Injection Well Performance Modeling for CO2 Phase and Pressure Shifts
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Solution Overview
Problem
Existing methods for controlling injection wells, particularly for CO2-rich fluids in deep or depleted reservoirs, fail to accurately predict and manage injection performance due to the complexities of fluid phase changes and pressure dynamics.
Innovation Solution
A process involving a surface network simulator and reservoir simulator is used to iteratively determine the relationship between flowrate and bottom hole flowing pressure, accounting for fluid phase changes and pressure conditions over multiple time steps, using VLP and enthalpy tables to accurately model fluid behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If VLP and IPR curves are used to control injection wells, then the control method is simple and widely applicable, but it fails to accurately predict injection performance for CO2-rich fluids in deep or depleted reservoirs
Solution Approach 1:
The patent transitions from using static VLP and IPR curves to a dynamic simulation approach that accounts for fluid phase changes, temperature variations, and pressure dynamics. The simulation model incorporates thermodynamic properties and phase behavior of CO2-rich fluids under reservoir conditions, enabling accurate prediction of injection performance in deep or depleted reservoirs where traditional methods fail.
2Measurement precision
If a simulation model accounting for fluid phase changes and temperature effects is used, then injection performance prediction accuracy is improved, but the computational complexity and data requirements increase
Solution Approach 1:
The patent employs an iterative simulation process that acts as an intermediary between the complex physical phenomena and the practical control requirements. The simulation model integrates thermodynamic calculations, phase behavior analysis, and flow dynamics to bridge the gap between theoretical accuracy and practical application, providing reliable injection performance predictions while managing computational complexity through structured iterative solving.
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 precise control of injection wells by predicting fluid phase distribution and temperature effects, ensuring well and reservoir integrity, and optimizing injection performance, especially in deep or depleted reservoirs.
Implementation Method 1
the fluid being injected at a wellhead at a wellhead flowing pressure and a wellhead flowing temperature at which the fluid is in liquid or dense phase
Implementation Method 2
The VLP accounts for phenomena occurring in the well, in particular frictional, gravity and acceleration pressure drops
Implementation Method 3
The VLP accounts for phenomena occurring in the well, in particular frictional, gravity and acceleration pressure drops and heat exchanges with the environment
Data Source
AI summary
A process of determining a future injection performance of a well, a fluid being intended to be injected from a surface network into a geological formation defining a reservoir, the injection performance providing a relationship between the flowrate and a bottom hole flowing pressure, the process comprising obtaining a first set of data (VLP and bottom hole enthalpy), obtaining a surface network simulator, and a reservoir simulator, providing the reservoir simulator with a current working point of the well, running the reservoir simulator and obtaining updated pressure conditions in the reservoir, calculating a second set of data (IPR) for a next time step, providing the surface network simulator with the second set of data, and obtaining the bottom hole flowing pressure for the next time step and an updated working point. The injection performance is obtained from the second set of data.