Learn Energy Data Analytics From Scratch

Practical application based Oriented Training for Energy Professionals
(Edvantage Learning in Collaboration with Petroleum From Scratch)
Duration: 6 Weeks
  • Flexible & blended learning model
  • Discussion Forum
  • Hands on experience on Oil & Gas Projects
  • No Prior coding experience
  • Certificate of Completion
Statistics
Python Fundamental
Data Analytics for Oil & Gas
Machine Learning
Data Science & Machine Learning Projects for Energy Industry

Material Balance for Gas Cap Reservoirs

Klinkenberg Effect

IPR Curve

Pressure Profiling

Skin Effect

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 200k recent petroleum graduates 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 a recent report, by 2025, the need for data science and machine learning capabilities is predicted to fuel a 27.9% increase in employment.

Data Analytics Research Projects

  • Comparison between Vogel's and Fetkovich's Model for IPR
  • Future IPR
  • MBAL Oil
  • The Klinkenberg Effect
  • Well Test
  • Effect of Skin on Bottom Hole Pressure
  • Gas Material Balance
  • Spinner Log Analysis
  • Vogel's IPR
  • 1D Pressure Diffusion Numerical Solution

Faculties

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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.

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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.

Tools & Languages

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Ready To Become Energy Data Scientist

Learn Energy Data Analytics From Scratch

Practical application based Oriented Training for Energy Professionals
(Edvantage Learning in Collaboration with Petroleum From Scratch)
Duration: 6 Weeks
  • Flexible & blended learning model
  • Discussion Forum
  • Hands on experience on Oil & Gas Projects
  • No Prior coding experience
  • Certificate of Completion

Python Fundamental (by pressure, production and reservoir data)

  • Module 1- Introduction to Python and Computer Programming Python
    1. Python - a tool, not a reptile
    2. There is more than one Python
    3. Let's start our Python adventure
  • Module 2 - Data Types, Variables, Basic Input-Output Operations, Basic Operators
    1. Your first program
    2. Python literals
    3. Operators - data manipulation tools
    4. Variables - data-shaped boxes
    5. How to talk to computer?
  • Module 3 - Boolean Values, Conditional Execution, Loops, Lists and List Processing, Logical and Bitwise Operations
    1. Making decisions in Python
    2. Python's loops
    3. Logic and bit operations in Python
    4. Lists - collections of data
    5. Sorting simple lists - the bubble sort algorithm
    6. Lists - some more details
    7. Lists in advanced applications
  • Module 4 - Functions, Tuples, Dictionaries, and Data Processing
    1. Writing functions in Python
    2. How functions communicate with their environment?
    3. Returning a result from a function
    4. Scopes in Python
    5. Let's make some fun... sorry, functions
    6. Tuples and dictionaries
  • Module 5 - Modules, Packages, String and List Methods, and Exceptions
    1. Using modules
    2. Some useful modules
    3. What is package?
    4. Errors - the programmer's daily bread
    5. The anatomy of exception
    6. Four simple programs

Data Analytics for Oil & Gas

  • Effective computations with Numpy:
    1. Numpy Introduction
    2. Numpy Arrays
    3. Arrays Dimension and Shape
    4. Arange and Linspace
    5. Zeroes, Ones, and Identity
    6. Array Indexing
    7. Array Slicing Arrays
    8. Indexing Higher Dimensional Arrays
    9. Application of array slicing in Machine Learning
    10. Array Reshape
    11. Data Distributions
    12. Random Number Generation
    13. Numpy Functions
  • Data Manipulation with Pandas: Dataframe, csv, excel etc.
  • Oil and Gas Projects
  • 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
  • Plotting and Visualization with matplotlib
  • Brief introduction of Jupiter Notebook and python programming
  • Introduction of data analytics application in upstream
  • Easily create high-quality visualisation of petroleum problems

Stats and ML (Introduction with Oil and Energy Context)

  • Data Statistics
  • Exploratory data analysis
  • Distributions
  • Introduction to Artificial Intelligence and Machine Learning

Feedback From Trainees

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Ayush Gandhi
B. TECH (Petroleum Engineering) Pandit Deendayal Energy University

I, Ayush Gandhi, would like to provide feedback on the "Data Science and Its Application in Oil and Gas" course. The team of "Edvantage" approached the course. It has been a wonderful course thus far, and it will continue to be so throughout the journey. The training is focused on oil and gas and is very practical. If somebody wants to start their career in data science in the oil and gas industry, I would recommend this course. To provide aid, the entire team assists and coordinates. They also provide interview support, which indirectly aids in the customization of the CV. The entire staff is enthusiastic about assisting with the project.

