Theory of deterministical and stochastical indicator mapping methods and their applications in reservoir characterization, case study of the Upper Miocene reservoir in the Sava Depression

Authors

  • Kristina Novak Zelenika INA - Oil industry Plc.

DOI:

https://doi.org/10.17794/rgn.2017.3.5

Abstract

The paper describes indicator based geostatistical methods (Indicator Kriging and Sequential Indicator Simulations),mostly used for facies mapping or facies modeling. Although it is assumed that in facies modelling variables should be descrete, it is possible to apply these methods on continuous variables as well. Continuous variables such as porosity can very well describe lithofacies. Methodology includes series of cut-offs. Indicator Kriging maps show probability of certain lithofacies appearing in some location. On the other hand, stochastical realizations provide different number of solutions for the same input data set. Those solutions can be very similar, but never identical. It is important to emphasize that all obtained solutions or results are equally probable. Results of Sequential Indicator Simulations are also probability maps. There are several advantages for Indicator based methods. They do not need normality for the input dataset, they can be implemented in case of bimodal distribution, and they can show connectivity of the largest or smallest values.

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Published

2017-06-21

How to Cite

Novak Zelenika, K. (2017). Theory of deterministical and stochastical indicator mapping methods and their applications in reservoir characterization, case study of the Upper Miocene reservoir in the Sava Depression. Rudarsko-geološko-Naftni Zbornik, 32(3), 45–53. https://doi.org/10.17794/rgn.2017.3.5

Issue

Vol. 32 No. 3 (2017): No. 37

Section

Geology

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