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Publication date:
16 December 2019

The problems of automation technological process of drilling oil and gas wells

Date of submission article: 2015-02-25
UDC: 004.5
The article was published in issue no. № 2, 2015 [ pp. 113-118 ]
Abstract:Nowadays the problem of IT development and controlling equipment in the oil and gas recovery industry is very important. In addition to the system-managed automated equipment with its characteristics and compatibility problems, an important component of the automation process is the adequacy of its information support. Accounting for all the comp o-nents of the information system requires systematization approach (automation of drilling is a complex process; compatibility problems; the problem of information uncertainty; intelligent decision support systems; the expert knowledge base; automat-ed brake control; automated speed control; automation and control of fluids while drilling; the problem of energy supply). The work of a drilling platform (automation and information aspects), especially during the development of the great depths, faces many uncertainties. This constantly causes accidents and emergency situations that o ccur with a frequency which is not typical for other industries. In addition to the lack of data, there is also the problem of high speed changes. While moving to the project depth, the character of the rocks, pressure, temperature and other important para meters vary sharply and this re-quires continuous collection of information about them. Under uncertainty and high variability of existing decisions on fu r-ther drilling operations management the use of intelligent systems for decision -making based on fuzzy logic and soft compu-ting is considered to be perspective. A new group of automation facilities can help to overcome many problems typical of the oil and gas industries, to improve the efficiency of oilfield development. This group can include new developments in the field of downhole sensors that will provide measurements of high quality; new developments in the design of drill pipes with cable or fiber optic wiring that will help to provide large amounts of received information to the surface.
Аннотация:В наше время проблема информатизации и контроллинга оборудования в нефте- и газадобывающей отраслях очень актуальна. Важной составляющей процесса автоматизации является достаточность его информационной поддержки, помимо управляемого системой автоматизации оборудования с его характеристиками и проблемами со-вместимости. Работа буровой станции (аспекты информатизации и автоматизации), особенно при освоении больших глубин, сталкивается со множеством неопределенностей, что вызывает аварийные и чрезвычайные ситуации, возникающие с частотой, нехарактерной для других отраслей. Помимо недостаточности данных, существует также проблема высокой скорости их изменения. По мере движения к проектной глубине характер пород, давление, температура и прочие важные параметры резко изменяются и необходим постоянный сбор информации о них. В условиях неопределенности и высокого уровня вариативности существующих решений по дальнейшему ведению буровых операций перспективным является применение интеллектуальных систем принятия решений на основе нечеткой логики и мягких вычислений. Новая группа средств автоматизации может помочь преодолеть множество проблем, характерных для нефте- и газодобывающей отраслей промышленности, повысить эффективность разработки месторождений. К этой группе можно отнести новые разработки в сфере скважинных датчиков, которые позволят обеспечивать высокочастотные замеры; новые разработки в области конструирования бурильных труб с кабельной или опто-волоконной проводкой, при помощи которых станет возможной передача на поверхность больших объемов получаемой информации.
Authors: S.G. Chernyi ( ) - Kerch State Maritime Technological University, Kerch, Russia, Ph.D
Keywords: mathematical expression, programming, fuzzy logic, algorithm, modeling
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Introduction. Automation of technological processes helped to improve the quality and increase profits in various branches of manufacture where it was introduced. At the same time automation of drilling in the oil and gas industry is a nontrivial task. Its solution is accompanied by many negative factors in the terms of automation. Success in this area will allow performing complex tasks effectively, in particular to learn more wells, drilling and development of which is currently technically impossible or unprofitable. Automation will allow not only developing complex fields technically, reducing the period of production preparation, improving the economic feasibility of many projects, but also increasing the efficiency of labour protection and environmental protection significantly.

Specialists know that oil and gas sector lags far behind other industries in terms of automation of drilling process. In this case it is designed to solve several important problems: to improve the technological process of drilling itself, to solve the problem of maintaining the state of the wells with high quality, to minimize emergency cases, to prolong the tool life as much as possible, to optimize the rate of drilling penetration as well as to improve its overall performance. So far the greatest success has been achieved in the mechanization and automation of operations on the drilling platform where in hazardous environment one must complete suspension of pipes, their subsequent connector and other operations with them. However, the process of drilling remains under manual control of the operator. The high degree of variability and uncertainty on the decision-making level are the mainlimiting factors in the way of the drilling process automation [1–3].

Automation of drilling is a complex process. For convenience it is often divided into more manageable modules that can be used individually or in combinations, theoretically forming an intelligent system, able to drill wells in offline mode.

The main modules include:

-      Integration of rig and the well systems;

-      Optimizing the rate of penetration: anomalies detection and corrective measures; monitoring and reducing the impact of shock and vibration loads;

-      Control over the direction of wellbore drilling;

-      Ensuring of the sustainability of the wellbore;

-      Control of the sequence of operations.

