Welcome,
Guest
.
Login
.
Türkçe
NİNOVA
COURSES
HELP
ABOUT
Where Am I:
Ninova
/
Courses
/
Institute of Science and Technology
/
PET 604E
/
Course Informations
Return to Faculty
Home Page
Course Information
Course Weekly Lecture Plan
Course Evaluation Criteria
Course Information
Course Name
Turkish
Rezervuar Mühendisliğinde Optimizasyon Yöntemleri
English
Optimization Methods in R.Eng.
Course Code
PET 604E
Credit
Lecture
(hour/week)
Recitation
(hour/week)
Laboratory
(hour/week)
Semester
2
3
3
-
-
Course Language
English
Course Coordinator
Mustafa Onur
Course Objectives
1. Advanced optimization concepts and methods used for reservoir characterization and management studies of petroleum, natural gas and geothermal reservoirs.
2. Fundamentals of solving forward and inverse problems in conjunction with advanced statistical and geostatistical concepts, theories and methods.
3. Advanced parameter estimation and performance prediction methods for underdetermined and overdetermined linear and nonlinear system of equations.
4. Methods for quantification of uncertainties associated with parameter estimation and future performance prediction.
Course Description
Deterministic and stochastic methods for optimization; forward and inverse problem definitions; Linear and non-linear regression; Optimization using non-gradient-based methods (simplex, Kalman and ensemble Kalman filter methods); Optimization using gradient based methods (conjugate gradient, steepest descent; Newton; Gauss-Newton, Levenberg-Marquardt); Simulated annealing; Neural networks; Eigenvalue and singular value decomposition; Applications to reservoir engineering and geostatistics.
Course Outcomes
Graduate students who successfully complete this course gain knowledge, skills and proficiency in the following subjects;
I. Basic knowledge and concepts in advanced reservoir optimization,
II. Linear and nonlinear reservoir modeling and parameter estimation,
III. Least-squares, maximum likelihood, and Bayesian estimation,
IV. History matching problem,
V. Geostatistics and its use in reservoir description,
VI. Unconstrained and constrained optimization algorithms,
VII. Gradient and nongradient optimization algorithms,
VIII. Future reservoir performance prediction and assessment of uncertainty in predictions
Pre-requisite(s)
Required Facilities
Other
Textbook
(1) Onur, M., 2009. Course Notes for PET604E, ITU Petroleum and Natural Gas Engineering Department.
(2) Oliver, D.S., Reynolds, A.C., and Liu, N. 2008. Inverse Theory for Petroleum Reservoir Characterization and History Matching, Advanced Engineering Mathematics, Cambridge University Press, Cambridge.
Other References
(1) Gill, P. E., Murray, W., and Wright, M. H., 1993. Practical Optimization, Academic Press, (10th printing), San Diego.
(2) Luenberger, D. G., 1984. Linear and Nonlinear Programming, Addison Wesley, (second edition), Massachusetts.
(3) Fletcher, R., 1989. Practical Methods of Optimization, John Wiley & Sons, Inc., New York.
(4) Tarantola, A., 1987. Inverse Problem Theory, Elsevier.
(5) Journel, A. G. 1978. Mining Geostatistics, Academic Press Inc., London.
(6) Isaaks, H. E., and Srivastava, R. M. 1989. An Introduction to Applied Geostatistics, Oxford University Press.
(7) Bard, Y., 1974. Nonlinear Parameter Estimation, Academic Press.
(8) Barlow, R. J. 1989. Statistics - A Guide to the Use of Statistical Methods in the Physical Sciences, John Wiley & Sons, New York.
(9) Sen, A., and Srivastava, M. 1990. Regression Analysis-Theory, Methods, and Applications, Springer Verlag, New York.
Courses
.
Help
.
About
Ninova is an ITU Office of Information Technologies Product. © 2025