Author(s): Abusal YA*, Prokofev AA, Ismakov RA, Gazizov RR and ALDwairi RA
This article presents an in-depth exploration of the design, modeling, and control of an advanced inflow control device (ICD). Existing control systems for ICDs are analyzed, highlighting their key features and assessing their advantages and drawbacks. Based on this analysis, the development of a new ICD design is proposed incorporating an electro-hydraulic control system.
The mathematical description of the valve operation is provided, elucidating the principles behind its functioning. To simulate and evaluate the performance of the proposed ICD, a comprehensive model is built using Simulink, integrating a matrix approach and neural networks. The model enables the qualitative determination of the valve position based on the generated pressure drop, contributing to the optimization of the device’s performance.
The article emphasizes the importance of automatically adjusting the actuator’s position based on real-time measurements from various instruments. This enhances the efficiency and reliability of the ICD in dynamically controlling the flow rate in production wells. The use of a neural network-based approach aids in accurately determining the density of the flowing fluid and its impact on pressure drop, facilitating effective control strategies.
The results of their research are demonstrated, showcasing the successful operation of the developed ICD model. Through the use of 3D views and crosssectional diagrams, the article provides a visual understanding of the ICD’s components, including the overall device, central axis, and pressure sensor setting.
This article contributes to the advancement of inflow control devices by offering novel insights into their design, mathematical modeling, and control mechanisms. The findings pave the way for improved reservoir management, enhanced production optimization, and more efficient utilization of oil and gas resources.
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