Data Science and Its Applications in Oil and Gas

Duration: 3 Months
  • Certificate From Persian Gulf University
  • Dedicated Internship/Placement/Project Support
  • Training Under World Class Data Science Trainers
  • Learn Data Science From Scratch
First 20 Participants will get a free recorded training on Python and its application in Oil & Gas
Certificate from Persian Gulf University
Flexible & blended learning model
Discussion Forum
Hands on experience on Oil & Gas Projects
No Prior coding experience
Internship/Placement opportunities

Get Opportunities In


Why to Learn Data Science in Oil & Gas?

  • Continuous job Cuts and lack of job opportunities in Oil & Gas sector
  • Increasing Opportunities in Oil & Gas Companies
  • To increase work efficiency by using data science application
  • Attractive Salary for Entry/Experienced Level Engineers

Application of Data Science in Oil & Gas

  • Analyzing seismic and micro-seismic data
  • Improving reservoir characterization and simulation
  • Reducing drilling time and increasing drilling safety
  • Improved petrochemical asset management
  • Optimization of the performance of production pump
  • Improved shipping and transportation

Current Updates Of Data Science In Oil & Gas

  • More than 400,000 oil and gas sector jobs have been cut this year, according to Rystad
  • Over more than 200k recently petroleum graduated are looking for job
  • ~53% of workforce concerned about job security
  • Less than 15% of OG&C employees are data analytics/mathematic majors

As per the recent Report by 2025 the demand of data science & Machine skills is expected to drive 27.9% increment in employment

AI & ML Research Project

  • Geosciences: Facies classification or well log prediction
  • Reservoir: PVT estimation
  • Drilling: ROP estimation
  • Completion: Fracture characterisation
  • Production: Liquid loading detection

Data Science Research Projects

  • Well Test Analysis
  • Reservoir Simulation (1D) from scratch
  • Well Log Visualization and High Level Interpretation
  • Thermal Stimulation concept using Darcy's law in Python
  • 2 Phase Rel Perm Models - Hands on Simple Data Visualization
  • Klinkenberg Effect
  • MBAL
  • Effect of Skin on BHP
  • Compaeison b/w Vogels and Fetkovich IPR models



Mehdi is a data-driven Lead Petro physicist and Reservoir Geomechanics specialist with 16 years of experience in monitoring, processing, and interpretation of open hole, cased hole, and advanced log (FMI, SONIC SCANNER, DSI, NMR...) with leading and cooperating in 22 MDP, FDP, and FFS in Iran, Oman, Turkey, Malaysia, and Austria.


Divyanshu has a background in data science and is a well-known figure in the oil and gas industry for data science. He has worked on a variety of full-scale and mini-scale projects utilizing Python and its packages, spanning from basic reservoir engineering concepts to drilling engineering concepts to oil production engineering and numerical simulations. He regularly maintains a GitHub Repository for Oil and Gas Data Analysis as well as Machine-Learning and Deep-Learning, in order to assist and mentor the community with everything he learns.


14 years of expertise with Java/J2EE/C++/Python technologies in comprehensive software development processes. Algorithms, Database Management, and Data Mining are post-graduate specialisations for Computer Science Engineers. Using Agile approaches, designed many software solutions to drive continuous improvement in processes, systems, workflow, and customer response. On hundreds of application development projects, I've worked as a project manager, client coordinator, lead developer, and/or team member.


Jaiyesh is a highly qualified and skilled Data Scientist with very good experience in Engineering Mathematics - Univariate and Multivariate Calculus, Reservoir Engineering, Production Engineering, Numerical Simulations, Oil and Gas Physics Statistics, Linear Algebra (Intuitive to Applied), ML-Algorithms, Deep Learning, Time Series Analysis, Predictive Maintenance, and Predictive Analysis.


Ishan graduated from the Indian Institute of Technology in Dhanbad with a degree in petroleum engineering. With an MBA from Indian School of Business, Hyderabad, he has also added a business management dimension to his resume. Ishan has close to 12 years of experience as a Production Technology/Engineer in the Upstream sector of the Oil & Gas Industry and domain expertise. He has a strong background in petroleum fiscal and economics, as well as digital in upstream production.

Tools & Languages


Course Journey

  • Statistics
  • Database Management
  • Data Mining Application
  • Deep Learning with TensorFlow and Keras
  • Python Fundamental
  • Data Analytics
  • Machine Learning
  • Data Science & Machine Learning Projects

Ready To Become Energy Data Scientist

Data Science and Its Applications in Oil and Gas

Duration: 3 Months
  • Certificate From Persian Gulf University
  • Dedicated Internship/Placement/Project Support
  • Training Under World Class Data Science Trainers
  • Learn Data Science From Scratch

Get Opportunities In

... ... ... ... ... ...


