| Code | Date | Time | Duration | Location | Currency | Team of 10 Per Person | Team of 7 Per Person | Early Bird Fee Per Person | Normal Fee Per Person |
|---|---|---|---|---|---|---|---|---|---|
| PPE25 | 21 - 25 Jul 2025 | 8 PM Indian Time |
3 Hours Per Day
|
Zoom Online
|
USD
|
750
|
850
|
1000
|
1250
|
The Classes Will be from Monday to Friday Via Zoom Online.
Boost your team's skills and your budget! Enjoy group discounts for collaborative learning. Send an inquiry to info@peassociations.com.
Python-Powered Petroleum Economics: From Forecasting to Risk Analysis
Join our 5-day intensive course to master petroleum economics using Python. Learn production forecasting, financial modeling, uncertainty analysis, and interactive dashboards with Streamlit. Perfect for professionals aiming to enhance project evaluation and decision-making.
Description
This comprehensive 5-day training program equips participants with the skills to leverage Python for petroleum economics. From production forecasting and revenue estimation to advanced Monte Carlo simulations, participants will gain hands-on experience in building robust financial models, visualizing key metrics, and analyzing risks. The course covers critical concepts like Time Value of Money, NPV, IRR, and sensitivity analysis, culminating in the creation of interactive dashboards using Streamlit. Designed for professionals in the energy sector, this course blends practical Python programming with real-world petroleum economics applications.
Demo Class
In the fast-evolving energy industry, data-driven decision-making is paramount. This Python-Powered Petroleum Economics course bridges the gap between programming and financial analysis, enabling participants to tackle complex economic evaluations with confidence. Over five days, you will learn to handle datasets, perform business calculations, visualize performance indicators, and assess project risks using Python. Whether you're forecasting production, calculating cash flows, or evaluating uncertainties, this course provides the tools and techniques to excel in petroleum project economics.
- Master Python for data handling, financial modeling, and visualization in petroleum economics.
- Understand and apply production forecasting, revenue estimation, and cost calculations.
- Learn to compute key financial metrics like NPV, IRR, and undiscounted cash flow.
- Explore depreciation methods (Straight-Line and Declining Balance) and their impact on project economics.
- Conduct sensitivity and scenario analyses to identify key economic drivers.
- Perform Monte Carlo simulations for probabilistic risk assessment.
- Build interactive dashboards using Streamlit to visualize financial outcomes dynamically.
The course employs a hands-on, interactive approach, combining theoretical explanations with practical Python exercises. Participants will work with real-world datasets, write Python code for financial calculations, and create visualizations using libraries like pandas, matplotlib, and plotly. Daily activities include coding sessions, group discussions, and case studies tailored to petroleum economics. The course culminates in building a Streamlit app for dynamic financial analysis, ensuring participants leave with tangible skills and deliverables.
- Improved decision-making through accurate financial models and risk assessments.
- Enhanced project evaluation capabilities, leading to better investment outcomes.
- Increased efficiency in data analysis and reporting with Python automation.
- Strengthened team capacity to handle complex economic evaluations.
- Adoption of modern tools like Streamlit for dynamic, data-driven presentations.
- Enhanced ability to analyze and interpret complex economic data using Python.
- Improved proficiency in financial modeling and risk assessment for petroleum projects.
- Practical experience in creating interactive dashboards for stakeholder presentations.
- Increased confidence in applying Python to real-world business challenges.
- Valuable skills in data visualization and probabilistic forecasting, boosting career prospects.
This course is ideal for:
- Petroleum engineers and reservoir engineers seeking to enhance economic evaluation skills.
- Financial analysts and economists in the energy sector.
- Project managers and decision-makers involved in upstream oil and gas projects.
- Data analysts and scientists looking to apply Python in petroleum economics.
- Professionals with basic Python knowledge aiming to specialize in financial modeling.
Day 1: Production Forecasting and Revenue Estimation
- Introduction to dataset (Excel): Year, Production Potential
- Python essentials: Reading Excel with pandas, user inputs
- Business calculations: Deferment %, Yearly Production, Yearly Revenue
- Formatting output: Rounding, exporting to Excel
- Visualization: Green bar chart (Production Potential), Blue bar chart (Yearly Revenue)
Day 2: Capex, Opex, Depreciation, Royalty, Tax & Undiscounted Cash Flow
- Recap of revenue calculations
- Capex and Opex modeling
- Depreciation: Straight-Line and Declining Balance methods
- Royalty and tax calculations
- Undiscounted Cash Flow (UCF) modeling
- Visualization and export to Excel
Day 3: Time Value of Money, NPV, IRR & Streamlit
- Time Value of Money: Present Value, Future Value
- Net Present Value (NPV) and Internal Rate of Return (IRR) calculations
- Introduction to Streamlit: Building interactive web apps
- Demo: Streamlit app for dynamic NPV analysis
- Visualization of NPV at different discount rates
Day 4: Decision-Making Under Uncertainty & Sensitivity Analysis
- Uncertainty in petroleum projects: Production, Price, Capex, Opex, Tax
- Sensitivity analysis: One-variable and multi-variable
- Tornado Charts using matplotlib/plotly
- Scenario analysis: Base, Best, Worst Case
- Export tables and charts to Excel
Day 5: Monte Carlo Simulation for Risked Economic Evaluation
- Introduction to Monte Carlo Simulation
- Defining input distributions: Triangular, Normal, Uniform
- Running simulations for 1000+ NPV outcomes
- Visualizing results: Histogram, cumulative probability plots
- Extracting P10, P50, P90 and exporting results
On successful completion of this training course, PEA Certificate will be awarded to the delegates
Biswajit Choudhury is a Reservoir Engineer with about 40 years of experience in oil and gas industry. During his long career he has worked for Oil India Limited, BG Group, Shell International and Petroleum Development Oman. He was the technical authority in Reservoir Engineering function in Shell International and Petroleum Development Oman. Biswajit has presented several technical papers in international conferences and has 12 publications in international journals.
Currently as a Freelance Reservoir Engineering Consultant, he is associated with IMC Limited and Petroleum Engineering association (PEA). He delivers several technical courses both online and in face-to-face mode and is a guest faculty at IIT (ISM) Dhanbad and IIT (Madras). Biswajit has BS and MS degree in Petroleum Engineering from IIT (ISM) Dhanbad.
