# 541-0602/04 – Geostatistics (GEOSTAT)

 Gurantor department Department of Geological Engineering Credits 5 Subject guarantor doc. RNDr. František Staněk, Ph.D. Subject version guarantor doc. RNDr. František Staněk, Ph.D. Study level undergraduate or graduate Requirement Compulsory Year 2 Semester winter Study language Czech Year of introduction 2019/2020 Year of cancellation Intended for the faculties HGF Intended for study types Follow-up Master
Instruction secured by
STA22 doc. RNDr. František Staněk, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Part-time Credit and Examination 8+8

### 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.

Lectures
Tutorials
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:

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. 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. LANTUÉJOUL, CH.: Geostatistical Simulation: Models and Algorithms. Springer, 2002.

### Way of continuous check of knowledge in the course of semester

Successful completion of written tests and defense of assigned programs.

### E-learning

\\geolserv\PRENOSY\Statistika

### Other requirements

Active participation in seminars and successful completion of written tests.

### 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. 4. Variogram. Anisotropies, drift. 5. Experimental variograms, models for variograms. 6. Structural analysis. 7. Dispersion as a function of block size. Regularization and deregularization of variograms. 8. Local estimation – kriging. 9. Ordinary kriging. Point kriging and block kriging. 10. Simple kriging. Universal kriging. Cokriging. 11. Nonlinear kriging. Lognormal kriging. Indicator kriging. Soft kriging. 12. Probability kriging. Cross validation. 13. Principles of stochastic simulation. 14. Global estimation.

### Conditions for subject completion

Part-time form (validity from: 2019/2020 Winter semester)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
Credit Credit 33  17
Examination Examination 67  18
Mandatory attendence parzicipation: doplnit, doplnit, doplnit, doplnit.

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### Occurrence in special blocks

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