top of page
Search

Study of Well Segmentation by using Self Organizing Maps (Kohonen Maps) in an Unsupervised ML mode

  • Writer: dromero
    dromero
  • Feb 14, 2019
  • 1 min read

Updated: Mar 18, 2019

This type of analysis could benefit engineers looking at possibly 1000’s of wells in their field when finding right candidates for workover or re-stimulation is needed.



The Self-Organizing Maps (SOM) model is a special class of Artificial Neural Networks, which is based on competitive learning.
A display of a feature showing a few clusters of affinity


Welcome to my blog post. I am sharing in this post a publication from my LinkedIn page submitted just a few years ago. Here is the link to the article https://www.linkedin.com/pulse/study-well-segmentation-using-self-organizing-maps-ml-dario-h-/ Enjoy it!


Finding similarities within your Asset

“A Self-Organizing Map is used extensively in market analysis, health care, banking and since a few years ago by the major Oil & Gas services companies in supporting reservoir studies, production optimization patterns, etc. .”

A Guide for Success

“Dividing the producing field (sample of wells) on the basis of some significant features will facilitate quick characterization.”
 
 
 

Comentarios


© 2019 by DNNAI. Proudly created with Wix.com

  • Facebook Black Round
  • Google+ - Black Circle
  • Twitter Black Round
bottom of page