Latest Articles/Papers

Science is about curiosity; Data Science is asking the right questions (19 May 2021) More Reading wells from SPE data repository (8 March 2021) More How deep should I go in learning data science, machine learning and computer science? (18 November 2020) More Online The introductory tutorial to my package rTorch has just been released (14 October 2020) More Online My R package rTorch 0.4.2 accepted by CRAN (12 October 2020) More Online

Unpublished

Published

2021

  • New test of a plot. (6 October 2021) More
  • Science is about curiosity; Data Science is asking the right questions. (19 May 2021) More
  • Reading wells from SPE data repository. (8 March 2021) More

2020

  • How deep should I go in learning data science, machine learning and computer science?. (18 November 2020) More Online
  • The introductory tutorial to my package rTorch has just been released. (14 October 2020) More Online
  • My R package rTorch 0.4.2 accepted by CRAN. (12 October 2020) More Online
  • rProsper adds batch automation, dataframe generation. (15 September 2020) More Online
  • Building a gallery of TikZ graphics with R. (1 June 2020) More Online  Github
  • Transcript of interview to John Hopfield by Lex Fridman. (20 April 2020) More Online  pdf  Github
  • Transcript of interview to Stuart Russell by Lex Fridman. (19 January 2020) More Online  Github

2019

  • Transcript of interview of Noam Chomsky by Lex Fridman. (2 December 2019) More Online  Github
  • Is there a clash between Data-driven modeling vs Physics-based modeling?. (6 November 2019) More
  • Transcript of interview of Ian Goodfellow by Lex Fridman. (24 October 2019) More Online  Github
  • Transcript of interview of Peter Norvig by Lex Fridman. (13 October 2019) More Online  Github
  • Any Petroleum Engineer can do reproducible Machine Learning. (22 September 2019) More Online  Github
  • A Generative Adversarial Networks (GAN) in rTorch for creating synthetic datasets. Season 1 Episode 1. (29 August 2019) More Online  Github
  • Transforming Petroleum Engineers in Data Science Wizards. Update 2019. (29 July 2019) More Online
  • R and Python commingled: RPyStats in Windows and Linux. Season 1, Episode 6. (18 July 2019) More Online
  • R and Python commingled: Creating a PyTorch project with RPyStats. Season 1, Episode 5. (17 July 2019) More Online
  • R and Python commingled: Creating a PyTorch project with RPyStats. Season 1, Episode 4. (16 July 2019) More Online
  • R and Python commingled: preparing your machine for RPyStats. Season 1, Episode 3. (15 July 2019) More Online
  • R and Python commingled: a Hello World of RPyStats. Season 1, Episode 2. (14 July 2019) More Online
  • R and Python commingled: how to get the best of both worlds. Season 1, Episode 1. (12 July 2019) More Online
  • Podcast - Petroleum Engineering Data Science. (7 May 2019) More Online
  • When Petrophysics Meets 'Data Science'​: What can Machines Do?. (21 April 2019) More Online  pdf
  • The impact of the Volve dataset. (29 March 2019) More Online
  • Integrating Python and R for data science. Converting Eclipse binary files to dataframes in the Volve dataset. (22 March 2019) More Online
  • A reproducible comparison of the Volve reservoir model. (12 March 2019) More Online
  • The fabrication of an artificial intelligence agent for reservoir history matching from the Volve dataset. (5 March 2019) More DOI
  • Descending into the bottomhole. A Marching Algorithm for Vertical Lift Performance in Petroleum Engineering. (5 February 2019) More Online
  • Exploring drilling data from the Volve dataset with WITSML and R. (27 January 2019) More Online
  • Evolution of data science, machine learning and artificial intelligence in Petroleum Engineering papers. (13 January 2019) More Online  Github
  • Being proven wrong on Linux every day. (11 January 2019) More Online
  • How do you sell a data science project to your boss. (8 January 2019) More Online
  • Why I decided to publish data science in a blog. (7 January 2019) More Online

2018

  • How can a Petroleum Engineer kick start with Data Science?. (4 December 2018) More Online
  • Best Practices for the Construction of Well Models (from the data science perspective). (2 December 2018) More Online slideshare
  • Scripts for Well Modeling and Batch Automation. (29 November 2018) More Online slideshare
  • A book review: Fundamentals of Data Visualization. (11 September 2018) More Amazon Online
  • For what things R programming language is better than Python?. (10 September 2018) More Online
  • An Artificial Lift Method Selector for Petroleum Engineering written in R. (18 July 2018) More Online
  • Is R as versatile as Python?. (4 July 2018) More Online
  • The most used Machine Learning algorithms in Petroleum Engineering. (28 March 2018) More Online
  • A Machine Learning paper research on Petroleum Engineering. (25 March 2018) More Online
  • Paper research in Petroleum Engineering: Do you know how to spell Gas Lift?. (24 January 2018) More
  • Virtualization brings Reproducibility to your Petroleum Engineering Workflow. (3 January 2018) More

2017

  • Text Mining for Petroleum Engineering: Modern Techniques for Paper Research. (24 November 2017) More Online  Github
  • Building your petroleum engineering library with R: Muskat's Material Balance Equation ODE. (9 November 2017) More Online  Github
  • R for Petroleum Engineers: text mining for SPE papers. (27 October 2017) More Online
  • Building your own petroleum engineering library with R: zFactor v0.1.7. (23 October 2017) More Online
  • Building your own petroleum engineering library: zFactor has a website. (8 October 2017) More Online
  • When Data is Too Big to Sail (in my RAM). (6 October 2017) More Online
  • Data Science for Petroleum Engineering: extracting metadata from papers in OnePetro. (1 October 2017) More Online
  • Neural Networks for Petroleum Engineering. (25 September 2017) More Online
  • Data Science for Petroleum Engineering: How does someone become good at Deep Learning?. (23 September 2017) More Online
  • Data Science for Petroleum Engineering. Part 6 - Tidy data. (13 September 2017) More Online
  • Transforming Petroleum Engineers in Data Science Wizards. (25 August 2017) More Online
  • Data Science for Petroleum Engineering - Part 5.3 Finding and filling missing well data in alphanumerics. (24 August 2017) More Online
  • Data Science for Petroleum Engineering - Part 5.2: Finding and filling missing data. (22 August 2017) More Online  pdf
  • Data Science for Petroleum Engineering - Part 5: "Transforming Excel well raw data into datasets.​". (18 August 2017) More Online  pdf
  • Data Science for Petroleum Engineering - Part 5.1: Data Introspection with R. (17 August 2017) More Online
  • Data Science for Petroleum Production Engineering 3: Anonymizing Well Data. (4 August 2017) More Online
  • Growing your petroleum engineering library: calling FORTRAN from R. (21 July 2017) More Online
  • Multiple VLP correlations on well segments. (12 July 2017) More Online
  • Building your own petroleum engineering library with "R": humble beginnings with the compressibility factor 'z'. (3 July 2017) More Online
  • "R" and the search of the ideal language for petroleum engineering. (21 April 2017) More Online

2016

  • Data Science for Petroleum Production Engineering. Part 2: Acquiring the data. (16 April 2016) More Online
  • Data Science for Petroleum Production Engineering. (14 April 2016) More Online
  • Cloudy with no chance of rain. (27 March 2016) More Online