Multivariable Controller for Gas Lift Optimization
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Solution Overview
Problem
Optimizing gas lift rates across multiple wells is challenging due to dynamic constraints such as ambient temperature, gas density, and back pressure, which affect the compression system capacity, leading to suboptimal production and economic viability issues.
Innovation Solution
A system and method that utilize a multivariable controller to concurrently control and optimize the lift-gas compression, extraction, and production separation processes based on asset data, enabling real-time adjustments to maintain optimal gas lift rates and maximize production while minimizing the impact of disturbance variables.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If gas lift rate is increased to increase production, then production increases, but loading on compression system increases and production may drop due to throttling
Solution Approach 1:
The system dynamically adjusts gas lift rates based on real-time compression system capacity and well conditions. The multivariable controller continuously optimizes gas lift rates as conditions change, transforming the static gas lift system into a dynamic one that adapts to varying production demands and compression capabilities.
Solution Approach 2:
The system changes operating parameters (gas lift rates, compression capacity, back pressure) to optimize production. By adjusting these parameters in response to changing conditions, the system navigates the trade-off between increasing production and avoiding compression system overload.
2Productivity
If gas lift rate is increased too far, then production drops due to high pressure drop in pipeline
Solution Approach 1:
The system uses feedback from pressure sensors and flow meters to monitor actual pressure drops and production rates. This feedback information is fed into the multivariable controller, which adjusts gas lift rates to maintain optimal pressure differentials, preventing excessive pressure drops that would reduce production.
Solution Approach 2:
The system dynamically responds to changing pressure conditions by adjusting gas lift rates in real-time, transforming a static pressure-management approach into a dynamic one that adapts to varying flow conditions and maintains optimal pressure differentials.
3Productivity
If multiple risers are gas lifted, then production from multiple wells increases, but determining optimal gas lift per well becomes extremely difficult
Solution Approach 1:
The multivariable controller serves multiple functions simultaneously: it optimizes gas lift rates for multiple wells, monitors compression system capacity, adjusts for ambient conditions, and coordinates between wells. This universal controller handles all optimization tasks in one integrated system rather than requiring separate control systems for each well.
Solution Approach 2:
The system merges the control of multiple gas lift operations into a single coordinated system. By combining individual well control with compression system management in one multivariable controller, the system simplifies the overall control architecture while optimizing total production across all wells.
4Adaptability or versatility
If ambient temperature, gas density and back pressure vary dynamically, then compression system capacity changes, but optimal gas lift determination becomes difficult
Solution Approach 1:
The system uses feedback from sensors monitoring ambient temperature, gas density, and back pressure to continuously update optimization calculations. This real-time feedback enables the multivariable controller to adapt to changing conditions and determine optimal gas lift rates despite dynamic environmental and operational variations.
Solution Approach 2:
The optimization system is designed to be dynamic, continuously adapting to changing ambient conditions, gas densities, and back pressures. This dynamic optimization approach transforms the difficulty of determining optimal gas lift under varying conditions into an automated real-time adjustment process.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for dynamic optimization of gas lift rates, ensuring that the production system operates closer to ideal steady-state values, increasing overall production efficiency and reducing the time required for optimization cycles, thus enhancing economic viability.
Implementation Method 1
Gas lifting is an upstream production activity which involves the pumping of gas through a pipework annulus to inject it into a mandrel on a riser between a wellhead and processing equipment. The gas is of a lower density than the medium into which it is injected and thus effectively lowers the density of the material in the riser.
Data Source
AI summary
A method includes controlling a lift-gas compression process, controlling a lift-gas extraction process, and controlling a production separation process. The method also includes receiving asset data and optimizing the lift-gas compression process, the lift-gas injection process, and the production separation process according to the asset data.