Jianbing Wu

A SGeMS code for pattern simulation of continuous and categorical variables: FILTERSIM

The new multiple-point geostatistical algorithm (FILTERSIM), which can handle both categorical and continuous variable training images, is implemented in the SGeMS software. The spatial patterns depicted by the training image are first summarized into a few filter scores; then classified into pattern groups in the filter score space. The sequential simulation approach proceeds by associating each conditioning data event to a closest pattern group using some distance function. A training pattern is then sampled from that group and pasted back onto the simulation grid. Local multiple-point statistics carried by patterns are captured from the training image, and reproduced in the simulation realizations. Hence complex multiple-scale geological structures can be re-constructed in the simulation grid, conditional to a variety of sub-surface data such as well data and seismic survey.

Applied Geostatistics with SGeMS: Data sets and SGeMS EDA tools

This chapter presents the data sets used to demonstrate the geostatistics algorithms in the following chapters. It also provides an introduction to the exploratory data analysis (EDA) tools of the SGeMS software. Section 4.1 presents the two data sets: one in 2D and one in 3D. The smaller 2D data set is enough to illustrate the running of most geostatistics algorithms (kriging and variogram-based simulation). The 3D data set, which mimics a large deltaic channel reservoir, is used to demonstrate the practice of these algorithms on large 3D applications; this 3D data set is also used for EDA illustrations. Section 4.2 introduces the basic EDA tools, such as histogram, Q-Q (quantile–quantile) plot, P-P (probability–probability) plot and scatter plot. The data sets The 2D data set This 2D data set is derived from the published Ely data set (Journel and Kyriakidis, 2004) by taking the logarithm of all positive values and discarding the negative ones. The original data are elevation values in the Ely area, Nevada. The corresponding SGeMS project is located at DataSets/Elyl.prj. This project contains two SGeMS objects: Ely1-pset and Ely1-pset-samples. • The Ely1-pset object is a point set grid with 10, 000 points, constituting a reference (exhaustive) data set. This point set grid holds three properties: a local varying mean data (“lvm”), the values of the primary variable (“Primary”) and the values of a co-located secondary property (“Secondary”).