CC BY
9Impact Factor: SJIF 2019 - 5.11
2020 - 5.497
2021 - 5.81
ТЕХНИЧЕСКИЕ НАУКИ
328
USiNG INTELLiGENT SYSTEMS METHODS iN THE OiL INDUSTRY
NURMAMMADOV RAFAiL
Azerbaijan State Oil and Industry University
Summary
Against the background of increasing interest in intelligent systems in the oil industry, the subject talks about the lack of "legalized" formulation of the concept of "Smart energy systems", "Smart well", "Smartfield" and others, and vulgarization of the considered terms to a certain extent. "Intelligent" is sometimes called energy systems, simply automation, alarm, dispatch system, computer network, etc. Equipped with Sixty years ago, the American scientist McKay (1951) introduced the concept of self-organizing or self-managing machines (at that time there was no concept of intelligent systems), which are classified according to how they perform the following general functions:
> receiving, classifying, memorizing and transmitting information;
> response to changes in the environment, including providing information about the condition of the machine itself;
> deductive reasoning and learning based on hypotheses or postulates.
In this case, learning consists of observing and controlling one's own purposeful behavior.
Of course, all these functions are characteristic of modern intelligent systems, including the oil and gas industry. The article discusses intellectual systems used in oil wells.
Key words: oil, system, intelligence, industry
Often, the definition of intelligent systems is considered through a number of functional features, for example, monitoring, dispatching, etc.
A more meaningful definition is to consider intelligence as a combination of the ability to predict the environment and the ability to choose an appropriate response from among different alternatives, taking into account the outcome of the prediction and the goal, i.e. to define intelligence in terms of the behavior of a goal-seeking (living or artificial) system and to measure its degree of intelligence by the adequacy of its decisions. Decision-making without purpose is meaningless, and the term "intelligence" has no meaning. It is this approach that makes it possible to design intelligent systems [1].
Generality of approaches to building systems in the energy and oil-gas industry, their automation and application in terms of Intellectual Technologies, including planning and processing of measurement results, building mathematical models, drawing up energy balances, etc. Enables the integration of the best solutions to achieve the most effective solutions in both the energy sector and the oil and gas industry. Examples of such integrated systems already exist: for example, commercial and technical accounting systems of all types of fuel-energy resources (electricity, heat, gas, fuel oil, etc.) [4].
Artificial intelligence neural network technologies are increasingly used in the development of intelligent sensors and information processing systems in oil and gas and other strategically important industries. They make it possible to create neural network models of automation objects and applied neural systems, which greatly facilitate the control of the technical condition of oil and gas industry facilities, perform their structural and parametric identification using neural network training algorithms [5].
The efficiency of industrial systems in the oil and gas industry created on the basis of artificial neural networks is determined by:
> the obtained degree of adequacy of neural network models to automation objects, it mainly depends on the correct selection of the structural and functional organization (specification) of the used neural networks;
Impact Factor: SJIF 2019 - 5.11 ТСХШЩЖМ НАУКИ
2020 - 5.497
2021 - 5.81
> the quality of information pre-processing performed by neural networks of intelligent sensors and data analyzers;
> the presence of analyzers of neural network systems for data processing of functions necessary for intelligent analysis of real-time data [3].
What effect is expected from the use of technology and, for example, how cost-effective is the concept of "smart areas"? This question is answered below:
> This is production optimization. Smart field systems provide the most detailed information about well operations, including information processing systems, operating conditions and reservoir conditions. Based on the detailed analysis of the received data, oil production conditions that are optimally suitable for its full exploitation should be created in each well. Thus, the rate of oil production and production will increase.
> Cost reduction. This is mostly related to the automation of production in the application of the "smart beds" system. The operator on duty should not need to visit the well pads, he should receive all the necessary information directly into the computer in real time. Thus, he will be less exposed to risk and spend more time on the quality of other important production tasks [2].
Another important advantage of this approach is the creation of a collaborative work environment, since people working in any office of the company have access to the same real-time information as personnel in the field. This improves the work of the entire team and expands our ability to optimize production processes.
The next important point is the need to urgently create an effective scientific assurance system with the application of production technologies, especially artificial intelligence methods [4].
Today, the share of science-intensive products and industrial expenditures in GDP are the main indicators of the knowledge-based economy. In most advanced economies, domestic spending on research and development is about 3% of total GDP
Thus, in Sweden - 3.8%, in Finland - 3.5%, in Japan - 3.44%, in Switzerland - 2.9%, in the USA - 2.84%, in Germany - 2.54%, in Russia - 1 ,2%, in New Zealand - 1.16%, in South Africa -0.92%, Belarus - 0.7%. At the same time, US spending is 35% of world spending - $390 billion.
Undoubtedly, the use of information technologies, including artificial intelligence methods, will allow more complete and efficient automation of production and transportation processes, and most importantly, it will allow to "train" industrial equipment to receive and process against each other, and sometimes [ 5].
