Sunday, 15 July 2018

Statistical and Mathematical Methods for Data Science (HEC)

Statistical and Mathematical Methods for Data Science
Credit Hours: 3
Prerequisites: None

Date : 7 June 2018


Course Contents:

Probability:
Probability basics (axioms of probability,



conditional probability,



random variables,



expectation, independence,




etc.), (Ignored)


multivariate distributions,


Maximum a posteriori and maximum likelihood estimation;






https://en.wikipedia.org/wiki/Maximum_a_posteriori_estimation


Statistics:

introduction to concentration bounds,



laws of large numbers,



central limit theorem,




https://www.youtube.com/watch?v=JNm3M9cqWyc


minimum mean - squared error estimation,




confidence intervals;




Linear algebra:
Vector spaces,





Projections (will also cover the least regression),



linear transformations,




singular value decomposition (this substitute for PCA),





eigen decomposition,



power method;





Optimization:
Matrix calculus with Lagrange Multipliers,







derivatives/constrained-optimization/a/lagrange-multipliers-examples




gradient descent,


coordinate descent,



introduction to convex optimization.




Teaching Methodology: Lectures, Problem based learning

Course Assessment:
Sessional Exam, Home Assignments, Quizzes, Project, Presentations, Final Exam

Reference Materials
Books:
1. Probability and Statistics for Computer Scientists, 2nd Edition, Michael Baron
2. Linear Algebra and Its Applications, 5th Edition, David C. Lay and Steven R. Lay
3. Introduction to Linear Algebra, 5th Edition, Gilbert Strang
4. Probability for Computer Scientists, online Edition, David Forsyth.

Contact Information :


If you would like to participate in this course and assessment development project, please contact Khawar Nehal on khawar@atrc.net.pk

You are welcome to send suggestions on how to improve this course.

Postal Address : C-55 Block A KDA Officers, Karachi 75260, Pakistan


Mobile : 92 331 2036 422

Petroleum Engineering - Unconventional Reservoirs HEC

Petroleum Engineering - Unconventional Reservoirs


By : Khawar Nehal

Date : 10 June 2018

Course code: PET-212

Course title: Unconventional Reservoirs

Credit hours: 3+0
Prerequisite: Pre - Engineering or Equivalent
Specific Objectives of Course:
To enable the students to understand unconventional reservoirs.
Course Learning Outcomes (CLOs): After studying this course, the learners will be able to: -
1. Discuss the fundamentals of different types of unconventional hydrocarbon resources.


2. Understand the economics , social, political and environmental
issues related to the development of unconventional reservoirs.

3. Calculate the reserves of unconventional reservoirs.

4. Understand basic measurement techniques for characterization of unconventional resources.

Content List
1. Introduction to Unconventional Energy Resources
a.Economic significance, technical, economic, political, and
environmental constraints on development of unconventional
resources.

2. Occurrences, resources and reservoir
characteristics.

a. Low-permeability (Tight) sands;


b. Shale reservoirs (gas and oil)

c. Coal Bed Methane (CBM)




d. Gas hydrates;

e. Heavy
oil



3. Drilling and completion methods for unconventional reservoirs.


4. Other unconventional energy resources


a. Geothermal energy,


b. Coal conversion to Gas,

c. Coal – to - gas and In-situ gasification.



d. Water and environmental issues.

e. Natural fractures and its importance in unconventional resources.

8. Basic measurements for characterization of unconventional
resources




Practicum NIL

Bibliography/References
1. Books:
a. Reza Rezaee, “Fundamentals of Gas Shale Reservoirs”
2015.
b. Usman Ahmed and Nathan Meehan; Unconventional Oil and
Gas Resources-Exploitation and Development, CRC Press,
2016, pp 860
c. Ma and Holditch, “Unconventional Oil and Gas
Resources Handbook: Evaluation and Development”, 1st Edition,
Elsevier, 2015
d. A Guide to Coal - bed Methane Operations, Gas Research
Institute, GRI, Chicago, 1992.
2. Journals/Periodicals: NIL
3. World Wide Web: NIL

Contact Information :


If you would like to participate in this course and assessment development project, please contact Khawar Nehal on khawar@atrc.net.pk

You are welcome to send suggestions on how to improve this course.

Postal Address : C-55 Block A KDA Officers, Karachi 75260, Pakistan


Mobile : 92 331 2036 422