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Hi šŸ‘‹, I am RODERICK Perez

Welcome to my geo{DataScience} Repository

avataaars

Seismic interpreter, with more than 15 years of experience in the Oil & Gas industry. Specialized in the characterization of unconventional reservoirs in the USA and Colombia. Expert in pre- and post-stack seismic inversion, as well as in the application of Machine Learning and Neural Networks in the analysis of geoscientific data.

Throughout his career he has worked for Anadarko Petroleum, Noble Energy, DrillingInfo, Pacific Rubiales. He currently serves as the President of ScientiaGROUP.

  • šŸ”Ø Iā€™m currently working on:
    • Webinars & Courses:
      • Python šŸ Programming for Geoscience
      • Machine Learning for Mineral and Hydrocarbon Exploration šŸ¤–
      • Deep Learning for Oil and Gas Exploration
  • šŸ’¬ Ask me about: Geology, Geophysics, Python, Blockchain Machine Learning and Deep Learning
  • šŸ“« How to reach me: https://www.linkedin.com/in/roderickperezaltamar/

Roderick Perez's Projects

code icon code

Compilation of R and Python programming codes

data icon data

Data Sets for Machine Learning Practice

dca_using_rnn icon dca_using_rnn

Automatic Decline Curve Analysis Using a Deep RNN (Recurrent Neural Network).

dcawithets icon dcawithets

Sandbox to do a Decline Curve Analysis method (A method to forecast production and calculate Remaining Reserves (RR) and Estimated Ultimate Recovery (EUR) with Error-Trend-Seasonality (ETS) Method

geodatascience icon geodatascience

Application of Machine Learning and Deep Neural Networks in Geology, Geophysics and Petroleum Engineers

ml_well_log icon ml_well_log

The code describes how unsupervised ML can be applied to well log data for efficient clustering. A part of the well log data is provided.

peg_python icon peg_python

Petroleum Engineering and Geosciences exercises in Python

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