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
Geostatistical assessment of groundwater arsenic contamination in the Padana Plain.
Massimiliano Schiavo,Beatrice Maria Sole Giambastiani,Nicolas Greggio,Nicolò Colombani,Micòl Mastrocicco +4 more
TL;DR: A geostatistical analysis of >3600 wells in the Padana Plain (Northern Italy) reveals arsenic contamination in confined aquifers along piedmont areas and in phreatic aquifers in lowland territories, driven by reductive dissolution and organic matter mineralization.
8
Detection of Tracer Plumes Using Full‐Waveform Inversion of Time‐Lapse Ground Penetrating Radar Data: A Numerical Study in a High‐Resolution Aquifer Model
Peleg Haruzi,Jessica Schmäck,Z.Y. Zhou,Janusz Kruk,Harry Vereecken,Jan Vanderborght,Anja Klotzsche +6 more
TL;DR: In this article , a numerical tracer experiment was conducted by injecting saline water, desalinated water, and ethanol in a heterogeneous aquifer to test the potential of time-lapse GPR FWI for imaging tracer plumes.
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Simultaneous stochastic optimization of an open-pit mining complex with preconcentration using reinforcement learning
TL;DR: In this paper , an actor-critic reinforcement learning agent learns to optimize the short-term production schedule and provides a more flexible framework for adapting heuristics to the scheduling problem.
8
A distributed surrogate system assisted differential evolutionary algorithm for computationally expensive history matching problems
TL;DR: In this article , a distributed surrogate system assisted differential evolution algorithm, termed DSS-DE, is proposed for history matching problems, which builds a large number of basic learners before optimization, to effectively approximate different regions in the search space.
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Simulation of the Spatial Distribution of Hydraulic Conductivity in Porous Media through Different Methods
TL;DR: In this article, the heterogeneity of hydraulic conductivity is investigated in water conservancy projects, groundwater research and geological research, and hydraulic conductivities is an important factor that affects the seepage field.
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.