Geostatistics Toronto 2021: Quantitative Geology and Geostatistics

Preface
Acknowledgements
Remembering Dr. Harry M. Parker (1946–2019)
Contents
Theory
A Geostatistical Heterogeneity Metric for Spatial Feature Engineering
	1 Introduction
	2 Methodology
	3 Results and Discussion
	4 Case Study
	5 Conclusion
	References
Iterative Gaussianisation for Multivariate Transformation
	1 Introduction
	2 Iterative Multivariate Gaussianisation
	3 Nickel Laterite Case Study
		3.1 Overview
		3.2 Workflow
		3.3 Multivariate Transformation and Simulation
		3.4 Benchmarking
		3.5 Artifacts
	4 Conclusions
	References
Comparing and Detecting Stationarity and Dataset Shift
	1 Introduction
	2 Materials and Methods
	3 Results and Discussion
	4 Conclusions
	References
Simulation of Stationary Gaussian Random Fields with a Gneiting Spatio-Temporal Covariance
	1 Introduction
	2 Theoretical Results
	3 A Discrete-in-Time and Continuous-in-Space Substitution Algorithm
	4 A Fully Continuous Spectral Algorithm
	5 Concluding Remarks
	References
Spectral Simulation of Gaussian Vector Random Fields on the Sphere
	1 Introduction
	2 Mathematical Background
	3 Simulation Algorithms
		3.1 Random Mixture of Spherical Harmonics (RMSH)
		3.2 Random Mixture of Legendre Waves (RMLW)
		3.3 Discussion
	4 Examples
	5 Conclusions
	References
Petroleum
Geometric and Geostatistical Modeling of Point Bars
	1 Introduction
	2 An Overview of Point Bar Geometry
	3 Modeling Approach
	4 Channel and Point Bar Facies Identification
	5 Channel Path Recreation
	6 Channel Path Migration
	7 Modeling the IHS Geometry
	8 Grid Generation
	9 Preservation of Point Bar Architecture and Its Internal Heterogeneity
	10 Concluding Remarks
	References
Application of Reinforcement Learning for Well Location Optimization
	1 Introduction
	2 Theory
	3 Well Location Problem
	4 Case Studies
	5 Discussion
	6 Conclusion
	Appendix
		Neural Network Architecture for Different Case Studies
		Visualization of Convergence
	References
Compression-Based Modelling Honouring Facies Connectivity in Diverse Geological Systems
	1 Introduction
	2 Connectivity in Facies Models and Natural Systems
	3 Compression-Based Facies Modelling
	4 Conclusions
	References
Spatial Uncertainty in Pore Pressure Models at the Brazilian Continental Margin
	1 Introduction
	2 Theoretical Foundations and Definitions
	3 Data Presentation and Interpretation
	4 Conclusions
	5 Benefits Promoted by This Work
	References
The Suitability of Different Training Images for Producing Low Connectivity, High Net:Gross Pixel-Based MPS Models
	1 Introduction
	2 Pixel-Based MPS Modelling with Common Training Images
	3 Pixel-Based Modelling with Low Connectivity
	4 Summary
	References
Probabilistic Integration of Geomechanical and Geostatistical Inferences for Mapping Natural Fracture Networks
	1 Introduction
	2 MPS Algorithm in Classification Framework
	3 Combination of Probabilities
	References
Mining
Artifacts in Localised Multivariate Uniform Conditioning: A Case Study
	1 Introduction
	2 Multivariate Uniform Conditioning and LMUC
	3 Case Study Presentation and Results
		3.1 Global and Local Scatterplots
		3.2 Correlation Between Localised Attributes
	4 Conclusions
	References
Methodology for Defining the Optimal Drilling Grid in a Laterite Nickel Deposit Based on a Conditional Simulation
	1 Introduction
	2 Sequential Gaussian Simulation
	3 Sequential Indicator Simulation
	4 Optimisation of a Drilling Grid
	5 Case Study
		5.1 Methodology
		5.2 Geostatistical Simulation with Original Database
		5.3 Geostatistical Simulation with a Virtual Drilling Grid Database
		5.4 Geostatistical Simulation of 100 Realisations of Thickness, Nickel and Ore Type
	6 Results and Discussion
	7 Conclusions
	References
LSTM-Based Deep Learning Method for Automated Detection of Geophysical Signatures in Mining
	1 Introduction
	2 Data Used
	3 Methodology
		3.1 Long Short-Term Memory (LSTM)
		3.2 Training and Validation
	4 Results and Discussion
	5 Conclusion
	References
Earth Science
Spatio-Temporal Optimization of Groundwater Monitoring Network at Pickering Nuclear Generating Station
	1 Introduction
	2 Site and Dataset
		2.1 Subsurface Geology
		2.2 Groundwater Monitoring
	3 Methodology
		3.1 Monitoring Objectives
		3.2 Decision Criteria
		3.3 Sequential Well-Reduction Algorithms
	4 Spatial Sampling Optimization
	5 Spatiotemporal Sampling Optimization
		5.1 Sensitivity Analysis of Temporal Samples
		5.2 Sampling Reduction, Considering Previously Sampled Data
	6 Conclusion
		6.1 Decision Criteria Are Geostatistical
		6.2 Spatial Correlation
		6.3 Temporal Correlation
	References
Domains
Applying Clustering Techniques and Geostatistics to the Definition of Domains for Modelling
	1 Introduction
		1.1 Machine Learning in Mining
		1.2 Stationarity in the Context of Mineral Resource Modeling
		1.3 Types of Clustering Algorithms and Background
		1.4 Discussions on the Validation Process
		1.5 Supervised Learning Applied to the Classification of New Samples
	2 Methods and Workflow
		2.1 Clustering Algorithms
		2.2 Validation Methods
		2.3 Automatic Classification of New Samples
		2.4 Workflow
	3 Case Study
		3.1 Exploratory Data Analysis
		3.2 Applying Cluster Analysis and Verifying the Results
		3.3 Discussions on the Results of the Cluster Analysis
		3.4 Supervised Learning Applied to the Automatic Classification of New Samples
	4 Conclusions
	References
Addressing Application Challenges with Large-Scale Geological Boundary Modelling
	1 Introduction
	2 Geology
	3 Gaussian Processes
	4 A Priori Data
	5 Model Building
		5.1 Spatial Rotations
		5.2 Region Overlap
		5.3 Mesh Resolution
		5.4 Model Evaluation
	6 Unassayed Production Holes
		6.1 Results
	7 Discussion and Conclusions
	References
Appendix A Appendix: Short Abstracts
Theory
Petroleum
Mining
Earth Science
Domains
Author Index