714-0929/01 – Geostatistics (GSd)
| Gurantor department | Department of Mathematics and Descriptive Geometry | Credits | 10 |
| Subject guarantor | doc. RNDr. František Staněk, Ph.D. | Subject version guarantor | doc. RNDr. František Staněk, Ph.D. |
| Study level | postgraduate | Requirement | Choice-compulsory |
| Year | | Semester | winter + summer |
| | Study language | Czech |
| Year of introduction | 2003/2004 | Year of cancellation | 2019/2020 |
| Intended for the faculties | HGF, FAST | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
This course is dedicated to basic properties and modelling of natural objects. These problems can arise from other courses as well as from practice. The main emphasis lays in explanation of fundamental principles of geostatistical methods and of their general properties. The students learn how to decide which geostatistical procedure is a suitable tool for solving a specific problem. An important ingredient of the course is learning how to use existing software specialized for geostatistical computations, too.
The first part of the course deals with basic geostatistical notions and with the way in which to understand these notions from both theoretical and practical points of view.
In the second part of the course the students learn the geostatistical way of thinking as a mean of understanding real-life processes. The basic methods of collecting and analysing geo-data are introduced. The students are taught how to use these general methods to solve the problems arising from other courses of their study and from practice.
Teaching methods
Lectures
Individual consultations
Project work
Summary
Basic properties and modeling of natural objects. Introduction to geostatistics. Random function. Regionalized variable. Stationary and intrinsic hypotheses. Variogram. Anisotropies, drift, models for variograms. Experimental variograms. Structural analysis. Dispersion as a function of block size. Local estimation – kriging. Ordinary kriging. Point kriging and block kriging. Simple kriging. Universal kriging. Cokriging. Nonlinear kriging. Soft kriging. Lognormal kriging. Indicator kriging. Probability kriging. Cross validation. Principles of stochastic simulation. Sequential Gaussian simulation (SGSIM) and direct sequential simulation (DSSIM).
Compulsory literature:
Armstrong, M.: Basic Linear Geostatistics. Berlin, 1998.
Deutsch, C., V.: Geostatistical Reservoir modeling. Oxford, 2002.
Deutsch, C., V., Journel, A., G.: GSLIB – Geostatistical Software Library and User's Guide. Oxford, 1998.
Goovaerts, P.: Geostatistics for Natural Resourses Evaluation. Oxford, 1997.
Isaaks, E., H., Srivastava, R., M.: Applied Geostatistics. Oxford, 1989.
Lantuéjoul, Ch.: Geostatistical Simulation: Models and Algorithms. Springer, 2002.
REMY, N., BOUCHER, A., WU, J.: Applied geostatistics with SGeMS: a user's guide. New York: Cambridge University Press, 2009.
Recommended literature:
Clark, I., Harper, W.,V.: Practical Geostatistics. Ecosse North America Llc, Columbus Ohio, USA, 2000.
Kitanidis, P.,K.: Introduction to Geostatistics: Applications to Hydrogeology. New York, 1997.
Webster, R., Oliver, M. A.: Geostatistics for Environmental Scientists. Wiley, 2007.
Way of continuous check of knowledge in the course of semester
Individual consulting.
E-learning
Other requirements
Active participation in consultations and successful defense of the project.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Basic properties and modeling of natural objects. Introduction to geostatistics.
2. Random function. Regionalized variable.
3. Stationary and intrinsic hypotheses. Variogram. Anisotropies, drift, models for variograms.
4. Experimental variograms. Structural analysis.
5. Dispersion as a function of block size. Regularization and deregularization of variograms.
6. Local estimation – kriging. Ordinary kriging. Point kriging and block kriging. Simple kriging. Universal kriging.
7. Cokriging. Nonlinear kriging. Lognormal kriging. Indicator kriging.
8. Soft kriging. Probability kriging.
9. Cross validation. Principles of stochastic simulation.
10. Global estimation.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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