Compatibility problems. It is typical that the problem of drilling process automation begins with aspects which are not directly related to conditions or site of production. Technical support of the drilling rig includes many components most of which belongs to different manufacturers. In the context of automation it complicates the problem greatly, as controlled equipment for long periods of time is required to collaborate under the control of a single automation system.

In its turn, a high level of automation involves the implementation of data exchange between all components of the system, and thus full compatibility in terms of methods, protocols, data transmission formats and types of controlling actions, as the foundation for the automation process implementation.

It is important to note that the decisions established in accordance with a specific configuration of equipment or geophysical conditions and not suitable for other units (in other words, localized solutions) are expensive and require human interfering and control. In this regard, development of a new technology of data exchange in described conditions is promising and sought-after. Or it is necessary to consider the possibility of applying solutions already existing in other industries in the oil and gas industry. In any case, the issues of their standardization, certification, compatibility, possibility of work in real time, the possibilities for data backup, protection and transfer for analysis and accumulation of databases on remote objects come to the foreground. Currently, drilling service companies, operators, equipment manufacturers, etc. use different standards for data portability [2–5].

At this point, in the oil and gas industry the Transfer Protocol WITSML is accepted as a standard of communication between systems of management and monitoring wells. But this is only a small part, because there is no a standardized communication Protocol for the rig itself and its equipment. Potentially the extension of the WITSML Protocol and its adaptation for this field of automation can be potentially productive here.

In the end, this hardware/software unified platform will allow realizing a complete and extensive monitoring, control and programmability of entire rig and drilling process, and hence the possibility of independent control.

The problem of informational uncertainty. In addition to the system-managed automation equipment with its characteristics and problems of compatibility, an important component of the automation process is the adequacy of its information support. The work of a drilling platform, especially during the development of the great depths, faces many uncertainties. It constantly causes accidents and emergency situations that occur with a frequency that is not typical for other industries. In addition to the lack of data there is also the problem of high speed changes. While moving to the project depth, the character of the rocks, pressure, temperature and other important parameters vary sharply and requires continuous collection of information about them. Obviously, this aspect is directly connected to the used method as well as data transmission protocol [3, 5, 6].

At this stage, the levels of automation which have found applications in the industry should be separated. So, for a long time on a drilling platform people use decision-making support systems that generate an optimal solution based on received sensor information, as well as a number of alternatives and perform the solution approved by an operator depending on the type of the system. Or the operator himself works on the proposed or alternative plan. A higher level of automation is using a system capable of taking all decisions autonomously and acting autonomously according to them. It should only inform the drilling engineer on the process.

In the first case a human operator performs drilling control analyzing the provided data and taking a final decision on further action. In the second case the automation system must be able to simulate the action of an experienced operator. So, it can select the most efficient and effective solution independently. To do this you must implement a closed autonomous system that operates on the basis of real time information and uses a mathematical model incorporated in the system for this area of drilling and its geological features. It is obvious that the problem can be somewhat simplified in the case of drilling multiple wells in the same geographic area. However, in any case, during operation the model must be corrected according to the data obtained on the surface, drill hole and parameters of the drill. Qualitatively and quantitatively these data are defined by the presence, quantity and characteristics of the sensors in the area of the bit and the drill stem. An equally important parameter is the frequency bandwidth of the data bus transmitting information from borehole sensors to the surface and commands from the surface into the well.

Thus, in general, to automate the process of drilling we need the following information. In terms of hydraulic parameters: data on rheology, value of the drilling pressure and hole cleaning. To control the geological parameters: quality of the barrel, the value of reservoir pressure and overall evaluation of the reservoir. For mechanical part: data of surface measurements, borehole measurements, as well as information on the actual state of the instrument that is the data feedback [6, 7].

In conditions of uncertainty and high variability of existing decisions on further drilling operations management, the use of intelligent systems for decision-making based on fuzzy logic and soft computing is considered to be perspective.

Intelligent Decision Support Systems. Obviously, the necessary amount of information on the state of the drilling process is determined by the requirements of the management system, and vice versa, designing the control system must take into account the limited amount of information supplied. At the same time the number of options available to measure directly is also limited, and therefore, for many important characteristics of the drilling process, it is necessary to estimate indirect available data and the dynamics of their changes. In addition to the search of correlating dependence, the use of fuzzy systems, soft computing and artificial intelligence systems are considered to be promising in this area [2, 8, 9].

The use of auto drillers that had to copy the actions of people in offline mode gave a significant advantage over manual control only in the areas where drilling conditions were well known and have changed smoothly. In the case of a sharp deviation from the expected parameters and conditions, auto drillers started working much worse than people. Ultimately, such systems have not risen higher than the second level of automation and their further evolution was focused on creating the most effective symbiosis of computer and human management. The operator must constantly monitor the progress of drilling and know what operation the machine is currently executing and what it plans to do next. As a result, the role of the operator in the drilling process has rather increased than decreased.