  • Sample or Population Data?
  • The Fundamentals of Descriptive Statistics
  • Measures of Central Tendency, Asymmetry, and Variability Lesson
  • Practical Example: Descriptive Statistics
  • Distributions
  • Estimators and Estimates
  • Practical Example: Inferential Statistics
  • Hypothesis Testing: Introduction
  • Hypothesis Testing: Let’s Start Testing!
  • Practical Example: Hypothesis Testing
  • The Fundamentals of Regression Analysis

Python Fundamental (by pressure, production and reservoir data)

  • Module 1 - Introduction to Python and Computer Programming
  • Module 2 - Data Types, Variables, Basic Input-Output Operations, Basic Operators
  • Module 3 - Boolean Values, Conditional Execution, Loops, Lists and List Processing, Logical and Bitwise Operations
  • Module 4 - Functions, Tuples, Dictionaries, and Data Processing
  • Module 5 - Modules, Packages, String and List Methods, and Exceptions

Database Management

  • Introduction to SQL
  • Introduction to Databases and RDMBS
  • Install a Database Engine
  • SQL Syntax
  • SQL Data Types
  • SQL Operators
  • SQL Expressions
  • SQL Comments

Data Analytics (Python and Power BI)

  • Brief introduction of PowerBI application in Data analytics
  • Confidently use Python to solve different RESERVOIR parameters such as, porosity, water saturation evaluation in sandstone and carbonate reservoirs, different approach in shale evaluation, logs relationship, and representing various cross plot such as Pickett plot.
  • Easily create high-quality visualisation of different well data such as NPHI, GR, RHOB, DT…to simplify the data analysis and get ready-to- apply plots for visualization by python or powerBI

Data Mining Application

  • Data Mining description and introduction all steps in CRISP-DM
  • SPSS application in Data (wells) Mining
  • Python application in Data (wells) mining
  • Reservoir characterization Understanding; Formation evaluation role in FFS
  • Data Understanding by Python; well logs, core data, cutting description, geological data….
  • Data Preparation by Python and SPSS; data cleaning, missing data handling, new data construction, and Integration well log data
  • Modelling; Selecting Modeling Techniques, generating a Test Design, Building the Models and Assessing the Model
  • Selecting the proper ML approaches to solve a particular problem in petrophysics; depending on the type of the challenges, data availability, data quality and solution requirements
  • Porosity estimation by log data by using Linear, Multi and polynomial Regression, Decision Tree, ANN
  • Well log construction such as CGR, DT and RHOB in bad hole intervals by using different ML approaches
  • Recognition Pay Zone from Non-Pay Zone by Classification approaches such as Decision Tree, Logistic Regression
  • Evaluation and Interpretation; evaluation different result such as Porosity estimation, Facies analysis

Machine Learning

  • Introduction to Artificial Intelligence and Machine Learning
  • Well Data Preprocessing
  • Supervised Learning in reservoir parameters estimation such as water saturation and compressibility factor
  • Feature Engineering for porosity estimation
  • Supervised Learning-Classification
  • Unsupervised Learning, in facies analysis
  • Time Series Modelling
  • Ensemble Learning in net/pey zone detection
  • Recommender Systems

Deep Learning with TensorFlow and Keras

  • AI and Deep Learning Introduction
  • Artificial Neural Network and reservoir parameters estimation
  • Deep Neural Network and Tools in permeability analysis
  • Deep Neural Net Optimization, Tuning, and Interpretability
  • Convolutional Neural Net (CNN)
  • Recurrent Neural Networks
  • Autoencoders

Schedule a call


There are lot of programs on data science why to join your program?

There are lot of platform who teach data science but we are the only institute who provide certified application based data science training in Oil & Gas.

I don’t have prior coding ? So can I join this program?

No worries we will start it from scratch. You don’t need any prior experience.

Will it be helpful for me if I Join this program as I have good knowledge of Python?

Well good this can help you to understand the data science concepts behind oil and gas application easily. You will get different data sets for practice and analysis.

What’s the fee for the program?

INR 22500 or 300 dollars

Will I get a certificate?

Yes you will get 3 months certificate from Persian Gulf university after the completion of the program.

What will be the timing?

Classes will be on evening probably 5 hours at weekends.

What if I miss classes?

No worries we’ll provide you recorded video along with necessary material.

Will there be an assignment?

Yes, we’ll have assignment on weekly basis and final project at end of the program.

Who can join this course?

Undergraduate/Graduate or professional working in energy sector.

When the program will start?

Program is likely to start from 16th of April 2022