Polymer Flooding Simulation Modeling Feasibility Study: Understanding Key Aspects and Design Optimization
- Wahyu Hidayat (Saudi Aramco) | Nasser ALMolhem (Saudi Aramco)
- Document ID
- Society of Petroleum Engineers
- SPE Middle East Oil and Gas Show and Conference, 18-21 March, Manama, Bahrain
- Publication Date
- Document Type
- Conference Paper
- 2019. Society of Petroleum Engineers
- 1.2.3 Rock properties, 5.4 Improved and Enhanced Recovery, 5.3.6 Chemical Flooding Methods (e.g., Polymer, Solvent, Nitrogen, Immiscible CO2, Surfactant, Vapex), 5.4 Improved and Enhanced Recovery, 0.2 Wellbore Design, 5 Reservoir Desciption & Dynamics, 5.5 Reservoir Simulation
- Enhanced Oil Recovery, Polymer Flooding, Reservoir SImulation, Optimization
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The paper discusses the feasibility study approach of polymer flooding enhanced oil recovery. This work is focused on understanding and quantifying key aspects of polymer flooding and design parameter optimization case. A synthetic reservoir simulation model was employed for the study.
The first stage is to identify and understand key factors that have most significant impact to polymer flooding response. There are eight parameters that are considered in the analysis, such as polymer concentration, polymer thermal degradation, polymer injection duration, and polymer-rock properties (adsorption, residual resistance factor, etc.). The impact of each parameter to oil recovery response was sensitized with its low, mid, and high values. The difference of high to low oil recovery output for all parameters was ranked to determine their significance levels. The top three parameters obtained from the sensitivity analysis are polymer injection duration, thermal degradation, and polymer concentration. Sensitivity cases of polymer injectivity and thermal degradation effects were covered in this work.
The second stage is to determine optimum design parameters of polymer flooding. The most significant parameters from the sensitivity analysis results were considered for further optimization. Three parameters that were selected for design optimization include polymer injection duration, polymer concentration, and well spacing. An optimization workflow with simplex algorithm is linked with a reservoir simulator to generate optimization cases by varying values of optimized parameters. The optimization iteration stops when the maximum value of the objective function, which is the net revenue, is reached. The optimization cycle was done for rock permeability of 500 md and 1000 md.
For a low rock permeability reservoir, the well spacing should be short and a lower polymer concentration is sufficient to provide a good response, in addition to avoiding potential injectivity problem. There should be minimum injectivity problem for reservoir with permeability above 1000 md. It is very important to apply polymer thermal degradation in the simulation model to avoid an optimistic performance prediction. The sensitivity analysis results provide a good understanding on the significance impact of parameters controlling polymer injection response and potential challenges. The optimization approach used in the study aids in investigating many optimization scenario within a short period of time.
|File Size||1 MB||Number of Pages||11|
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