The development of learning algorithms that use accumulated base of knowledge or skills may be an alternative means of development of such systems. Such robust control can be based not only on their own experience of drilling, that is to learn not only from their mistakes, but also to analyze the experience of others that will significantly raise the reliability and efficiency of such systems and reduce the workload of operator supervising the drilling process.

Development of this direction requires solving two problems.

The first is the creation of a robust control system with dynamic qualities that could be improved due to priori evaluative inaccuracies and forecast of uncertainty as well as a posteriori data in the form of information coming from the measurement system. And that is impossible from the point of view of the classical approaches to the implementation of robust systems. Work under conditions of frequent unreliability of both priori and current information, a high probability of erroneous predictions and poorly understood situations causes the need to solve the whole complex of problems in managing dynamic processes under such conditions. A new approach involves the development of mathematical models and criteria that adequately address to the real laws of control object functioning in a specific information field and take into account its specific properties. This approach can be implemented using robust control in conjunction with the theory of fuzzy sets. In particular, using fuzzy control law method formed by means of the theory of robust control based on methods of optimal and modal control.

The second is an implementation of intelligent decision support systems that are capable of generating a plan of action under conditions of high variability and various uncertainties. One of the ways to create such an automatic control system is to use a collected expert knowledge base.

The expert knowledge base. Here it is appropriate to speak not only about the knowledge base of a particular management system with its individual experience, but also about the global knowledge base where information is collected from a variety of drilling sites. The accumulation of such knowledge base or experience is still quite a difficult task. First of all, it is connected to the mentioned above problem of gathering enough information from the rig. Secondly, there is a problem of transferring information from multiple remote objects, usually lacking any developed system of communications, into a single center [1, 2, 4].

The use of satellite communications and the global Internet network in this direction is prospective. In this case, local data collection systems may periodically transmit collected data to a special server when connections with the satellite are strong enough. Further, it is necessary to develop algorithms capable of analyzing the received streams of information, developing solutions and correcting mathematical models, etc., on the basis of positive and negative experience gained on various drilling sites under various conditions.

In addition, this approach can help to conduct statistical studies of work of multiple drilling sites with subsequent optimization of operations.

Automated brake control. In the past the pulley system brake control was used to control the load on the bore bit. The transition from it to disc brakes allows creating electronically driven automated drillers which maintain constant weight on the bore bit or constant rate of penetration. However, as it was mentioned above, the control of such auto drillers in automatic mode is hampered by many uncertainties and imperfections of existing computer control algorithms. As a result, despite the complete controllability, there is also a problem of the implementation of efficient control algorithms.  Such algorithms are able to work with high performance only in well-known drilling conditions, where geological properties of the reservoir, temperature and pressure can be accurately taken into account [9–11].

Automated speed control. Experimental studies show that automated speed control of drilling on basis of the load on the bore bit, its speed and sufficient supply of drilling mud, even in advisory mode can increase the speed of rocks passing an average of 30 %, and with a closed-loop automatic control system of the whole rig up to 50 %. Besides, the system must monitor such parameters as torque, rate of penetration, frequency of bit rotation, as well as the sensitivity of a particular bit which was a special diamond bit [10–14].

However, mentioned above indicators have been achieved in the fields with well-known favorable lithological characteristics. Changing or unexpected formation characteristics can cause disruptions to the bore bit or BHA. Their removal will require continuous adjustments of the weight on a bore bit and rotation speed. Surface measurements may be insufficient to ensure that the engineer detects the change or its cause when it happens. It usually takes a very long time for a drilling engineer to detect and take appropriate corrective measures if such a phenomenon occurs. Taking into account such delays and many factors that affect the measured surface sensors, it is not surprising that the drilling engineer can make a wrong decision that in the best case will change nothing and in the worst case can be harmful.

The problem of the barrel trajectory accuracy. In case of the horizontal distance of the object of development it is necessary to drill wells with deviation from the vertical. These deviations often have large angles, so the horizontal displacement of the face from the mouth can be up to several kilometers. It is necessary to determine the passage of borax in space and then to follow precisely the optimal trajectory of drilling. This trajectory for maximum efficiency of field development often must take place in a narrow range of depths. The trajectory thus consists of straight line segments and changes of direction of the barrel.

For directional drilling a downhole motor with the curve sub or rotary-driven systems are typically used. In this case the increase of drilling speed can be achieved without interrupting drilling operations. Such stops are connected with the necessity of lifting the tool at a certain distance from the face to adjust the position of a whipstock in the case of using downhole motors and drilling slide. The use of rotor systems can increase the rate of penetration and improve the quality of the barrel because of more efficient cleaning. And the resulting ability to conduct drilling operations at reduced discharge pressure reduces the density of the drilling mud circulation and thus reduces the risk of fractures in the reservoir. However, in this case the control occurs by manual control of the discharge of drilling mud. That provides remote controlling the trajectory of the well.

