Machine Learning Guide for Oil and Gas Using Python

Frac intensity classification example

The next example is to go over a classification problem and apply the discussed algorithms to solve the problem using the scikit-learn library. One of the applications of ML in the O&G is predicting hydraulic frac stages that are expected to be challenging to treat. In other words, if these stages can be flagged ahead of time prior to the frac start date, it will provide a lot of insight prior to the frac start date and it will eliminate surprises during frac jobs. This info can also be provided to the frac supervisor and consultant on site. In this exercise, the following input features are available per stage: measured depth in ft, resistivity in ohm-m, Young's modulus over Poisson's ratio (YM/PR in 10