“This book, titled “3D Geoscience Modeling Computer Techniques for Geological Characterization” reflects a career devoted to developing and applying computer techniques in the geosciences. The necessity for a geoscience modeling reference became evident during my active involvement in workshops and conferences on the subject over the past three years. I express gratitude to Keith Turner, Brian Kelk, George Pflug, and Johnathan Raper for organizing these events and fostering insightful discussions that significantly contributed to the book’s contents. The dedication extends to countless colleagues who, over the years, have played vital roles in shaping the presented concepts and techniques.
The “3D Geoscience Modeling Computer Techniques for Geological Characterization” book introduces various computer-based techniques for creating 3D geological models. Firstly, it explains how 3D modeling helps characterize geological structures and properties in space and time. Specifically, these models integrate diverse data to visualize and analyze the earth’s crust. For instance, models can map the distribution of rocks, fluids, and fossils. Additionally, they enable simulation of dynamic processes occurring underground.
The text then outlines commonly used modeling approaches. Notably, it contrasts deterministic and stochastic techniques. On the one hand, deterministic methods directly convert available data into 3D representations. On the other hand, stochastic techniques statistically analyze input data and calculate numerous probable models. Afterwards, the book compares numeric and geometric modeling methodologies. While numeric techniques compute quantitative models, geometric ones build spatial representations using points, lines, surfaces and solids.
Subsequently, the author examines diverse data sources for modeling the subsurface. For example, direct sampling provides physical specimens for analysis. Meanwhile, geophysical surveys measure responses to detect buried features. Furthermore, remote sensing and existing maps offer additional clues about geology. The book also covers data management tactics, including quality control and integration of multisource data.
Later sections detail various modeling algorithms and software tools. Specifically, the text outlines grid, mesh and vector approaches for handling nodes and cells. It additionally explores key processes like interpolation and extrapolation. When discussing software, the book highlightspackages for tasks ranging from data preprocessing to dynamic visualization. Tables compare capabilities of different modeling platforms.
In conclusion, the book systematically introduces standardized workflows for constructing 3D geoscience models. It intends to equip earth science researchers and industry practitioners to efficiently characterize the complex geology below ground. The comprehensive coverage of concepts, methodologies and technologies will assist implementation of 3D modeling.
This compilation would have been unattainable without direct contributions from several colleagues. Specifically, Ed Rychkun, Joe Ringwald, Dave Elliott, Tom Fisher, and Richard Saccany not only reviewed sections of the text but also provided invaluable comments. Mohan Srivastava offered insights and enhancements to some geostatistical presentations. Mark Stoakes, Peter Dettlaff, and Simon Wigzell were instrumental in processing numerous application examples. Anar Khanji and Randal Crombe aided in preparing the text and computer images, while Klaus Lamers assisted with printing. The application examples drew data support from the US Geological Survey, the British Columbia Ministry of Environment, and contributions from Dave Elliott and others. Sincere thanks to all who contributed directly to make this book possible.”
