Scientists regularly scare oil-producing countries with statements about the era of oil soon passing and readily available hydrocarbons being almost exhausted. At the end of 2017, known world resources of hydrocarbons amounted to 1.665 trillion barrels, according to OPEC reports. Experts claim that the current global consumption rate is 90.5 million barrels per day and that this should continue for another 50 years. Moreover, there is growing competition from renewable energy sources.
The digitalization of the oil&gas industry allows us to immediately respond to both of these challenges: to simplify the extraction of hard-to-reach oil and, at the same time, to extend the “lifespan of hydrocarbons” for more than one decade. However, oil&gas and production companies are generally conservative. Indeed, many companies are already implementing projects in the field of predictive repairs, while the use of AI to optimize production is only beginning to be tested.
The term “smart oil deposit” means a set of software and hardware used to manage an oil reservoir and boost hydrocarbon production. The system is based on the idea of a caring attitude to the deposit and maximum extension of its operating life, primarily by increasing extraction volumes and the efficiency of the technological process. Thus, the introduction of this concept is helping companies to reduce energy production costs. Deployment of smart technologies in the oil&gas industry is also being driven by low prices, competition from other types of energy resources and government policies. For example, in Norway, the law requires companies to reduce carbon dioxide emissions by 50% in thirty years.
There are several mandatory stages in the development of smart oil deposits. The first involves the creation of well models at the development stage and the recording of various measurements during production. In the second stage, these are connected up to form a single network – the Internet of Things – while various types of leaks are simulated and emergency response training is provided. As a result, “smart” technologies provide remote access to all oilfield equipment and enable diagnosis of its condition. Another feature of the “smart oil deposit” is intelligent power supply, which involves flexible power distribution systems, detailed metering and the ability to control power consumption. Thus, integrated modelling, integrated planning, minimization of the human factor, etc. become distinctive features of the “smart oil deposit”.
Leading consultancies reckon that the overall impact of smart oil deposit implementation is a 7–10% reduction in operating costs by optimizing work and reducing underproduction: according to Gartner, application of the “smart oil deposit” concept could help oil companies to cut costs by 5% and enhance production volume by 2%; CERA believes that the incremental oil & gas rate in a smart deposit is 1–6%, while oil-well downtime is reduced by 1–4% with a 25% saving on labour. Experts suggest that it will be possible to increase global oil production by 30-50% due to the transition to smart next-generation technologies.
One of the drivers for the digitalization of the oil industry is the development of hard-to-reach fields, primarily offshore. In particular, ExxonMobil has launched comprehensive real-time drilling support based on logging data and drilling rig sensors. This is based on three activities: 1) data collection from hundreds of sensors at the bottom of the well and on the drilling rig; 2) transfer of the data received to a remote drilling operations support centre; 3) updating of the digital model of the well in real time with feedback to the drilling rig. As a result, the company has achieved a 50% increase in well productivity over the past five years with a $40 reduction in the time needed to build new wells, while also reducing NPT by 10%. In November 2018, ExxonMobil also introduced a new SMART by GEP® platform, consisting of a single, unified cloud solution. The system has many features allowing users to perform key actions in one place, including managing supplier profiles or monitoring the status of key contractor activities.
In its turn, Shell is actively introducing unmanned technologies in hydrocarbon production on its platforms in the North Sea, as well as automatic adjustment of production volumes depending on external factors. Data is collected using receivers, sensors, drones and satellites before being transmitted through an optical fibre to a single control centre. Monitoring and analysis of all indicators occur automatically. As a result, there are no people in the hydrocarbon production area, thereby drastically reducing risks and operating expenses. According to the company’s own estimates, it has been able to increase production by 3,000 barrels per day. Shell explains that it is one of the first companies in the world to introduce smart oil deposit technology. As a result, each field is monitored by thousands of sensors built into the equipment. For example, valves and pumps send data on temperature, pressure and other oilfield parameters to onshore control centres. Teams of engineers monitor production in real time and all decisions are made on an on-going basis. Previously this took at least a week.
In 2019, Gazprom Neft, one of the largest Russian oil companies, together with Zyfra Group, started to implement “smart” solutions at some of its fields. The company expects to halve Gazprom Neft’s major project implementation times and thereby optimize the timing of first oil production from those fields. With plans to implement about 500 initiatives in the sphere of digitalization and digital transformation, Gazprom Neft has set up a cluster of technology centres acting as operators of developments in the field of applied IT solutions. To stimulate the creation of new IT solutions, the company is also developing its own digital production management platform. In particular, the project creates digital twins of all production plants for integration within a single management system.
Thus, the introduction of digital solutions in the oil&gas industry has a proven positive impact, yet at the same time the new technology has not been applied on a massive scale. The process is noticeable only in individual product segments as there are number of objective prerequisites for its implementation.
Obstacles to Digitalization
The first obstacle is organizational readiness: Is there any real interest in digitalization? The oil&gas industry is a capital-intensive, technologically well-established process, and not everyone sees prospects in the intensification of production through digitalization. The second obstacle is technological readiness: Do the current IT landscape and, above all, data, allow the application of digital capabilities? For example, in order to make predictive analytics looking three years ahead, AI must be trained on 10 years of historical data. If such work has not been carried out or the quality of the data is inadequate, one must first start with the data collection. The third obstacle is the value provided by the digital initiative to the company. In some technological areas, the effectiveness of introducing digital solutions is very low, offering gains of approximately 1-2%. Thus, companies see no point in the additional efforts and significant funds required to achieve this improvement. The fourth obstacle is the difficulty of implementation. A company may have prepared itself, collected the data and determined the benefits, but for various reasons it can be difficult or even impossible to implement the project – for example, if it requires drastic changes in all business processes. In the case of introducing the Internet of Things in the oil industry, there is also an additional risk associated with cybersecurity issues.
The introduction of modern technologies in oil production, in particular, AI and the Internet of Things, reduces the cost of resource extraction and helps to boost competitiveness against other energy sources. In the long run, it will help extend the lifespan of hydrocarbon resources by at least 50% and the technologies developed will also find application in other industries. However, as in the industrial sphere, this revolution will not happen overnight. It requires time and cumulative impact before the new technological stage becomes reality.
(Dmitry Lukovkin is AI Business Director at ZYFRA. ZYFRA Group was founded in November 2017 and currently operates in Finland, China, Russia, Bulgaria, and India, and its platform connected over 8,000 CNC machines across the countries. By the end of 2018 more than 270 production facilities are equipped with its products.)