I uploaded to GitHub a Python version of the sand sieve analysis spreadsheet that I used for years. The script will generate a number of plots that help graphically determine sand control options, in a method better than the traditional Excel spreadsheets do.
https://github.com/jack-charles/Sand-Sieve-Analysis
It has a straightforward terminal prompt that allows for:
- Opening a new sieve data file with multiple samples
- Combining multiple sieve data results (plotting old core data with newer offset wells is easy!)
- Selection of screens and proppants as options
- Calculation of the cumulative weight percentages, uniformity coefficients, sorting coefficients, etc.
- Plots of distributions, parameters against depth and other parameters, and screen/proppant data to determine suitability of sand control
- Basic input error detection, but don’t stress the program if you can help it!
- Displays to terminal or outputs to a JSON file
On my to-do list is to incorporate logging data, such as gamma ray, sonic, and density logs to help establish other views of the formation. I would like to also add in sand retention test data from a flow cell (typically retained perm vs pressure and flow) to help make selections. I will make periodic updates to add in other calculations, including converting this to a Flask or other web framework application, and integrating to an SQL database for complete data collection.
If you find this useful or have suggestions for improvements, please let me know. These graphs work for me, but may not be the best for users globally.
This is a first baby step I have in mind for delivering bespoke production and well engineering calculations through an online (internet or intranet) platform. We’re all familiar with enterprise software like Landmark and trust their reliability for well integrity, but I believe there are many other critical calculations that we rely too heavily on Excel for. Even worse is when we must rely on Excel for calculations that are then put into EDM and other software. I will discuss more on my philosophy in later posts, but my own experiences and observations leads me to believe that operator and vendor data is not well managed. GIGO, unaudited calculation tools, and user laziness is a real thing that can make a database with hundreds of entries and gigs of data effectively useless.
Interested in adding this and more to your company’s workflows? Contact me to see how we can make this happen.