Module 1: (Day 1 & 2)

Installing Anaconda Python & Packages

Introduction to Anaconda & Software Packs

Introduction to Python & Why Python?

Basics Expressions in Python

Variables and Data Types

Sequences in Python (List, Tuple, Set, Dictionary)

Simple Plot with Matplotlib

Inflow Performance Example

Module 2: (Day 3 & 4)

More on Sequences

Programming (For and While loops)

Integrated If Statements and Loops (including break, continue)

Introduction to Python Function (def keyword)

Recovery Factor Example (Guthrie Corr.)

A PVT Example

Exporting Plots

Exporting Calculation Results to Excel

Module 3: (Day 5 & 6)

Introduction to Pandas

Reading Tabulated Data & Excel Sheets

Historical Data Plotting

Introduction to JupyterLab

Plotting with Plotly Express

Liquid Loading Example (Turner's Rate)

Chan Plot Diagnostic (with Polynomial Regression)

Basic Matplotlib Figure Configurations

Polynomial Fitting Using Numpy

Module 4: (Day 7 & 8)

Introduction to Matplotlib 2D Surface Mapping

Contour Plots and its Variants in Python

Oil Field Formation Depth Mapping Example

Water Oil Contact 3D Mapping

Data Averaging Techniques (utilizing Oil Production and WHP)

Working with Las Files and Well Logs using Lasio

Module 5: (Day 9 & 10)

Introduction to Plotly Configuration

Plotly Subplots

Introduction to Sankey Charts

Production Back Allocation Example

Creating Well and Separator Networks Visuals

Introduction to Two-Phase/Multiphase Flow Package (psapy)

Prediction of BHP using Beggs and Brill

Module 6: (Day 11 & 12)

Introduction to Flow Mapping using Fluids Package

Multivariate Scatter Coloring and Symbol Setup

Flow Stability Advisor Example

NORSOK M-506 Corrosion Monitoring Example

Reading OLGA Trend Plots using Pyfas

Introduction to Dashboarding

Working With Streamlit

Module 7: (Day 13 & 14)

Creating Nodal Analysis Dashboard

Historical Production Data Dashboard

Recreating a PVT Calculator using Dashboards

Working with DCA (Simple Time-Rate Solution)

Module 8: (Day 15 & 16)

Introduction to Object Oriented Python

Producing Clean Code & Maintenance/Refactoring Tips

Introduction to Machine Learning

Data Shaping and Normalization

Training Testing Split

Regressions and Output Prediction

Classification Problems with Machine Learning

Creating Production Prediction using ML

Multivariate Regression