Open AccessBook
Applied Geostatistics with SGeMS: A User's Guide
Nicolas Remy,Alexandre Boucher,Jianbing Wu +2 more
- 23 Mar 2009
TL;DR: In this article, the authors present a general overview of Geostatistics: a recall of concepts, data sets, SGeMS EDA tools, common parameter input interfaces, estimation algorithms and stochastic simulation algorithms.
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Abstract: 1. Introduction 2. General overview 3. Geostatistics: a recall of concepts 4. Data sets & SGeMS EDA tools 5. Variogram computation and modeling 6. Common parameter input interfaces 7. Estimation algorithms 8. Stochastic simulation algorithms 9. Utilities 10. Scripting, commands and plug-ins List of programs List of symbols Bibliography.
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Citations
Efficient variography with partition variograms
Júlio Hoffimann,Bianca Zadrozny +1 more
TL;DR: This work proposes a generalization of directional variograms to general partitions of spatial data, and introduces a parallel estimation algorithm that can efficiently handle large data sets with more than 105 points.
5
A workflow for modelling fluvial meander-belt successions: combining forward stratigraphic modelling and multi-point geostatistics
TL;DR: In this paper, a new workflow was developed for modeling reservoir successions that comprise fluvial meander-belt deposits, based on algorithms that employ multi-point statistics (MPS).
5
History Matching for Geological Carbon Storage using Data-Space Inversion with Spatio-Temporal Data Parameterization
Su Jiang,Louis J. Durlofsky +1 more
TL;DR: History matching for geological carbon storage using data-space inversion enables efficient uncertainty reduction in posterior pressure and saturation fields, improving aquifer management in industrial-scale carbon storage operations.
Hydraulic Tomography Estimates Improved by Zonal Information From the Clustering of Geophysical Survey Data
Chenxi Wang,Walter A. Illman +1 more
TL;DR: Hydraulic tomography estimates are improved by integrating geophysical survey data through k-means clustering and spatial constraints, enhancing hydrostratigraphic boundaries and zonation models, and further refined with local K measurements for more accurate subsurface characterization.
5
Assessment of alluvial aquifer heterogeneity and development of stochastic hydrofacies models for the Hat Yai Basin in Southern Thailand
Arun Lukjan,Tanit Chalermyanont +1 more
TL;DR: In this paper, an indicator-based geostatistical approach was used to develop hydrofacies models using sequential indicator simulation, which indicate three distinct aquifer units, namely Hat Yai, Khu Tao, and Kho Hong aquifers, which can be used in groundwater modeling and simulations.
5
References
A Computational Approach to Edge Detection
TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
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Inverse Problem Theory and Methods for Model Parameter Estimation
Albert Tarantola
- 20 Dec 2004
TL;DR: This chapter discusses Monte Carol methods, the least-absolute values criterion and the minimax criterion, and their applications to functional inverse problems.
Conditional Simulation of Complex Geological Structures Using Multiple-Point Statistics
TL;DR: The approach proposed in this paper consists of borrowing the required multiple-point statistics from training images depicting the expected patterns of geological heterogeneities from the geostatistical numerical model where they are anchored to the actual data in a sequential simulation mode.
1.6K
The intrinsic random functions and their applications
TL;DR: The intrinsic random functions (IRF) are a particular case of the Guelfand generalized processes with stationary increments and constitute a much wider class than the stationary RF, and are used in practical applications for representing nonstationary phenomena as discussed by the authors.