Introduction to Machine Learning for Geoscience

What is Data Science:

• Data Science life cycle
• Different types of Data Science jobs
• Data Science example in O&G

● Programming concepts and workflow:

• Coding workflow
•  Which language we should start

● Learning Python:

• Why we should learn coding
• Numerical, array operations using (Numpy)
• Data frame operation using (Pandas)
• Plotting using (Matplotlib, Seaborn)
•  Geoscience libraries
•  Welly
• Segyio

● Machine Learning:

• Machine Learning vs coding
• Machine Learning algorithm types
• Machine Learning algorithms classification
• Examples in Geoscience
• Supervised Machine Learning example
• Linear regression (LM)
• Logistic regression (LR)
• Support vector machine (SVM)
• Clustering Machine Learning example
• K-means
• Principal Component analysis (PCA)
• Random forest (RF)
• Neural Network in theory and Application

Instructor : Mr Amr Abdel Fattah

A versatile and highly skilled Geophysicist has 12 years’ industry experience, and wide ranging expertise from interpretation in exploration and resource development to 3D depth imaging technology development and application using a wide range of geosciences software. experienced in seismic interpretation, prospect generation; computer mapping and 3D visualization.

 He has a good command of R programming and data analysis that empowers me to solve technical problems in particular in statistics, Monte Carlo simulation and machine learning.