Abstract
This paper addresses control over flushing a well, which belongs to the class of non-stationary dynamic stochastic objects. The object evolves over time and has a large transport delay, which increases with an increase in the well's length. The current work is aimed at solving the tasks on improving a mathematical model of the automated control system taking into consideration a constraint on the capacity of a drilling pumping unit. The normalized transition functions of a pumping unit have been examined, based on which the magnitude of the delay has been determined, and the structures and parameters of typical controllers have been synthesized. It has been established that the only way to improve control quality is to use a more complex controller, which can reduce the negative impact of the delay. The closed automated control systems with delay have been investigated, which ensures better indicators of the control process compared to the industrial systems based on PI controllers. It has been shown that the Fuzzy-PID-controllers demonstrate better quality indicators – an overshooting of 0 % and a transition process duration of 15 s in a wide range of changes in the external influences and system parameters. An issue of the feasibility of applying the PI, PID-controllers with a Smith predictor has been considered. It has been shown that the quality of the control process involving a PID-controller and the Smith predictor is close to the quality indicators of the system with a Fuzzy-PID-controller. The need has been established to build a system that could independently adapt to changes in the geological and technical conditions and the geo-environment that occur in the process of deepening the well. It has been demonstrated that such systems should have a decision support circuit or be adaptive. The obtained data are useful and important because they make it possible to improve the efficiency of the control process of a technical hydraulic system of deep wells flushing during their deepening
Highlights
The world practice of automating the drilling of wells shows that one of the important tasks for oil gas companies is to increase drilling performance and reduce energy consumption
The following tasks have been set: – to develop an algorithmic structure of the improved controller to improve the efficiency of a drilling mud pressure stabilization system at the inlet to the well; – to synthesize the system of automated control, which ensures the stabilization of drilling mud pressure at the well inlet in real time, without overshooting; – to investigate the quality indicators of the transition process of a drilling mud pressure stabilization system at the inlet to the well, which is based on different types of controllers
The methodological apparatus is a systematic approach and the methods of mathematical analysis, based on which we modeled the system of automated control over the stabilization of drilling mud pressure at the inlet to a borehole with the inverse multiparametric Fuzzy-controller
Summary
The world practice of automating the drilling of wells shows that one of the important tasks for oil gas companies is to increase drilling performance and reduce energy consumption. The automation of a wells flushing process occupies a special place in resolving these issues This is due to the fact that the hydraulic systems of wells flushing belong to the class of complex nonlinear non-stationary dynamic stochastic objects that function under the a priori and current uncertainty regarding their structure and parameters. Programmable controllers have been widely used to control the continuous technological processes in the oil and gas industry They make it possible to implement a control system with Fuzzy controllers, Smith predictors, as well as with multiparametric controllers based on the use of a rotation operator with respect to the object of control, or an adequate mathematical model. In view of the above, it is a relevant task to undertake additional research into the clarification of a mathematical model of the well flushing process and to build the multiparametric inverse controllers, Fuzzy-controllers, and controllers with a Smith predictor for adjusting the operation of drilling pumping units
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