Artificial Intelligence,Feature Engineering

Applying AI in Artificial Lifts

Level: Basic Grades: In College

Artificial Intelligence,Feature Engineering

50 Hours of LIVE instruction

Weekend and Weekdays

1:1 1:5

45000.00 50000.00

10% off

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Course Overview 5/5

This course aims at providing the student with the working knowledge of python and its libraries, at the same time enabling the student to have a strong command over the niche areas of the Upstream Sector. The application of AI-ML in artificial lifts provides crucial insight into the production operations of the field and the nuances associated with their operations.

Topics Covered

What is Machine Learning

Creating a Digital Twin

Creating a Machine Learning Model

Feature Engineering

Course Curriculam

Module 1: Python/ML in Artificial Lift 1 hrs.

Module 2: Python/ML in SRP 5 hrs.

Module 3: Physics based model for SRP in Python 12 hrs.

Module 4: Wave Modeling for downhole dynacard from surface data 12 hrs.

Module 5: Calculate fillage from DDC using python 5 hrs.

Module 6: Torque Analysis in Python 7 hrs.

Module 7: Stress Analysis in Python 5 hrs.

Module 8: 3D Visualization of wave propagation 3 hrs.

Pick a batch

1st Apr - 15th Jun
Mon, Tue, Wed, Thu, Fri
07:00 - 08:00PM

1st Apr - 30th Sep
Sat, Sun
12:00 - 01:00PM

Python Numpy and Pandas

Projects you will build

Digital Twin for Sucker Rod Pump

Calculating downhole dynacard from surface dynacard and pump failure identification using automated dynacard identification.

Artificial Intelligence

Digital Twin for Sucker Rod Pump

Digital Twin, Prescriptive Maintenance

Learn Effectively with our Industry Focused Approach

Petrocoder runs most specialised courses in oil & energy sector developed by industry specialists after several decades of experience.