Introduction to Gaussian Random Function Simulation The so-called Gaussian Random Function simulation (GRFS) differs substantially from the Sequential Gaussian simulation (SGS) from GSLIB. GRFS more accurately reproduces distributions. It is typically faster than SGS, with additional efficiencies due to its parallel architecture. GRFS also has an option to run a fast collocated cosimulation – f...

Sequential Gaussian simulation (sgsim) and sequential indicator simulation (sisim) have emerged as powerful tools for stochastic imaging of Earth Science phenomena and are currently widely accepted fast simulation algorithms. In this paper, we will expand the sequential simulation toolbox by relying on a recent development in geostatistical theory (Journel, 1994) denoted as direct sequential si...

This paper presents practical methods for the sequential generation or simulation of a Gaussian two-dimensional random field. The specific realizations typically correspond to geospatial errors or perturbations over a horizontal plane or grid. The errors are either scalar, such as vertical errors, or multivariate, such as x, y, and z errors. These realizations enable simulation-based performanc...

In this paper, we explore a sequential Bayesian bound for state-space models focusing on hybrid continuous and discrete random states. We provide an analytic recursion for the sequential Weiss–Weinstein (SWW) bound for linear state-space models with solutions for Gaussian, uniform, and exponential distributions as derived, as well as for a combination of these. We compare the SWW bound for disc...

Truncated Gaussian Simulation (TGS) is a well-known method to generate realizations of the ore domains located in a spatial sequence. In geostatistical framework geological domains are normally utilized for stationary assumption. The ability to measure the uncertainty in the exact locations of the boundaries among different geological units is a common challenge for practitioners. As a simple a...

The fracture characterization using a geostatistical tool with conditioning data is computationally efficient for subsurface flow and transport applications. main objective of the paper to propose framework methods model network. In method, we have chosen neighborhood area apply Gaussian Sequential Simulation in order generate network unknown region. angle was propagated from seed where guide d...

This study applies variogram analyses of normalized difference vegetation index (NDVI) images derived from SPOT HRV images obtained before and after the ChiChi earthquake in the Chenyulan watershed, Taiwan, as well as images after four large typhoons, to delineate the spatial patterns, spatial structures and spatial variability of landscapes caused by these large disturbances. The conditional L...