Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling pp 403-433 | Cite as

# Stochastic Modeling of Continuous Geospatial or Temporal Properties

## Abstract

This chapter presents geostatistical methods for stochastically simulating continuous geospatial properties. For facilitating the presentations, it uses many temporal data in stochastic simulations benefiting from the 1D simplification. The commonly used simulation methods for spatial data include sequential Gaussian simulation and spectral simulation. Unlike estimation methods (e.g., regression and kriging), one main goal of stochastic simulation is to model the heterogeneities of physical properties.

Stochastic simulations are often mathematically extended from estimation methods. Therefore, the kriging methods presented in Chap. 16 are used as a methodological basis for stochastic simulations. Readers should be familiar with kriging, especially simple kriging, before reading this chapter. The main texts in this chapter focus on basic methodologies and three appendices cover more advanced topics.

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