Subject ▸ R

Data Science for Petroleum Production Engineering 3: Anonymizing Well Data

It happens with certain frequency: we need to share some well data but for confidentiality reasons we can’t. It could be a paper, sharing with colleagues, a conference, a lecture, an article; 1001 reasons. How can we share some well data without giving away our well names, or platform, and field? Note: this is a recurrent topic in medicine, genetics, bio-sciences, health care and other industries where privacy is paramount.

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Growing your petroleum engineering library: calling FORTRAN from R

If you have already installed R and RStudio in your Windows PC or your Linux laptop or your Mac Book, then you need to think about including FORTRAN subroutines in your R toolbox. There are plenty of excellent math libraries built with old friend FORTRAN that greatly deserve to be part of our engineering library, either, to improve performance, or just avoid retyping (convert) of the whole routine in R.

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Building your own petroleum engineering library with "R": humble beginnings with the compressibility factor 'z'

Few weeks ago I was working on the marching algorithm to create vertical lift performance (VLP) curves and datasets for statistical analysis using the classical Hagedorn-Brown and Fancher-Brown correlations. Then I noticed some weird variations in the column for the compressibility factor or z. I started to investigate and found discontinuities in parts of the isotherms that are used for building the gas compressibility correlations. Digging a little bit more finally found that the problem was that the values of the fluid properties of my well had accidentally hit a critical point in the equations.

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My blogdown adventure

I have had my notes here and there: Evernote, network drives, LinkedIn, SPE forums. And I could never find the ideal way to put the data and info together until I found Hugo. Blogdown documentation I borrowed the template ideas for my blog from Ron J. Hyndman blog. The source code for the site is now hosted on github. If you find any problem in this site, please feel free to let me know at.

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"R" and the search of the ideal language for petroleum engineering

I have to confess my sin. I am coming from writing thousands of lines of Python code for a well modeling and optimization project. I did Exploratory Data Analysis (EDA) for the resulting well models and applied statistics using Python, pandas, matplotlib, SciPy and NumPy. I went full throttle and didn’t look behind. Got the results, the production engineering team increased the oil production we were looking for.

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