Polymer Flooding Spreadsheets

Polymer Flooding Spreadsheets Disclaimer: All information is provided in good faith for guidance and reference purposes only. The user is the only person accountable for the outcomes, and we therefore ask to check the relevance and accuracy of the data provided.

This Polymer Flooding Spreadsheet page provides a collection of spreadsheets, scripts, and technical tools designed to support polymer flooding and conformance water shutoff projects. Whether you’re working on EOR optimization, injection design, or water control strategies, these resources help streamline calculations, improve decision-making, and enhance operational efficiency.

All resources are freely available to help you simplify workflows, run simulations, and improve field applications. Browse, download, and integrate these tools into your projects for data-driven polymer flooding and water shutoff solutions.

Feel free to provide suggestions or your own material to help other geoscientists improve their workflows to move faster from the concept to the field implementation.


Polymer Flooding & Chemical EOR Economics Spreadsheet

Gain a clear and structured approach to evaluating the economic feasibility of polymer flooding and other chemical EOR methods with this three-sheet spreadsheet. It provides a basic yet accurate estimate of total costs, helping you rank candidate projects, build stronger scenarios, and make informed decisions about implementation.

What’s Inside?

🔹 Sheets 1 & 2 – Focus on polymer flooding (PF), surfactant-polymer (SP), and alkali-surfactant-polymer (ASP) methods. These sheets intentionally omit the time value of money, allowing you to quickly estimate costs based on pore volume, oil in place, polymer cost, and injection rate. By adjusting concentrations and injected volumes, you can model total project expenses. While the duration of oil recovery remains uncertain, the model conservatively assumes that once polymer injection stops, water breakthrough will end the project—defining its economic lifetime.

🔹 Sheet 3 – Introduces basic production profiles, adding a time factor to the equation to enhance long-term planning and forecasting.

This tool is perfect for early-stage evaluations, offering a practical way to assess cost-effectiveness before diving into detailed simulations.

✅ Quickly estimate OPEX & CAPEX
✅ Compare and rank EOR candidates
✅ Refine project assumptions with scenario modeling

Purchase now for 95 euros.


Calculating Shear Rates in Vertical Wells – Python

This python code will plot the shear rates in vertical wells to help assess potential mechanical degradation.

Calculating shear in vertical wells – python code
Calculating shear in vertical wells – python code

Here’s a code to calculate and plot the shear rate in python. The file is in PDF but code can be copied easily. Any feedback is welcome.

Remarks: The code  provided is written in Python and uses the `tkinter` module for GUI. This code is compatible with both Windows and Unix-like operating systems without any modifications. However, there are a few things to note for a seamless experience:

1. **Libraries:** Ensure that you have the required libraries installed (`numpy`, `tkinter`, and `matplotlib`). You can install them using pip:
“`bash
pip install numpy matplotlib
“`

2. **Python Environment:** The code is written for Python 3, so make sure you are running it with Python 3.x.

3. **Matplotlib Backend:** `Matplotlib` uses different backends to render its plots. While it should automatically pick the best one for your OS, if you run into any issues on Windows, you might want to explicitly set the backend to be used with `TkAgg` (which works well with `tkinter`). To do this, add the following lines before importing `matplotlib.pyplot`:
“`python
import matplotlib
matplotlib.use(“TkAgg”)
“`

4. **Windows High DPI Displays:** If you’re running the application on a high DPI display in Windows, the application might appear blurry by default. This can be fixed by adjusting the DPI settings for Python in Windows or by adding a manifest file to your Python application.

For most standard setups, the code will work on Windows without any modifications. However, based on the specifics of the environment, you may need to address the points mentioned above.


Polymer Flooding Predictive Model

Polymer Flood Predictive Model (PFPM)

Polymer flooding modelling with commercial simulators hasn’t provided full satisfaction so far. Predictions regarding injectivity, oil recovery, and sweep efficiency are often far away from the actual field results.

Some analytical methods exist as proposed by Gary Pope’ student in the 80’s, reused for Captain field injectivity calculations for instance. Other companies prefer a benchmark using simple 1D (Buckley-Leverett) simulation (see Hilcorp, Milne Point) to provide the teams with robust comparisons.

In the late 80’s the US DOE developed a small MSDOS exe called PFPM which has disappeared from the web.

This tool is  a streamline/tube model with the following characteristics:

  • 3D, 2-phase (water and oil) 5-spot computer model to predict oil recovery from a polymer flood
  • Developed by US DOE
  • Combines oil recovery prediction with economics to get NPV
  • Fractional flow and streamtube method
  • Correlation based on simulation results used to model polymer slug size effect
  • Adsorption, RRF are included
  • Heterogeneity is accounted for by entering layer data
  • Single value of polymer viscosity and adsorption
  • Streamtube method used to calculate areal and vertical sweep efficiency
  • The area between 2 streamlines is a streamtube
  • Each layer is divided into 8 streamtubes from the injector to the producer
  • 1/8 of a five-spot pattern is used for calculations due to symmetry of flow patterns
  • 1D linear displacement is calculated along each streamtube using fractional flow theory
  • Each streamtube is divided into 20 equal initial pressure drop increments (blocks)
  • Combined results from all streamtubes and layers provide the 3D performance

It is a bit more detailed compared to basic 1D, and provides already useful insights. The only part missing is control of injection pressure/injectivity, which is the main factor impacting economics and the oil recovery calculation results.

For the .exe, please drop us a message. We have attached here a couple of screenshots + pictures of the model.


Excel Spreadsheet for Shear Rate in Vertical Wells

Spreadsheet – shear calculations for vertical perforated wells

This Excel spreadsheet can be used to understand how shear rates vary in perforated vertical wells. This should help design the perfect completion to minimise mechanical degradation and avoid studying some parameters such as shear-thickening.

You can also check our YouTube channel for additional videos and podcasts and navigate the Polymer Flooding Guide for more content or our Academy for online training courses.