Data Analysis and Geostatistics

Syllabus of

Data Analysis and Geostatistics

Lecturer: Asaad Fagheh

2014-2015

Soran University

Module Specification Template

1. Module Title:Data Analysis and Geostatistics

2. Module Code: PGE305

3. Module Level: Third year

4. Module Leader: Asaad Fagheh

5. Teaching Semester: Fall Semester/2014

6. Credit Rating for the module: 3

Final Exams - written tests designed to measure knowledge of presented course material (60%)

Quizzes- two quizzes will be held which cover 30% of final grade

Exercises - Post chapter questions and problems to support chapter learning objectives (5% of final grade)

Continues attendance - participation in classes (5% of final grade)

7. Prerequisites and co-requisites: Probability and Statistics, Reservoir Rocks and Fluid Properties

8. Module Summary

This course will build on a brief review of basic statistics to cover traditional and modern data analysis techniques, with a focus on robust estimates of statistics with uncertainties. Also, provides students with fundamental knowledge in statistics and computational techniques to study problems with random factors in geology. In addition, some software that deals with Geostatistics such as SGeMS and GSLIB are also presented in the course.All contents for lectures, exams and homework in this course will be delivered in English.

Furthermore, the level of the students in chemistry will be checked by executing the FinalExams, Quizzes, and Exercises from Post chapter questions and problems to support chapter learning objectives and focus on continues attendance.

9. Module Aims

The main focus of the course will be detailed introduction of geostatistical methodology withemphasis on applications in Petroleum engineering. The following maintopics will be discussed: spatial variability and its characterization; mapping reservoir variables via geostatistical tools; and accounting for spatial variability inanalysis of designed experiments.

10. Learning Outcomes

At the end of this course, the course is designed to help students to understand:

1-Quantify spatially distributed data in terms of spatial statistics (e.g. correlation length, trends), estimate and model the Variogram / covariance

2-Estimate values in unsampled locations using basic spatial interpolation/extrapolation and geostatistical methods

11. Theory Syllabus

Week 1

Univariate statistics

Measures tools of Location and Spread
Mean, median, variance, Standard Deviation

Week 2

Univariate Plots

Histogram
Probability Density Function (PDF)
Cumulative Density Function (CDF)

Week 3

Types of Distributions

1.Parametric:Normal (Gaussian),Log-Normal

2.Non-Parametric

3.Outlier Handling

Week 4

Bivariate Statistics

Bivariate Data Display: Scatterplot or Cross plot
Bivariate Measures (Covariance, Correlation Coefficient)

Week 5

Linear Regression
Declustering

Week 6

Midterm exam

Week 7

Basic spatial interpolation: nearest neighbors, inverse distance, trend surfaces

Week 8

Characterization of spatial processes: Variogram and covariance

Week 9

Estimating and modeling the variogram

Week 10

Local estimation or prediction and quantifying uncertainty in estimates: kriging

Week 11

Cross-correlation, co-regionalization, cokriging

Week 12

Introduction to simulation methods

Week 13

Cross validation and comparing the discussed geostatistics methods

Week 14

Revision week

Week 15

Final exam

Practical Labs of Data Analysis and Geostatistics

Week 1:
Problem solution about Basic statistics
Week 2:
Problem solution about Basic statistics
Week 3:
Installation and general familiarity with SGeMS(Stanford Geostatistical Modeling Software)
Week 4:
Univariate statistics in SGeMS
Week 5:
Univariate statistics parameters in SGeMS
Week 6:
Univariate Plotsin SGeMS
Week 7:
Bivariate statistics in SGeMS
Week 8:
Midterm exam
Week 9:
Variography by SGeMS
Week 10:
Kriging algorithm by SGeMS
Week 11:
Other kriging methods by SGeMS
Week 12:
Simulation methods by SGeMS
Week 13:
Data analysis and Variography by Petrel
Week 14:
Making a real project

12. Assessment Strategy

Briefly, the level of the students in basic statistics and geostatistics will be checked by executing the semifinal exams, quizzes, and exercises from post chapter questions and problems to support chapter learning objectives with focus on Continues attendance.

13. Summary description of assessment items

Theory (60% of total course marks)

1-The average of 2 written examinations for each semester will stand for 25% of the total course marks.

2-A Final examination will stand for the remaining 40% of total course marks.

Practical (40% of total course marks)

1-The average of 2 written examinations (two each semester) will stand for 15% of the total course marks.

2-A final examination will stand for 20% of the total course marks.

The average grade of several practical reports will account for 5% of the total course marks. Each group of 3-4 students has to submit a report about the laboratory work. The reports have to be approved by the lecturers in order for the group to be granted admission for the final examination.

14. Learning Session Structure

The structure of each weekly learning session will be 1 hour and 30 minute lecture followed by 30 minute quiz, and 2:30 hour practical in the lab followed by 30 minute quiz.

15. Learning and Teaching Methods

This course strives to show the student how statistics can enhance data analysis and characterization procedures. The importance of geology during all phases is emphasized, so that the student understands how and why to include all information, including engineering judgment, during the analysis. Numerous examples and problems cover both routine and special applications.

16. Bibliography

[1] Isaaks, Edward H., and R. Mohan Srivastava / An Introduction to Applied Geostatistics, Oxford University Press(1989).
[2] Caers, Jef. / Petroleum Geostatistics,Society of Petroleum Engineers., USA (2005).
[3] Yang et al. / Statistics for research, John Wiley & Sons, New Jersey, USA (2004)
[4] Deutsch and Journel / GSLIB Geostatistical Software Library and User’s Guide, Oxford University Press, USA (1998).

17. Authored by

Asaad Fagheh, 20/ 11/ 2014

18. Validated and Verified by

[Another member of staff who has checked the module specification to ensure that it meets the requirements of the course of which it a part and has checked the specification for any errors. This will include the date it was approved.]