/pdf/downhole-water-loop-dwl-well-completion-for-water-coning-zzagympesw.pdf

Downhole water loop (DWL) well completion for water coning control --- theoretical analysis


 The main challenges during the operation of electric submersible pumps (ESP) lifted wells include running the well at its optimal point, while honoring operational constraints posed by the production system, and extending the service life of the equipment. Overcoming these challenges will typically require building and continuously updating a model of the system. Now, due to issues such as high cost of sensors (including installation, calibration and maintenance), difficulty to reach the sensing point or lack of adequate technology, measuring some variables may be very hard or even impossible. An alternative is to develop a virtual sensor (model) to estimate unmeasured variables from measured values of other variables at different locations along the well. This work presents a model developed based on physical principles to accurately estimate key operational parameters of ESP lifted wells. The model comprises three differential equations that express the derivatives of pump flowrate, submergence level and well head pressure. Assuming as known the pump frequency, casing head pressure and production line pressure, these equations are solved numerically to estimate time profiles of submergence level, well head pressure, pump flowrate, pump intake pressure, pump discharge pressure and flowing bottomhole pressure. The model was instantiated and simulated for a particular ESP lifted well, and showed outstanding performance when estimating pump intake pressure and pump flowrate, as compared to a commercial simulator. The proposed virtual sensor exhibits high accuracy using a model with simplified equations, which can be executed quickly and reliably using few computational resources (processing time and memory); therefore, this sensor is completely suitable for direct installation in the ESP well (on a PLC or a RTU) for real-time monitoring, control and optimization. Other advantages of the proposed model include that it (i) reduces the required surface and bottomhole instrumentation, (ii) estimates the values of the variables during the transient between operating points, (iii) can be used to analyze the influence of operating parameters in the well behavior, without affecting production rate, (iv) incorporates a service factor to account for the equipment wear due to normal operation and (v) can be used in the implementation of optimization and control strategies.

A First Principles Model for Virtually Sensing Operational Parameters in an ESP Well

Ingress of water and sand is the most common complication, especially characteristic of the latest gas field development stage as it is approaching the end of life. Reducing the flowrate below a certain threshold results in the accumulation of fluids in the bottomhole, which further reduces the flowrate and causes a self-kill. High flowrate removes moisture but can destroy the bottomhole formation zone and increase the sand production. This makes it imperative to keep the flowrate within a specific optimal range, which is established by means of periodic gas dynamics tests. In the inter-test time, there is no data on the well status except the wellhead temperature and pressure. This paper proposes an automatic flowrate control system to complement the standard well-based parameter recorder; the system is based on a sensor that uses acoustic emissions to detect sand and condensed moisture. The sensor monitors the sand production and condensed moisture removal; it transmits this data to the site APCS on request or as an alarm. Data is transmitted via the wireless channel used by the recorder. The system enables quick detection of well complications to alter its operating parameters so as to keep the flowrate within acceptable limits. Continuous update of the well status keeps the geological and mathematical models of the field up-to-date.

Automatic Gas Well Flowrate Control System for Urengoy Gas-Condensate Field

Abstract Due to the pumping units' dual role as alternating loads and new energy sources, multi-source DC microgrid pumping unit well clusters experience increased fluctuation in voltage and power as well as peak and valley values that are superimposed. This work presents a distributed cooperation strategy based on the grouping weighted moving average algorithm for pumping unit well groups in multi-source DC microgrid. Centralized control program is implanted in the RTU of the single well controller of each pumping unit, and the communication of each single well is realized by SCADA system to construct the distributed well group system. The real-time power values of the pumping well group are calculated by grouping the power values and granting weighted weights to each group, using the total power fluctuation threshold of the well group as the control target, and further using a weighted moving average algorithm to predict the next power value and form a table of predicted real-time power spectra. According to the power value in the community power spectrum table, the inverter frequency is proportionally adjusted downward to achieve the power peak before deceleration to reach; after crossing the power peak, the frequency is raised in the same way to accelerate the compensation to achieve the power valley before acceleration to reach, that is, acceleration compensation, and finally achieve the power peak and valley values of the bus system to level off, and further learn to reach the set impulse, and finally form a stable impulse. Through laboratory testing and field application in Shengli XIN-11 block application proved: the group control software module not only effectively suppresses the active power peak and valley values and voltage fluctuations of the bus system, the active power fluctuation rate range decreases by more than 70%, the DC bus voltage fluctuation range decreases by more than 80%, but also reduces active power by about 6% without increasing the cost of new hardware. 

Research on Multi-source DC microgrid Distributed Group Control Strategy for Pumping Well Cluste

Due to the alternating loads on pumping units and the integration of new energy sources, multisource DC microgrid pumping unit well groups experience increased fluctuations in voltage and power as well as superimposed peak and valley values. This work presents a distributed control strategy for pumping unit well groups on a multisource DC microgrid based on the weighted moving average algorithm. A centralized control program is implanted in the RTU of the single-well controller of each pumping unit, and communication with each well is realized via SCADA and multicast communication, resulting in a distributed well group system. The real-time power values of the pumping well group are calculated by grouping the power values, and each group is weighted using the total power fluctuation threshold of the well group as the control target. Then, a weighted moving average algorithm is used to predict the next power value and form a table of predicted real-time power spectra. According to the power values in the community power spectrum table, the inverter frequency is proportionally adjusted downwards to reach the power peak before deceleration; after the power peak is crossed, the frequency is increased in the same way to reach the power valley before acceleration. Finally, the peak and valley power values of the bus system level off and further learn to reach the set impulse; ultimately, a stable impulse is formed. In laboratory testing and field application in the Shengli Oilfield XIN-11 block, the group control software module effectively suppressed the active power peak and valley values and voltage fluctuations of the bus system, the active power fluctuation rate range decreased by more than 70%, and the DC bus voltage fluctuation range decreased by more than 80%; moreover, the active power decreased by approximately 6% without additional hardware costs. 

Development of a distributed group control strategy for pumping well groups connected by multisource DC microgrids

In this paper is presented an Intelligent Well Systems for the Industrial Production of Oil. Such scheme is tested for gas lift (GL) oil wells. The proposal is based on the production assessment, in the utilization of the process variables (specifically, the bottom-well and surfaces pressures), and the operational scenarios detection (in the case study, the production of the oil well), with the objective of optimizing the producing performance of the well. The proposal combines intelligent techniques (Fuzzy Classification Systems) and Mass Energy Balance. Our approach allows determining and controlling the oil or gas flow that a well can produce, taking into account the completion geometry and the reservoir potential, as well as the criteria related to the well's performance curves of oil and gas.

Intelligent Well Systems

Modelados de pozos de producción por bombeo mecánico utilizando técnicas de computación inteligente

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Intelligent Well Systems

Modelados de pozos de producción por bombeo mecánico utilizando técnicas de computación inteligente