Some autonomy in modern rotor systems is achieved primarily via implementing automatic deduction of the specified angle and azimuth of constant rate. However, even for the observance of barrel vertical trajectory in offline drilling it is necessary to consider not only available for measuring, but also predictable forces that affect the column can deflect the trajectory of the drilling tool from its specified trajectory. According to research, in this case the most effective is the algorithm that on the basis of the received real-time downhole data gives the most accurate prediction of possible deflecting impacts and incorporates them in the formation of control signals.

Currently, even in manual operation a significant percentage of erroneous operator actions is caused by the insufficiency of downhole data. A small number of sensors and their low accuracy, low update rate of information from them on the surface, and a large propagation delay distort the real situation on the basis of which the operator makes decisions, leading to emergency situations.

Automation and control of fluids while drilling. Maintenance of drilling fluids properties in the range of values required in the definite drilling conditions is the most important condition for the effectiveness and success of drilling operations. The hydraulic system consists of the following subsystems: solid fractions control, waste disposal, processes at the bottom of the borehole and drilling mud preparation and injection [10–14].

Automation in this system has become possible due to implementing a method of drilling a under control pressure. In this method back pressure at the mouth is controlled by the nozzle to maintain a constant bottomhole pressure. The exact location of the nozzle is calculated by the hydraulic model which is constantly adjusted during drilling operations. The adjustment is conducted according to a bore bit depth, speed of rotation, torque, density of the drilling fluid, rheological data, temperature, flow rate. Selection and analysis of the drilling mud sample is carried out manually and takes a lot of time, so that the errors appear in the model.

The most important controlled solution parameters are: solids content, flow, pressure, electrical stability, oil-water factor, viscosity, oil-based capacitance of fluids, density, static and dynamic downhole pressure, etc. It is necessary to consider amendments to temperature fluctuations, etc. In addition to regular actual measurements, the accuracy of trend changes determining is also important.

Only by taking into account all of these factors it is possible to implement automation into the process of preparation of drilling mud and to get a positive effect. Hypothetically, it is possible to achieve the greater effect by integrating this system into the overall automation system of the rig.

The problem of energy supply. Normal functioning of the automation is impossible without a set of qualities of electricity on the rig. This problem becomes the most actual on stand-alone objects. The limited capacity of the stand-alone power plant and the growth of Converter load with nonlinear volt-ampere characteristic of stand-alone objects make electromagnetic compatibility of technical means the matters of primary importance. The use of thyristor drive and semiconductor frequency converters of electric power decrease the power factor of the electricity system and increase the power of the distortion consumed from the main plant. As a result, inactive power (the amount of power distortion and reactive power consumed from the power plant) becomes commensurate with the useful power. Higher harmonics of current and voltage generated into the net by Converter load create inactive power distortion. They also become interferences which spread over power supply circuits and signal circuits and interrupt the normal operation of automation.

This problem is important on ships and platforms when they location must be kept unchanged. Positioning can be performed either according to the tag (RFID) at the well or according to a global positioning system (GPS or GLONAS). Currently, the systems of dynamic positioning are embedded for these purposes. But regardless of the implementation of the tracking object, the control of a vessel or platform still remains main the task. Different thrusters with electric drive power up to 1,5–2 MWatt are used for object positioning. The number of such devices on floating platforms can reach 4 pieces. Besides, the devices should have high dynamic and other characteristics. So, asynchronous motors in conjunction with frequency inverters, converters, etc. in the function of propeller engines of bow thrusters become widespread.

Specific characteristics of the autonomous power systems make it impossible to use the means of improving electric power quality and electromagnetic compatibility applied at coastal enterprises. They require new specific solutions.

The conclusions. A new group of automation means can help to overcome many problems typical for oil and gas industries, to improve the efficiency of oilfield development. This group can include new developments in the field of downhole sensors that will provide measurements of high quality; new developments in the design of drill pipes with cable or fiber optic wiring. These drill pipes will allow providing large amounts of received information to the surface. They will also ensure an opportunity to monitor pressure and temperature in the annulus along the drillstring which will allow monitoring the parameters along the whole barrel.

The industry also needs tools and algorithms of rapid compression, decompression and analyze of  large volumes of information which will allow drilling engineers and automation systems to detect risk factors, such as freeze-failure, torsion, axial shock, Bouncing bits, etc. in real time. It is also necessary to have algorithms for data systematizing, diagnosing the  phenomena, generating corrective actions and making decisions on the further course of the process without human intervention.


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The article was published in issue no. № 2, 2015 [ pp. 113-118 ]

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