Machine Learning,Supervised Learning

Machine Learning in Oil & Gas

Level: Basic Grades: In College
Machine Learning,Supervised Learning
45 Hours of LIVE instruction
Weekend and Weekdays
49500.00 55000.00
10% off
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Course Overview

This course is focused on strengthening the basics of the student in data science language and their application in reservoir and well trajectory. The student will gain hands-on experience by working on regression and classification models and will learn the application of techniques like PCA and XGBoost.

Topics Covered

  • What is Machine Learning
  • Creating a Machine Learning Model
  • Feature Engineering
  • Working with well logs in Python

Course Curriculam

  • Material Balance in Python
  • Vogels Equation
  • Reservoir Modeling
  • Deviated Well Trajectory Calculation and Plotting

  • What is Machine Learning
  • Digitalization in O&G Industry
  • How Machine Learning will impact O&G Industry
  • Future of Data Scientist in O&G Industry

  • Getting Started
  • Importing the Libraries
  • Importing the Dataset
  • Taking care of Missing Data
  • Encoding Categorical Data
  • Splitting the dataset into the Training set and Test set
  • Feature Scaling
  • Mini Project

  • Simple Linear Regression
  • Multiple Linear Regression
  • Polynomial Regression
  • Support Vector Regression
  • Decision Tree Regression
  • Random Forest Regression
  • Evaluating Regression Models Performance
  • Regression Model Selection
  • Hyperparameter tuning
  • Mini Project

  • Logistic Regression
  • K-Nearest Neighbors (K-NN)
  • Support Vector Machine
  • Kernel SVM
  • Naïve Bayes
  • Decision Tree Classification
  • Mini Project
  • Random Forest Classification
  • Classification Model Selection
  • Evaluating Classification Model
  • Hyperparameter tuning
  • Mini Project

  • Logistic Regression
  • K-Nearest Neighbors (K-NN)
  • Support Vector Machine
  • Kernel SVM
  • Naïve Bayes
  • Decision Tree Classification
  • Mini Project
  • Random Forest Classification
  • Classification Model Selection
  • Evaluating Classification Model
  • Hyperparameter tuning
  • Mini Project

  • Supervised Clustering
  • Unsupervised Clustering
  • Mini Project

  • Principal Component Analysis (PCA)
  • Linear Discriminant Analysis (LDA)
  • Kernel PCA
  • Mini Project

  • Model Selection
  • XGBoost
  • CatBoost
  • Mini Project

Pick a batch

Python Numpy and Pandas Exploratory Data Analysis

Projects you will build

Data Driven Sonic Well Log Model

Machine-learning techniques to predict DTC and DTS logs to improve subsurface characterization.

Artificial Intelligence
Data Driven Sonic Well Log Model
Supervised Learning, Classification

Learn Effectively with our Industry Focused Approach

Petrocoder runs most specialised courses in oil & energy sector developed by industry specialists after several decades of experience.

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+91-120-6838899
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