Subject ▸ petroleum engineering

Data Science for Petroleum Engineering - Part 5.1: Data Introspection with R

17 August 2017

NOTE. You can find the PDF version of the R markdown notebook in GitHub at this link. The reproducible R markdown notebook (.Rmd) itself is here. Both are full versions of this LinkedIn article. For the time being, LinkedIn publishing does not support markdown which would make sharing scientific and engineering documents much easier. Transforming Excel well raw data into datasets This section is about getting familiar with our data.

Growing your petroleum engineering library: calling FORTRAN from R

21 July 2017

petroleum engineering, R, engineering library

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.

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

3 July 2017

petroleum engineering, fluid properties, R

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.

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

21 April 2017

petroleum engineering, R

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.

OTC 2016: second day

5 May 2016

petroleum engineering, conference

For the first time since I started attending OTC in 2001, I could park in the first row of the parking lot. I wonder why! Couple of things grabbed my attention immediately during the session “Coping with low prices”: a more collaborative attitude between Deepwater companies to share R&D costs; “co-creation”, and despite of the low oil prices and financial straits, keeping safety first as a non-negotiable. I was happy to hear that maintaining the culture of safety is as important, or more, than fitting the financial targets.

Data Science for Petroleum Production Engineering. Part 2: Acquiring the data

16 April 2016

data science, petroleum engineering

In the past session we got an introduction to the multiwell statistics package showing a few of the things that we can do with the Petronas PTech Engineering Library. Now, we will explore some more functionality. It is incredible the huge amount of information when we get from all the wells in one scan pass. The data starts to have sense. A well in isolation or standalone doesn’t tell used much about the field or differences between well parameters from well to well.

Data Science for Petroleum Production Engineering

14 April 2016

data science, petroleum engineering, python

In the last century, the production engineer built the well models one by one and analyzed the results also one by one. With the ubiquity of the personal computer, desktops and laptops, an unimaginable computational power has been put in our hands. But we need the right tools! The spreadsheet was invented in the 80’s and was a great invention. The beauty of it is that you can produce results right away.

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