Subject ▸ python

Python, 3D seismic using segyio by Matteo Nicoli

Found this interesting article in LinkedIn: WORKING WITH 3D SEISMIC DATA IN PYTHON USING SEGYIO AND NUMPY (MOSTLY) by Matteo Nicoli. It comes with code, Python notebook and repository. Keywords: segyio, seismic, python, notebook References: segyio Software Underground Post

Calculate economic risk with regression using Python by Matteo Niccoli

Another reproducible example of regression using Python to calculate economic risk. By Matteo Niccoli (2017). Keywords: References Article Post Python notebook

Python and PVT by Mark Burgoyne

PVT coded in Python! Keywords: PVT, Python, phase behavior, EOS References Article Post Python notebooks Repository geostats guy repo Book Phase Behavior at SPE Juan W Cottier at LinkedIn

I learned with Python but I now love R

I learned Python 10+ ago. With R now in my toolbox, it is difficult to go back. But still I am coding in Python to maintain the old code. What I really dislike is: the Jupyter notebooks, although I fell in love with them at first sight; the acceptance of organized chaos with the multiple versions floating around. I guess you get use to it when you are part of the Py ecosystem.

Python libraries for Production Engineering

Somebody asked me earlier if I know of libraries for Production Engineering written in Python. Meaning, open source code for production engineering, production optimization, artificial lift, or gas lift, specifically. Unfortunately, to my knowledge, there are not open source Python libraries for Production Engineering. Most of the applications or software for optimization and nodal analysis are proprietary requiring fees and and licenses. From that side, the curious petroleum engineer would have to code everything, practically, from scratch.

For what things R programming language is better than Python?

I used and wrote Python applications for more than 10 years. Then, I started to use R for my data science projects in Petroleum Engineering. I know Python quite well, being one its major weaknesses multiple versions of Python floating around and packages with no “adult” supervision. Anyway, after 2 years of R experience (far too short if you compare it with that of the R experts), this is my take on what makes R better than Python:

Is R as versatile as Python?

The short answer is no. R is not a versatile as Python. R is a comprehensive statistical, mathematical and scientific tool. Its learning curve could be daunting and intimidating but the effort pays if you deal with data every day. Python and R are not in the same league either. While Python is a generic developing and prototyping tool, R focus is narrower, focusing on providing sciences and engineering with well thought data analytics functions and packages.

Data Science for Petroleum Production Engineering

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.

Scripts applied to well and network modeling

Table of Contents Getting data from a well model using a single well class Geothermal gradient and downhole equipment arrays Automatically calculating BHP from WHP State of the file before BHP calculations State after BHP calculations Getting basic well test data from a model Building a well test dataframe A dataframe for Downhole Equipment