Multivariable MPC for Coalbed Methane Production Optimization
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Solution Overview
Problem
Conventional control systems for coalbed methane (CBM) production are inefficient due to their single-variable regulatory control solutions, which cannot handle multiple constraints or coordinate the operation of separate regulatory controls to achieve global optimization objectives, leading to operational complexity and reduced production efficiency.
Innovation Solution
The implementation of multivariable model predictive controllers (MPCs) that simultaneously manipulate multiple inputs to maintain desired outputs within constraints, using a dynamic multivariable predictive model to optimize coalbed gas production by regularly measuring and adjusting process parameters in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If single variable regulatory control solutions are used, then the control system is simple to implement, but it cannot handle multiple constraints or achieve global optimization objectives
Solution Approach 1:
The patent merges multiple single-variable control systems into a unified multivariable MPC system that simultaneously manages multiple controlled variables (well pressures, flow rates, compressor pressures) and manipulated variables (choke valve positions, compressor speeds). This integration enables the system to handle multiple constraints and achieve global optimization objectives that individual control systems cannot accomplish separately.
Solution Approach 2:
The multivariable MPC system serves multiple functions simultaneously: it optimizes gas production rates, maintains pressure constraints across multiple wells, coordinates compressor operations, and adapts to changing field conditions. This multi-functionality replaces the need for separate specialized control systems for each function, improving overall productivity while managing complexity through a single unified controller.
2Productivity
If multivariable MPC is implemented to optimize production, then production efficiency and quality improve, but system complexity increases
Solution Approach 1:
The MPC system employs dynamic prediction models that continuously adapt to changing CBM field conditions, well performances, and operational constraints. The controller dynamically adjusts manipulated variables based on predicted future states of the system, enabling it to handle non-deterministic behavior and optimize production in real-time despite the inherent complexity of managing multiple interconnected wells and compressors.
3Ease of operation
If separate regulatory controls are used for each well, then individual well control is simple, but coordination between wells and compressors is poor
Solution Approach 1:
The multivariable MPC system implements comprehensive feedback mechanisms that continuously monitor controlled variables from all wells and compressors, compare actual performance against target values, and adjust manipulated variables accordingly. This coordinated feedback approach ensures that individual well control actions are harmonized with overall field objectives, maintaining reliable system-wide coordination while preserving the ability to control individual wells.
Data Source
AI summary
A multivariable model predictive controller (MPC) for controlling a coalbed methane (CBM) production process. The MPC includes input ports for receiving a plurality of measurement signals including measured process parameters from CBM wells in a well field. A control loop includes a mathematical model that controls the CBM gas production. The model includes individual production characteristics for each CBM well that predicts its behavior for controlled variables (CVs) with respect to changes in manipulated variables (MVs) and disturbance variables (DVs). The control loop calculates future set points for the MVs based on the model and the measured process parameters for CBM production to achieve at least one control objective for the well field. A plurality of output ports provide control signals for implementing the future set points which when coupled to physical process equipment at the plurality of CBM wells control the physical equipment to reach the future set points.