COURSE OVERVIEW

This intensive 10+ hours training is designed to bridge petroleum engineering fundamentals with modern computational techniques. Participants will gain hands-on exposure to Python programming, machine learning workflows, and practical applications in production engineering-ranging from inflow-outflow modelling to nodal analysis and flow assurance.

Prerequisites

No prior advanced knowledge required. Basic exposure to petroleum engineering or programming is helpful but not mandatory this course caters to both new learners and experienced professionals.

Course Contents

·        Python for Oil and Gas Applications

·        Machine Learning for Production Data

·        Production Analysis &Nodal Analysis

·        Flow Assurance & Applications

Learning Objectives in Terms of Career

·        Boost Employability

·        Advance Career Roles

·        Industry-Relevant Skills

·        Advance Career Roles

·        Future-Proof Expertise

FREQUENTLY ASKED QUESTIONS

Who can attend this training?

Petroleum engineers, production engineers, reservoir engineers, data scientists in oil & gas, and students aspiring to enter the energy sector.

Do I need prior Python knowledge?

No, the training starts from basics and builds up to advanced oil & gas applications.

Is this training hands-on or only theory?

The course is designed with 50% practical sessions, including group exercises and case studies.

Will real oil & gas datasets be used?

Yes, participants will work with real-world production datasets for practice.

What software/tools are required?

Python (Anaconda/Spyder/Jupyter), libraries like Pandas, NumPy, Scikit-learn, and Matplotlib. Installation guidance will be provided.

Will I get course material and codes?

Yes, participants receive datasets, Python scripts, and learning resources for future use.