century. To date, all readily available onshore oil and associated natural gas deposits have been developed. Since the end of the 20th century, technologies for their extraction have been developed in difficult conditions: shale oil production, Arctic, offshore and deep-water drilling. For a long time, the development of such deposits was carried out only in the presence of large proven reserves. For medium and small volumes, it was unprofitable due to high costs, but in recent years, the attitude towards them has been revised. New technologies have appeared that make it possible to start their effective development.
Digital transformation is now taking place in all major oil and gas companies. The economic effects associated with it are mainly due to the reduction in costs and the possibility of a more complete development of deposits.
Digital Transformation in Oil and Gas Examples
Today, leading oil and gas companies use high resolution tomography to analyze rock samples recovered from wells. Detailed 3D maps of seismological exploration work are built using them at the stage of exploratory drilling. Then, using the obtained computer models, the geological structure of the deposits is assessed and the optimal scheme for their further development is selected.
Nearly all technological processes can be modeled and the most appropriate scenario can be selected in advance, rather than acting on the spot by trial and error. A few hours of simulation replaces months of testing, while providing an even more accurate representation of the formation properties. As a result, years of labor are saved, and oil recovery is increased by one and a half to two times.
A large role in modeling is traditionally played by hydrodynamic calculations, which are used to assess the performance of fields, calculate the required number of wells and their parameters, select the optimal drilling methods, and estimate the planned volumes and rates of production. It is the initial calculations that determine investment risks, therefore, to improve their accuracy, companies try to use the best practices of data collection and analysis.
Oil and gas companies are actively introducing Big Data technologies in field development.
At the end of 2018, Growth Horizons introduced the world’s first RFID tag for extreme oil and gas production. RFID-tag “Hermes-1” with protection class IP69K can be used to mark downhole equipment. It simplifies logistics operations, virtually eliminating random errors and deliberate falsification of data. The miniature 12mm x 3mm tag speeds up inspection and lifecycle monitoring of drilling equipment components, allowing you to accurately track their actual operating life.
Prevention of common drilling problems is also achieved through the introduction of continuous directional survey. This is a constant tracking of the zenith and azimuth inclination of the well for more accurate control in space.
Continuous assessment methods reduce the development time of deposits by reducing the frequency of static measurements (up to a complete rejection of them). The operator always receives data in real time, rather than doing a retrospective analysis of individual control measurements.
During the development of a field, it is important to understand how its properties change over time, and to make a forecast of future use based on this data. Some areas are depleted faster than others, and after a while additional wells or modifications to existing ones may be required. Now, 4D seismic is used for this – three-dimensional seismic data superimposed on a timeline (the fourth dimension is time). They are used to assess the refined boundaries of oil occurrence, various geomechanical effects, movement of oil and gas between natural reservoirs and other dynamic factors.
In other words, a 3D seismic survey is periodically performed, and the new results are compared with the previous ones. Based on this difference, they see how the oil-water contact zone shifts, how the water cut level of the reservoir changes in different areas, and adjust the production methodology and forecasts.
Another important area of optimization in oil and gas production is telemetry, which allows continuous remote monitoring. For example, most of the Russian wells are located in underdeveloped regions with a cold climate.
Already, costs are being reduced by digitally controlled automated drilling and continuous wear assessment of highly loaded assemblies. This is another area of Big Data that helps you plan repairs and staff rotation more efficiently, reducing downtime. Reducing the number of specialists directly involved in servicing the mining complex will significantly reduce costs. Most operations today can be performed remotely.
Digital Transformation in Oil and Gas Trends
Digital transformation in the oil and gas industry in the past couple of years has become almost the main topic of discussion by specialized media, industry specialists, and a reason for holding large-scale forums.
The basic principle of the new industry – the so-called Industry 4.0. – is the transition from fragmentary automation of individual stages or industries to fully automated digital production controlled by intelligent systems in real time.
According to Vygon Consulting experts, cited in the study “Digital Oil Production: Tuning for the Industry”, BP and Shell were pioneers in this area, introducing new digital technologies since the early 2000s – that is, even before the official start of the digital reboot of the world economy. Today, digitalization has become part of the development strategies of all the largest oil and gas corporations.
For example, BP, in its Technology Outlook published in 2018, predicts that, due to technological development, the increase in recoverable oil reserves in the world will exceed 1 trillion barrels by 2050, with an average decrease in production costs by 30%. Digitization should provide about a third of this cost reduction.
The focus for investments has already been determined: BP believes that artificial intelligence and cognitive computing technologies will have the maximum impact on reducing the cost of production.
Machine learning technologies open up new opportunities for the oil and gas industry. Oil and gas companies are starting to pay particular attention to working with big data. Companies collect huge amounts of data every day and are actively working on how to get the most out of it and turn it into something useful. Vygon Consulting calculated that an average mine equipped with the Internet of Things generates about 15 petabytes (15 * 1015 bytes) of information per year, which, of course, is impossible to work with without using tools and methods for processing big data.
Software AG experts made a forecast of the main directions of digitalization in the oil and gas industry for the next year and came to the conclusion that in conditions of fierce competition and unstable energy prices, the main task of oil companies will be to obtain analytics on production and economic processes in real time.
The deterioration in the quality of the resource base today is perhaps the main challenge facing the oil industry. The lack of new large projects for the production of light oil forces the majority of the industry players to maximize the period of profitable exploitation of mature fields. The digital recipe for solving this problem is the so-called smart, or intelligent, fields.
