Subject ▸ Text Mining

Evolution of data science, machine learning and artificial intelligence in Petroleum Engineering papers

Motivation I have been lately curious about how the terms data science, machine learning and artificial intelligence evolved over the years in petroleum engineering papers. It is not that machine learning or data science are brand new fields of study; quite the contrary, they have been around for decades, as it has been artificial intelligence. Procedure The current hype is due to (i) the sheer computational power available; (ii) the availability of fast engines in the cloud; (iii) open source software such as Python, R, Octave, Hadoop, Spark, Scala, MongoDB, Javascript, VirtualBox, containerization tools; (iv) an operating system that runs under all platforms Unix/Linux and different microprocessor architectures;; (v) the almost-free online education by some of the best professors in the world; (vi) and the dissemination of knowledge through the internet (books, papers, articles).

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Text Mining for Petroleum Engineering: Modern Techniques for Paper Research

Last week I was talking with a colleague about some projects that could be deployed using R, and then the topic of well technical potential came up. I got hooked by the term and then decided to explore it a little bit more. What is not better that going to the OnePetro website and search for papers on “technical potential”. I did and found 132 papers matching the term. Well, I was not going to purchase those 132 papers, you know.

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R for Petroleum Engineers: text mining for SPE papers

Introduction If you you love searching, finding, reading and collecting papers when working on a particular petroleum engineering topic, keep reading. We will be using some digital tools and stats to keep up with the 21 century. :) I have just published a new R package called petro.One which website you could see here. All the code, notebooks, datasets, figures, etc., are located in GitHub at this repository. Everything is explained in detail there but I will show here a summary of what the package does.

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Data Science for Petroleum Engineering: extracting metadata from papers in OnePetro

Hi there, digging into the papers available in OnePetro is intoxicating. You know a bit - get a piece of the data - and you want to know more and more. That resource could be further developed into accepting comments, notes and highlights from those who have read, or reading, the papers. And of course, assigning subjects and disciplines as categories. In other words, the OnePetro site could turn into giving smarter response to queries.

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