ML and Data Analytics for Petroleum
Learn how to use Machine Learning and Data Analytics in the Oil and Petroleum Industry
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About this course
Contributors & Instructors
What you will learn?
Course Content
1. Introduction
5
About this Course
Newton Raphson Method
The Klinkenberg Effect
Nodal Analysis with Python
Well Testing Web App Demo
2. Numpy for Petroleum Engineering
8
Introduction to Numpy
Array Dimensions and Shape
Generating Numpy Arrays with In-built Methods
Array Indexing
Array Slicing
Reshaping Arrays
Random Number Generation Using Numpy
Numpy Functions
3. Pandas for Petroleum Engineering
9
Introduction to Pandas
Data Structures in Pandas
Reading CSV Data into Pandas
Reading Data from HTML
About Volve Field Production Data
Basic Pandas Functions
Descriptive Statistics Using Pandas
Indexing and Accessing Columns
Volve Field Data EDA
4. Projects
4
Analyzing Well Log Data
Darcy's Law for Reservoir Pressure Profiling
Interactive GUI for Dynamic Pressure Profiling
Frontal Displacement App
5. Visualization for Petroleum Engineering
2
Relative Permeability Plot
Univariate and Bivariate Plotting
