Python Computation Bootcamp for Geoscientist and Engineers
About the course, Goal and Objectives
The aim of this course is to teach computer programming using examples from Mathematics, Engineering, and Geosciences.
We have chosen to use the Python Programming Language because it combines remarkable expressive power with very clean, simple, and compact syntax.
Python is easy to learn and very well suited for an introduction to computer programming. Python is also quite similar to MATLAB and a good
Language for doing Mathematical Computing. It is easy to combine Python with compiled languages, like FORTRAN, C, and C++, which are widely used languages for scientific computations.
The examples in this course will integrate programming with applications to Mathematics, Physics, Geology and Engineering.
Prerequisites:
1. Knowledge of Basic One-Variable Calculus and Physics as taught in hundred level or secondary schools.
2. Your Laptop and a Stable Internet Connection
3. Zoom Mobile App or Zoom Desktop App
4. WhatsApp for Communication
5. Dedication and Commitment
Objectives:
Since we will be having mainly geoscientists in this course, some of the most useful and frequently used computational tools we will be learning and applying will fall under the broad category of image processing.
This course will introduce you to some core image processing methods by solving a handful of realistic tasks related to Geology and Geophysics.
The goal is to gain familiarity with key "building blocks" and terminology so that you can understand how to use common Python libraries such as scipy.ndimage, numpy and sklearn in your day-to-day work.
Training Duration: 4 Weeks
Project Duration: 2 Weeks
Date: 17th July - 31st August, 2021
Time: 1pm – 4pm
Venue: Zoom and Private WhatsApp Support Group.
Bootcamp Packages: Mini Project Assignment, Worksheet, Data, Software Installation, Training Materials, Evaluation Quiz and Certificate of Completion…
Bootcamp: N15, 000 Naira…
Number of Participants: 40 Participants
Project Category: You will be asked to PICK ONE Category to Build and Complete the Project after the Training Section.
- Data Driven Reservoir Modelling in Python
- Preparing Data for Petrophysical evaluation and Petrophysical Analysis with Python.
Course Content: Image processing with Python for Geoscientist and Geophysicist
Technologies to be used: numpy, scipy, sklearn, scipy.ndimage
Overview / Introduction
Computing Formulas
- using variables
- using a program as a calculator
- Evaluating standard mathematical functions
- complex numbers in python
- symbolic computing ( Basic differential and integral equation)
Loops and lists
- while-loops
- for loops
- range construction
- list comprehensions
- Nested lists/Matrices
Functions and Branches
- local and global variables
- program flow
- return and print
- if-else blocks
- lambda Functions
User input and Error handling
- Read from CLI
- reading data from files
- turning user Text into live objects
- writing data to file
- handling Errors
Arrays computing and Curve Plotting
- vector concept
- Numerical python arrays
- computing coordinates and functions values
- compact array generation
- plotting of scalar and vector fields
- contour lines / the gradient vector field
Matplotlib and Mayavi
- surface plots
- contour plots
- vector fields
- 3D scalar field and its gradient
Dictionary and strings
- making Dictionaries/ dictionaries operations
- storing file data in dictionaries
- using nested dictionaries
- strings and string operations
- reading and writing spreadsheet files
Classes and objects
- simple function classes
- the self-variable
- special methods
- class for vectors in plane
- class for complex numbers
- Inheritance and Class Hierarchies
Seamount Detection Example
- Thresholding,
- Filtering
- Segmentation,
- Simplification
Slope and Hill shade of Topographic Data
- Gradients
- Hill shade
Toe of Slope Detection
- Laplacian
- Skeletonization
Lineament Analysis from Aerial Photography
- Edge detection
- Hough Transform
- Structure Tensor
Grain Detection in Thin Sections
- Color-based segmentation
- SLIC
- Image moments