Artificial Intelligence,Machine Learning,Feature Engineering

Upstream Data Science Specialist

Level: Advance Grades: Finished College
Artificial Intelligence,Machine Learning,Feature Engineering
200 Hours of LIVE instruction
Weekdays
180000.00 200000.00
10% off
Enrol Now

Course Overview 5/5

Upstream Data Science Specialist course is focused on building strong concepts in and around python and its libraries, with a focus on the application of these concepts in multiple subdomains of Upstream. We have a strong focus on building concepts and developing a practical approach by incorporating several industry use cases from the industry.

Topics Covered

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

Course Curriculam

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

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

  • 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

  • Supervised Clustering
  • Unsupervised Clustering
  • Mini Project

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

  • 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

  • Model Selection
  • XGBoost
  • CatBoost
  • Mini Project

  • ML in Artificial Lift
  • ML in SRP
  • Physics based model for SRP in Python
  • Wave Modeling for downhole dynacard from surface data
  • Calculate fillage from DDC using python
  • Torque Analysis in Python
  • Stress Analysis in Python
  • 3D Visualization of wave propagation
  • Image Classification Model for DDC
  • Feature Extraction from DDC
  • Feature Engineering
  • Classification Models
  • CNN, ANN, Transfer Learning
  • Time Series Modeling for predictive maintenance
  •  

  • Getting Data (Volve Dataset)
  • Data Visualization
  • Exploratory Data Analysis
  • Feature Engineering
  • Outlier Detection
  • Filling NaN values
  • Flagging Bad Hole (based on logs)
  • Predicting DTC, DTS log
  • Predicting Geomechanical Logs
  • Supervised Facies Classification
  • Unsupervised Facies Classification

Pick a batch

Session 1:1st Jan Thursday
07:00 - 08:00PM
Session 2:1st Jan Thursday
07:00 - 08:00PM
Python Numpy and Pandas OpenCV Exploratory Data Analysis Feature Engineering Supervised Learning

Projects you will build

Supervised Lithology Classification

Using AI/ML tools to identify facies

Artificial Intelligence
Supervised Lithology Classification
EDA, Feature Engineering, Volve Dataset

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.

Email us at

[email protected]
Call us at

+91-120-6838899
Request a call back!

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