Stratigraphic modeling based on physical and geologic principles has been improved by more sophisticated process models and increased computer power. However, such efforts may reach a limit in their predictive power because of the stochastic, multiscaled nature of the physical processes involved. Building on techniques from the geostatistical literature, a conditional simulation method, dubbed ...

Complex categorical variables are usually classified into many classes with interclass dependencies, which conventional geostatistical methods have difficulties to incorporate. A two-dimensional Markov chain approach has emerged recently for conditional simulation of categorical variables on line data, with the advantage of incorporating interclass dependencies. This paper extends the approach ...

Reservoir simulation is ubiquitous in the petroleum industry, and conditioning models to production data (history matching) has become an essential job of reservoir engineers. Traditional history matching methods directly perturb reservoir properties without regard to the existing geological continuity. When the geological heterogeneity is destroyed, the result is often a history-matched model ...

Advanced Simulation Capability for Environmental Management (ASCEM) is an emerging state-of-the-art scientific methodological and computational framework for analyzing and predicting subsurface flow and contaminant transport in natural and engineered systems. ASCEM is supported by the U.S. Department of Energy Office of Environmental Management (DOE-EM). The ASCEM framework is designed to provi...

Modern geostatistical mapping methods are being applied to various types of data to produce more realistic and flexible characterizations of a natural random process. The Bayesian Maximum Entropy (BME) is a well-known geostatistical estimation method, especially for the use of soft knowledge as well as exact measurement data. Although development in geostatistical methods helps us to solve limi...

Pattern-based spatial modeling relies on training images as basic modeling component for generating geostatistical realizations. The methodology recognizes that working with the unit of a pattern aids its reproduction, particularly for large systems. In this paper improvements are made, in terms of both the computation time and conditioning, of a pattern-based simulation method that relies on t...

[1] The simulation of conservative solute transport in a heterogeneous unsaturated soil depends on the description of spatial variability of soil hydraulic and chemical properties. The data from the Las Cruces Trench Site were used to explore the impact of alternative ways of describing the variability of hydraulic properties. Three different approaches were considered: Miller and Miller scalin...