High-resolution truncated plurigaussian simulations for the characterization of heterogeneous formations

Integrating geological concepts, such as relative positions and proportions of the different lithofacies, is of highest importance in order to render realistic geological patterns. The truncated plurigaussian simulation method provides a way of using both local and conceptual geological information to infer the distributions of the facies and then those of hydraulic parameters. The method (Le Loc'h and Galli 1994) is based on the idea of truncating at least two underlying multi-Gaussian simulations in order to create maps of categorical variable. In this manuscript we show how this technique can be used to assess contaminant migration in highly heterogeneous media. We illustrate its application on the biggest contaminated site of Switzerland. It consists of a contaminant plume located in the lower fresh water Molasse on the western Swiss Plateau. The highly heterogeneous character of this formation calls for efficient stochastic methods in order to characterize transport processes.Comment: 12 pages, 9 figure

Inverse Methods in Hydrogeology: Evolution and Recent Trends

[EN] Parameter identification is an essential step in constructing a groundwater model. The process of recognizing model parameter values by conditioning on observed data of the state variable is referred to as the inverse problem. A series of inverse methods has been proposed to solve the inverse problem, ranging from trial-and-error manual calibration to the current complex automatic data assimilation algorithms. This paper does not attempt to be another overview paper on inverse models, but rather to analyze and track the evolution of the inverse methods over the last decades, mostly within the realm of hydrogeology, revealing their transformation, motivation and recent trends. Issues confronted by the inverse problem, such as dealing with multiGaussianity and whether or not to preserve the prior statistics are discussed. (C) 2013 Elsevier Ltd. All rights reserved.The authors gratefully acknowledge the financial support by the Spanish Ministry of Science and Innovation through project CGL2011-23295. We would like to thank Dr. Alberto Guadagnini (Politecnico di Milano, Italy) for his comments during the reviewing process, which helped improving the final paper.Zhou, H.; Gómez-Hernández, JJ.; Li, L. (2014). Inverse Methods in Hydrogeology: Evolution and Recent Trends. Advances in Water Resources. 63:22-37. https://doi.org/10.1016/j.advwatres.2013.10.014S22376

Combining the Pilot Point and Gradual Deformation Methods for Calibrating Permeability Models to Dynamic Data

We focus on specific parameterization techniques developed in inverse stochastic modeling for determining permeability fields from dynamic data using a reduced number of parameters. Two major contributions are the pilot point method and the gradual deformation method. They were designed to reduce the number of parameters and to respect the inferred spatial structure. Weaknesses have been revealed for the pilot point method: pilot points can be assigned unreasonably extreme values and possible correlations among the pilot points are neglected. To bypass these limitations, a new approach, called the gradual pilot point method, is suggested. It follows the basic workflow of the pilot point method, but the pilot point values are not driven by the optimization procedure. Intermediate gradual deformation parameters are introduced which govern the pilot point values. Compared to the original pilot point method, the gradual pilot point method does not produce extreme variations. Moreover, when the whole set of pilot points is modified simultaneously from a single deformation parameter, the correlations among the pilot points are accounted for. Thus, many pilot points can be placed on the permeability field, whatever their locations. They can produce local and global deformation. The performed numerical experiments show that a two-step approach for calibrating permeability fields is useful. First, the gradual deformation method is used to globally deform the permeability fields. Once the permeability fields have been globally improved, they can be locally refined using the gradual pilot point method

Elements for an Integrated Geostatistical Modeling of Heterogeneous Reservoirs

The geostatistical approach for modeling heterogeneous reservoirs allows, on one hand, to integrate data of various natures and scales, and on the other hand, to evaluate uncertainties by generating multiple possible scenarios of the reservoir heterogeneity. Building a geostatistical reservoir model must account for the geological depositional environment of the reservoir, so as to represent the major heterogeneities that control fluid flow. The quantitative information from wells, seismic and well tests, etc., must be used for the inference of the model structural parameters. Constraining model realizations to the hydrodynamic data from production allows to further increase the model reliability for production forecasts. This paper presents the elements of an integrated methodology for modeling heterogeneous reservoirs. We first introduce the basic geostatistical models used to describe the heterogeneous reservoirs. This is followed by an outline on the inference of the model structural parameters. Then, we present an inverse approach based on the gradual deformation method for history matching