Introduction to Python and Petroleum Data Analytics

By Prof. Archana | IIT(ISM) Dhanbad

Learners enrolled: 798 | Exam registration: 9

ABOUT THE COURSE:

Petroleum Data Analytics (PDA) is rapidly transforming the oil and gas industry through the integration of Artificial Intelligence (AI) and Machine Learning (ML). As we look ahead, it's evident that mastering these technologies will be pivotal for shaping the future of engineering disciplines, particularly in petroleum engineering.

This 12- week course aims to equip the next generation of petroleum professionals with essential foundations in PDA. While it's acknowledged that a single course cannot cover all aspects of becoming a PDA expert, it serves as a crucial starting point. Participants will gain a realistic understanding of AI and ML fundamentals as they apply to solving engineering challenges in the petroleum sector.

For engineering-domain experts, transitioning into skilled AI and ML practitioners is becoming increasingly important. The ability to harness data-driven insights through these technologies will not only optimize existing processes but also drive innovation in exploration, production, and operational efficiency within the industry.

Ultimately, this course serves as a catalyst for enthusiasts and professionals alike to grasp the transformative potential of PDA. It's a step towards unlocking the future where data-driven strategies and advanced analytics play a central role in shaping the trajectory of the oil and gas industry.

INTENDED AUDIENCE: Undergraduate, post graduate and PhD students’ professional practitioner in the discipline of Petroleum Engineering, Petroleum Refinery Engineering, Chemical Engineering

PREREQUISITES: Bachelor’s degree in any Engineering discipline

INDUSTRY SUPPORT: ONGC,OIL, ESSAR, IOCL, CAIRN, GAIL

Summary

Course Status :	Upcoming
Course Type :	Elective
Language for course content :	English
Duration :	12 weeks
Category :	Chemical Engineering Minor 2 in Chemical
Credit Points :	3
Level :	Undergraduate/Postgraduate
Start Date :	21 Jul 2025
End Date :	10 Oct 2025
Enrollment Ends :	28 Jul 2025
Exam Registration Ends :	15 Aug 2025
Exam Date :	02 Nov 2025 IST
NCrF Level	4.5 — 8.0

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Week 1:

Significance of Python and Petroleum Data Analysis
Introduction to Python and Programming Fundamentals: Environmental set up- Installation of Python and anaconda, Python packages, basics of data structures.

Week 2: Programming fundamentals:

Data types (Immutable & Mutable), Operator types, loops, functions, conditions, objects, and classes)

Week 3: Implementation of Python libraries:

Pandas: Environment set up, PANDAS –series, data frame, read CSV, cleaning data, correlations, lotting, panel, basic functionality, descriptive statistics, function application, iteration, and sorting.

Week 4: Implementation of Python libraries:

NUMPY: Introduction and environment set up, data types, array, indexing & slicing, binary operators, string functions, mathematical functions, arithmetic operations, statistical functions, sort, search & counting functions.
Plotting in Python: Installation of Matplotlib, Pyplot, plotting, markers, line, labels and title, grids, subplot, scatter, bar, histograms, pie-charts

Week 5: Data wrangling and preprocessing on reservoir/Unconventional resources data:

Understanding the concept of data wrangling using sub setting, filtering, and grouping, detecting outliers and handling missing values, concatenating, merging, and joining.

Week 6: Data wrangling and preprocessing on reservoir/Unconventional resources data:

Encoding categorical data, dataset splitting into test and training data, Feature scaling.

Week 7: Data manipulation:

Data cleaning, Data Preprocessing, Feature Engineering

Week 8: Algorithms and Application to Petroleum Data:

Supervised Learning

Week 9: Algorithms and Application to Petroleum Data:

Unsupervised Learning

Week 10: Regression for Petroleum Engineering Applications:

Linear regression, multiple linear regression used for regression and classification

Week 11: Regression for Petroleum Engineering Applications:

Logistics regression and decision tree for regression and classification.

