In this example, you will see how to create your own custom plot of drill core data containing location, orientation, depth, and geotechnical data (lithography. fracture count, rock strength, weathering, and RMR).
In this study, we address the issue of using graphs to predict flow as a fast and relevant substitute to classical DFNs. We consider two types of graphs, whether the nodes represent the fractures or the intersections between fractures.
This work presents a hybrid modeling approach to efficiently estimate and optimize rock movement during blasting. A small-scale continuum model simulates early-stage, near-field blasting physics and generates synthetic data to train a machine learning (ML) model. Key parameters such as expanded hole diameter, burden velocity, and gas pressure are obtained through the ML model, which then inform a discontinuum model to predict far-field muckpile formation. The approach captures essential blast physics while significantly accelerating blast design optimization.
Typical sedimentary sequences overlying coal seams consist of interbedded sandstones, siltstones, shales, and rider coal seams.