OOIR: Observatory of International Research

Papers

(The TQCC of Mathematical Geosciences is 6. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-05-01 to 2024-05-01.)

Article	Citations
GANSim: Conditional Facies Simulation Using an Improved Progressive Growing of Generative Adversarial Networks (GANs)	42
Graph Deep Learning Model for Mapping Mineral Prospectivity	41
Robust Feature Extraction for Geochemical Anomaly Recognition Using a Stacked Convolutional Denoising Autoencoder	40
A Physically Constrained Variational Autoencoder for Geochemical Pattern Recognition	24
Classical and Robust Regression Analysis with Compositional Data	24
A Truly Spatial Random Forests Algorithm for Geoscience Data Analysis and Modelling	24
MIN3P-HPC: A High-Performance Unstructured Grid Code for Subsurface Flow and Reactive Transport Simulation	23
A Coarse-to-Fine Approach for Intelligent Logging Lithology Identification with Extremely Randomized Trees	23
Fusion of Geochemical and Remote-Sensing Data for Lithological Mapping Using Random Forest Metric Learning	23
Quantifying the Tetrad Effect, Shape Components, and Ce–Eu–Gd Anomalies in Rare Earth Element Patterns	22
Three-Dimensional Structural Geological Modeling Using Graph Neural Networks	22
Contaminant Source Identification in Aquifers: A Critical View	20
One Step at a Time: The Origins of Sequential Simulation and Beyond	20
Stochastic Modelling of Mineral Exploration Targets	18
Statistical Interpolation of Spatially Varying but Sparsely Measured 3D Geo-Data Using Compressive Sensing and Variational Bayesian Inference	18
Entropy and Information Content of Geostatistical Models	17
Finite Difference Implicit Structural Modeling of Geological Structures	15
Analysing Pairwise Logratios Revisited	15
Special Issue: Geostatistics and Machine Learning	14
Seismic Stratum Segmentation Using an Encoder–Decoder Convolutional Neural Network	14
Bayesian Deep Learning for Spatial Interpolation in the Presence of Auxiliary Information	14
Variational Autoencoder or Generative Adversarial Networks? A Comparison of Two Deep Learning Methods for Flow and Transport Data Assimilation	14
On the Use of Interferometric Synthetic Aperture Radar Data for Monitoring and Forecasting Natural Hazards	12
Contaminant Spill in a Sandbox with Non-Gaussian Conductivities: Simultaneous Identification by the Restart Normal-Score Ensemble Kalman Filter	12
Multiple-Point Statistics Simulation Models: Pretty Pictures or Decision-Making Tools?	12

Compositional Data in Geostatistics: A Log-Ratio Based Framework to Analyze Regionalized Compositions	12
Construction and Application of a Knowledge Graph for Iron Deposits Using Text Mining Analytics and a Deep Learning Algorithm	11
Comparing Methods and Defining Practical Requirements for Extracting Harmonic Tidal Components from Groundwater Level Measurements	11
Towards Geostatistical Learning for the Geosciences: A Case Study in Improving the Spatial Awareness of Spectral Clustering	11
Diagenetic Facies Classification in the Arbuckle Formation Using Deep Neural Networks	11
Application of Bayesian Generative Adversarial Networks to Geological Facies Modeling	10
Boundary Identification and Surface Updates Using MWD	9
Stochastic Inversion of Gravity Data Accounting for Structural Uncertainty	9
High-Order Data-Driven Spatial Simulation of Categorical Variables	9
Spatiotemporal Precipitation Estimation from Rain Gauges and Meteorological Radar Using Geostatistics	9
Resource and Grade Control Model Updating for Underground Mining Production Settings	9
Geological Mapping Using Direct Sampling and a Convolutional Neural Network Based on Geochemical Survey Data	8
Comparison of Recursive Neural Network and Markov Chain Models in Facies Inversion	8
Blind Source Separation for Compositional Time Series	8
A Graph Clustering Approach to Localization for Adaptive Covariance Tuning in Data Assimilation Based on State-Observation Mapping	8
Finite Element Solvers for Biot’s Poroelasticity Equations in Porous Media	8
Discriminant Analysis for Compositional Data Incorporating Cell-Wise Uncertainties	8
Automated Machine Learning-Based Landslide Susceptibility Mapping for the Three Gorges Reservoir Area, China	8
Three-Dimensional Refined Modelling of Deep Structures by Using the Level Set Method: Application to the Zhaoping Detachment Fault, Jiaodong Peninsula, China	8
Quantifying Mineral Resources and Their Uncertainty Using Two Existing Machine Learning Methods	7
Resource Model Updating For Compositional Geometallurgical Variables	7
Is Cell-to-Cell Scale Variability Necessary in Reservoir Models?	7
Revealing Geochemical Patterns Associated with Mineralization Using t-Distributed Stochastic Neighbor Embedding and Random Forest	7
Training Image Free High-Order Stochastic Simulation Based on Aggregated Kernel Statistics	7
Compositional Scalar-on-Function Regression with Application to Sediment Particle Size Distributions	7
Machine Learning-Based Mapping for Mineral Exploration	7
Stochastic Inverse Modeling and Parametric Uncertainty of Sediment Deposition Processes Across Geologic Time Scales	7
Automatic Semivariogram Modeling by Convolutional Neural Network	7
New Validity Conditions for the Multivariate Matérn Coregionalization Model, with an Application to Exploration Geochemistry	6
Stochastic Modeling of Subseismic Faults Conditioned on Displacement and Orientation Maps	6
An Automatic Well Planner for Complex Well Trajectories	6
A Spatial Correlation-Based Anomaly Detection Method for Subsurface Modeling	6
Geographically Optimal Similarity	6
An Interpretable Graph Attention Network for Mineral Prospectivity Mapping	6
Weighting of Parts in Compositional Data Analysis: Advances and Applications	6
Stochastic Local Interaction Model: An Alternative to Kriging for Massive Datasets	6
Conditional Simulation for Mineral Resource Classification and Mining Dilution Assessment from the Early 1990s to Now	6
Deep Reinforcement Learning for Mineral Prospectivity Mapping	6
The Physical Meaning of the Koval Factor	6
Bridging Deep Convolutional Autoencoders and Ensemble Smoothers for Improved Estimation of Channelized Reservoirs	6
Bayesian Decomposition Modelling: An Interpretable Nonlinear Approach for Mineral Prospectivity Mapping	6
Enhancing Slope Stability Prediction Using Fuzzy and Neural Frameworks Optimized by Metaheuristic Science	6
Random Noise Attenuation by Self-supervised Learning from Single Seismic Data	6