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Sahil Vora
B. TECH (Petroleum Engineering) Pandit Deendayal Energy University

I, Sahil Vora, would like to share feedback on the course "DATA SCIENCE AND ITS APPLICATION IN OIL AND GAS". Overall, the course has been very comprehensive and easy to understand so far. The instructors made sure that they are giving the information in a way that won't make me confused. This course is designed such a way that we can do hands-on practice of data science project using python. I loved this course; it was very objective and direct. I'm sure it will be very useful in my life as a student and as a professional. Thank you so much for this great course.

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M Faiz Nurrohman

Hi, my name M Faiz Nurrohman, i would like to share feedback on the course "Data Science and Its Application in Oil and Gas". Overall, the explanation from the speaker is very easy to understand. And in this course, we can ask questions if we still don't under stand the material given. We are also given questions to test our abilities so that we can implement the material that has been given. And I'm sure this course will be useful for me in the future.

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Anas Babai
Geoscience Lecturer in University of Bahri & +3 working experience in oil Industry & Ph.D. scholar

My Name is Anas Babai I would like to share my feedback on the course" Data Science and its applications on oil and gas”, I was looking toward such course since it matches my career orienta tion. The course content was designed to cover almost most aspects of data science, and the way things were explained was very simple making it easy to understand even for those who don't have data science experience, starting form covering most used Python libraries, SQL database and projects. I believe this course will put anyone in the right track toward mastering data science and ML. I highly recommend this course to everyone. My deepest gratitude to Edvantage for organizing this course.

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Hojatollah Gholami
PhD Candidate at University of Sistan & Baluchistan

I, Hojatollah Gholami, would like to share feedback on the course "DATA SCIENCE AND ITS APPLICATION IN OIL AND GAS". Over all, the course has been very comprehensive and understandable so far. The instructors provide useful information about this course and make sure that students receive it well. Online class room management is well done, and the courses learning ap proved with exercises and support. This course is designed so that we can practically do a data science project using Python. I like this course and find it useful; it was very objective and direct. I am sure it will be very useful in my life as a professional. Thank you so much for this great course.

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Muhammad Yunus

Hello! I am Muhammad Yunus from Indonesia. Joining in "Data Science and Its Application in Oil and Gas" is a great choice for me as a person who want to be professional in data science. All the instructors are friendly and smart. They know well how to stimulate a comprehensive understanding to the entire audiences and deliver it in easy way to be understood even for people who have a different background and zero experience in data science application. In addition, every class is full filled by many practical things so that the new knowledge is directly applicated. Thanks!

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Fakhrur Novianto
Bachelor of Engineering - BE, Teknik Geology/Geophysical, Universitas Pembangunan Nasional Veteran Yogyakarta.

Hi, I’m Fakhrur Novianto, would like to share feedback on the course "DATA SCIENCE AND ITS APPLICATION IN OIL AND GAS". The lessons delivered are very clear and easy to understand for me, besides that the teacher provides interesting case studies in the application of the formulas used in data analysis. The instruc tor always asks us about the participants' understanding of each material presented, which is good so that participants can relate and apply it to more complex issues. Interactive learning is very helpful for us in solving problems in writing program code. Assignments given to participants make participants more sensitive and accustomed to practicing what they have learned, and the opportunity to ask questions about the assignments given in the fol lowing week is a good thing so that participants can confirm their understanding of the tasks given. Thank you.

FAQ's

Why should I join your data science programme when there are so many others?

There are other platforms that teach data science, but we are the only institute that offers accredited application-based data science training in the oil and gas industry.

What if I don't have any prior coding experience? Can I still join this course

Don't worry, we'll start from scratch. There is no requirement for prior experience.

Will joining this program be beneficial to me because I am proficient in Python?

This might help you readily comprehend the data science ideas underpinning oil and gas applications. You will receive many data sets for practise and analysis.

What’s the fee for the program?

INR 15000 or 200 USD

Will I get a certificate?

Yes, you will receive a 6-week training certificate upon completion of the programme.

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 23rd of July 2022