The principle of operation of smart fields is in the combination of measurement, control and management technologies in real time, the formation of a continuous information flow that allows you to quickly respond to the situation and make optimal decisions. The key element of the system is smart wells, which continuously collect information about the situation in the bottomhole, analyze it and, based on the data obtained, adjust the operating modes. The first Smart Fields program was launched by Shell back in 2004. With the development of digital technologies, the idea of an intelligent field has become even more relevant. Such projects combine the use of Big Data, the Internet of Things, and digital twins.
A study by Cambridge Energy Research Associates (CERA) suggests that the oil recovery factor in smart fields is 2-10% higher than in conventional fields. At the same time, according to expert estimates, mining within the framework of an intelligent field reduces operating costs by 10%, and capital costs by up to 50%.
The use of Industry 4.0 technologies in the upstream, of course, is not limited to exclusively smart fields. For example, Chevron is using artificial intelligence in California to identify new drilling sites by analyzing historical data from wells in the region. This has already enabled the company to increase production by 30%. Equinor (formerly Statoil) developed a continuous reservoir monitoring system for the Johan Sverdrup field in the North Sea and now automatically monitors drilling from the platform using high-speed drill pipe telemetry and a virtual subsea flow measurement and control system. The result is a significant increase in oil recovery compared with the average indicators of other fields.
In general, the Norwegians are one of the leaders in the automation of offshore production.
At the Osgard field in the Norwegian Sea, Equinor plans to use the Eelume robot snake to inspect production equipment and pipelines, thereby reducing subsea inspection costs. Two of these underwater drones will live and recharge in a special docking station at the bottom.
Oilmen, including Russian ones, have been using ground (or rather, above ground) drones for a long time and successfully. One of the main drone professions is monitoring pipeline systems. To do this, drones are equipped with special equipment for shooting and diagnostics. According to experts, in some cases the use of unmanned aerial vehicles can reduce the cost of operating pipelines by up to 85%.
In general, there are already a lot of fields of application of digital technologies in upstream, and this list is constantly growing. Wood Mackenzie estimates the impact of digitalization on the world’s 10 largest production projects at $ 20 billion, or 40% of the projects’ total net present value (NPV). At the same time, the potential for the development of the digital direction is huge.
In the downstream, the flywheel of complex digitalization was launched earlier than in the upstream. The catalyst for this process was the transition in the 1980s from pneumatic systems for monitoring and control of technological processes of refineries, first to analog, and later to digital.
According to the refiners themselves, interviewed in “The Intelligent Refinery” by Accenture, the use of advanced process control systems and analytical solutions are most influencing the growth of profitability in refining today. It is in these systems that processing enterprises plan to invest the largest part of the funds allocated for digital technologies in the near future.
The main tasks that both domestic and Western oil companies solve during digitalization are maximizing productivity through uninterrupted operation, increasing the level of industrial and information security and, of course, reducing costs.
The answer to all these challenges was the concept of a digital factory – production, where the state of each installation, each piece of equipment is continuously monitored in real time, and management decisions are made on the basis of information analyzed on the fly. The digital information environment that is being created in modern enterprises using the industrial Internet of Things (IIoT) technology already makes it possible to actively develop this concept.
Ron Beck, AspenTech’s director of industry marketing, points to another important digitalisation trend – prescriptive analytics as an effective alternative to the traditional calendar approach to industrial asset maintenance. “Predictive analytics technologies examine production data streams and, based on them, identify complex signatures and patterns of upcoming events in advance of their occurrence,” says Beck. The operator is informed not only that the compressor may fail, but also that this problem is associated with a liquid leak into the gas pipelines, indicating a certain concentration or, for example, with a small change in pressure recorded by the system. A prescriptive approach to maintenance not only identifies an impending problem, but also recommends measures to prevent it.” However, according to the AspenTech manager, this methodology is still in its infancy.
“Refiners are currently taking advantage of only a small fraction of the benefits of digital technology,” said Tracy Countryman, managing director of Global Resources Industry X.0 at Accenture. “The next step is the combination and large-scale implementation of various technologies, which will allow us to completely rethink business processes and launch transformational changes at the enterprise level.”
Obviously, transformational changes are waiting for not only processing, because smart fields and factories are just today’s upper level of industrial digitalization. Tomorrow is the bringing together of all elements of the value chain on a common platform. Ron Beck of AspenTech, in particular, says about this: “We expect the development of a new trend, which we call ‘networks of industry competition’. Connecting the elements of the value chain will give a competitive advantage to companies that exploit the opportunities for partnerships and business alliances across the entire value chain. Like Amazon, which organized the supply chain for consumer goods, oil and gas businesses will respond appropriately to market and manufacturing opportunities and pricing challenges.”
To create such ecosystems, advanced players in the oil and gas market are already actively preparing sites for production, refining, and the sales segment, where intelligent systems for monitoring and comprehensive analysis of the array of data coming from every element of the network – right down to every gas station are also being created. Obviously, this entails digitalization and all other areas of the oil companies’ activities.
Together with the unification of production processes, people will also be connected to the network. This is what the Connected Worker concept is all about, which tracks the location and movement of workers to keep them safe and efficient. Thanks to wearable devices, repair and production personnel can instantly contact experts or access an electronic database to get accurate answers to questions that arise during the work.
New communication tools such as virtual and augmented reality (AR/VR) simulations enable enterprise-wide collaboration. AR/VR technologies are also actively used in the training of employees, whose qualifications are increasingly demanding.
VR learning tools are already being used in petrochemical, oil and gas, mining and energy companies. A number of the largest industrial companies are now testing augmented reality platforms and assisting reality solutions.