Mineral exploration is at a turning point. The future of this sector will be defined not only by geological structures but also by how data science is used to read them more efficiently and responsibly, ensuring the supply of metals for the global energy transition. The new methodology significantly reduces the costs and timeframes of mineral exploration, facilitates the re-evaluation of historical core samples, and, crucially, decreases the uncertainty inherent in the industry's strategic decisions. The value of this tool lies in its speed and its ability to capture geological patterns invisible to the human eye. The combination of this technology with machine learning algorithms enables the objective and reproducible classification of lithologies and alterations. Geologist Felipe Bugueño notes that this methodology introduces a less intuitive, data-driven approach to mineral exploration. This paradigm shift transforms exploration from a discontinuous process marked by long laboratory waits into an information flow in near real-time. Geologist Bugueño anticipates that artificial intelligence and immediate data analysis will play a leading role in the near future. A key example is hydrothermal breccias. These have historically been recognized as essential indicators in the architecture of porphyry systems – giant geological formations that supply most of the world's copper – revealing the history of mineralizing fluid flows that concentrate strategic metals like molybdenum, zinc, and copper. However, traditional interpretation was based on point, fragmented, and slow sampling that created information gaps. This limitation is being overcome by technologies like Scan™, which allow for the continuous integration of geochemical (XRF) and hyperspectral scanning over drill core. Geologist Felipe Bugueño of Veracio states that the current dilemma is not to drill more, but to better understand the existing geology through the use of advanced data. During the FEXMIN fair in Chile, Veracio demonstrated how these tools are identifying geochemical contrasts that mark transitions between mineralizing domains, such as arsenic concentrations in breccias associated with porphyries or the increasing presence of lead and zinc in high-sulfidation environments. Amid the sustained global increase in demand for critical metals like copper and lithium, driven by the energy transition, the industry is seeking more precise, efficient, and sustainable methods for resource discovery.