Prospects for the development of the infrastructure of the oil and gas industry include, first of all, the automation of the full range of work related to the development, production, transportation and processing of oil and natural gas based on intelligent systems, because the task of reducing the work related to the development, production, transportation and processing of oil and natural gas is set. This task includes design and technological control of exploratory drilling, calculation of drilling parameters, management of geological and geophysical data, etc. Automation of basic processes helps in areas such as [4].
When developing offshore and deep water fields, oil and gas companies of Azerbaijan should widely use the advanced achievements of scientific institutions and universities, including innovative technologies for developing oil and gas fields in real time.
The interest in smart technologies in the oil and gas industry is not just about fashion trends, but about real problems facing mining companies today. Few fields in the world can boast of flowing wells, where the task of increasing efficiency is not yet so urgent [5].
Smart Field ("smart field", SF) is a software and hardware complex that allows you to manage an oil reservoir to increase hydrocarbon production. The system is based on the idea of prudent use of savings, maximum extension of its service life. That is, not predatory exploitation of the earth's surface, but a reasonable increase in production volumes. Another important task of SF is to increase the energy efficiency of equipment and technological processes. Thus, the implementation of this concept helps companies reduce energy costs and leads to an overall reduction of carbon dioxide emissions into the atmosphere [4].
ОФ "Международный научно-исследовательский центр "Endless Light in Science"
Impact Factor: SJIF 2019 - 5.11 TE^HHK^ ^YKH
2020 - 5.497
2021 - 5.81
The SF system consists of a number of components responsible for different functions. The solution offered by Schneider Electric includes end-to-end automation, technical tools for data collection and analysis, as well as solutions for implementing activities to increase the efficiency of the oil and gas company at various levels. Thus, a component of the smart bed system is the Foxboro NetOil&Gas solution, which allows you to measure the flow rate of the well directly at the wellhead and determine the flow rate of water, oil and gas [2].
SF can control the individual well, or rather, the operating modes of the pumps. It also provides oil and gas treatment systems, including booster pump stations, flare systems, etc. Manages. SF operates formation pressure maintenance systems including intake stations, water metering units, injection wells and supervises oil pumping stations and tank farms.
The system involves the use of various intelligent and multi-parameter sensors. "Smart" technologies provide remote access to all field equipment, allowing you to diagnose its condition and configure it if necessary. An important segment of SF is the organization of smart energy supply, which involves flexible energy distribution systems, detailed accounting and the ability to control energy consumption [4].
The concept also envisages the application of physical (video surveillance, access control, fire extinguishing) and information security systems. The highest level of SF is the automated management of the entire production process on the MES Production Execution System, which allows linking the actual production with the rest of the processes taking place in the enterprise.
The main goals of SF are to increase oil and gas production, extend the life of the hydrocarbon reservoir, and optimize production costs. The use of intelligent technologies in the field allows to take a step forward compared to the use of traditional automation systems.
The "smart" system provides the company's managers with all the necessary information in real time and allows to react adequately and almost immediately to changes in parameters, to flexibly adapt to changing conditions and to achieve maximum production with the help of adjustments [1].
Important functions of SF are short-term forecasting and situation modeling. The "Smart field" system is built strictly according to the real geological-geographical model of the deposit, in addition, it collects information about its current condition. This allows you to play different scenarios and draw conclusions with high accuracy about how the warehouse will behave not only in the present, but also in the future during certain human impacts.
As a rule, it is important for the management of oil and gas companies to understand what effects the application of "smart field" will have on the business [3].
In the current economic conditions and production decline, the application of smart field technologies becomes a critical condition for maintaining the competitiveness of oil companies. Moreover, the use of intelligent technologies in oil and gas production can raise the industry to a new level [3].
Conclusion
We came to the conclusion from the article that today there are many innovations in oil production. These innovations are used enough.
During the extraction of oil from oil wells, there are many intelligence systems, these systems are very useful in oil extraction.
Today, many domestic oil and gas companies, realizing the advantages of intelligent technologies, are interested in the possibilities of using them. Until now, individual components are implemented more often, but there will be a gradual transition to complex projects, because it is precisely such solutions that can give the maximum effect.
33 О
Impact Factor: SJIF 2019 - 5.11
2020 - 5.497
2021 - 5.81
REFERENCE LiST
ТЕХНИЧЕСКИЕ НАУКИ
331
1. Aliyev H.A. "Azerbaijani oil in world politics" Baku. 1997
2. Ismayilov H., Aliyev T. "Teaching methodical recommendation". Baku. DNA 1998.
3. Mammadova G.G. Prediction of condensate loss by stages by controlling the technological mode of wells. Materials of ADNA 19 PhD students and young researchers of the scientific and practical conference "Azerbaijan-2020: development prospects of the oil and gas industry" dedicated to the 90th anniversary of the birth of the National leader of the Azerbaijani people H. Aliyev. 2013, p. 115-116
4. Mammadova G.G. Justification of the determination of the technological regime of the wells. XIX Republican Scientific Conference of doctoral students and young researchers. Azerbaijan State University of Economics, April 7, 2015, p. 87-89
5. Karimova A.G., Mammadova G.G. A new method of research of gaslift wells. "Khazarneftgazyatag-2014" Scientific-practical conference, December 24-25, 2014, Collection of articles. P. 63-69