Week 12: Regression for Petroleum Engineering Applications:

KNN used for regression and classification. Overfitting and under fitting.

Books and references

Python for Everybody: Exploring Data in Python By Dr Charles R. Severance., ASIN ‏ :‎ 9352136276, Publisher ‏ : ‎ Shroff Publishers; First edition (10 October 2017), Language ‏ : ‎ English, ISBN-10 ‏ : ‎ 9789352136278, ISBN-13 ‏ : ‎ 978-9352136278, Country of Origin ‏ : ‎ India
Machine Learning for Subsurface Characterization 1st Edition, Kindle Edition by Siddharth Misra, Hao Li, Jiabo He, ASIN ‏ : ‎ B07Z5YPHST, Publisher ‏ : ‎ Gulf Professional Publishing; 1st edition (12 October 2019), Language ‏ : ‎ English
Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences by Srikanta Mishra , Akhil Datta-Gupta, ASIN ‏ : ‎ B076HLT4CX, Publisher ‏ : ‎ Elsevier; 1st edition (27 October 2017), Language ‏ : ‎ English
Python Data Science Handbook: Essential Tools for Working with Data by Jake VanderPlas , ASIN‏ : ‎ B01N2JT3ST, Publisher ‏ : ‎ O'Reilly Media; 1st edition (21 November 2016), Language ‏ : ‎ English, Page numbers source ISBN ‏ : ‎ 1491912057
Machine Learning Paperback – 1 July 2017 by Tom M. Mitchell (Author), Publisher ‏ : ‎ McGraw Hill Education; First edition (1 July 2017), Language ‏ : ‎ English, ISBN-10 ‏ : ‎ 1259096955, ISBN-13 ‏ : ‎ 978-1259096952

Instructor bio

Prof. Archana

IIT(ISM) Dhanbad

Prof. Archana has over 17+ years of working experience in teaching, research and Software industry. I did my PhD from Department of Petroleum Engineering, IIT(ISM), Dhanbad, India, Dec 2018. MTech from and IIT Guwahati, India, May 2006 and B.Sc Engineering in Chemical Engg from BIT Sindri, Dhanbad India, July 2004. Currently I am working as Assistant Professor in Department of Petroleum Engineering in Indian Institute of Technology (Indian School of Mines), Dhanbad since 25th Oct 2010 till date. Before that I worked as a Project Engineer, Software Developer, System Tester, Team Lead, Business Analyst and Solution Delivery Analyst in Wipro Technologies, Bangalore from August 2006 till Oct 2010. I have taught the course “Introduction to Python and Petroleum Data Analytics” in academic year (2022-23) & (2023-24) in IIT(ISM), Dhanbad I have gone through the following certified trainings to have the good knowledge and understanding of the course:1.Certified 5-day (30 Hour) FDP on 'AI/ML Fundamentals and its Application in Oil and Gas Industry' organized by “The School of Petroleum Engineering in association with TCS-Research and AlgoAsylum, India, From 27.06.2022-01.07.2022 2.Certified ‘30-Hours Live online instructed-led training | Faculty Development Program’ on “Applied Machine Learning, AI & Its Applications using Python” organized by Eduxlabs, India from 1st June to 13th June 2021.3.Certified online training on “Artificial Intelligence (AI)” organized by MSME-Technology Development Centre (PPDC) duration 25.05.2020-29.05.2020 Certified online training on “Machine Learning & Data Analysis” organized by MSME-Technology Development Centre (PPDC)- duration 14.05.2020 to 17.05.2020

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.

The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).

Date and Time of Exams: November 02, 2025 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.

Registration url: Announcements will be made when the registration form is open for registrations.

The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.

Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

Please note that assignments encompass all types (including quizzes, programming tasks, and essay submissions) available in the specific week.

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Kharagpur .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team

SWAYAM Helpline / Support