Erick de la Barra

We investigate multimodal seismicity by analyzing it as the result of multiple seismic sources. We examine three case studies: the Redoubt and Spurr regions in Alaska, where volcanic and subduction-related seismicity occur, and the Kii Peninsula in Japan, where shallow and deep earthquakes are clearly separated. To understand this phenomenon, we perform spatial, temporal, and magnitude analyses. Our application of non-extensive statistical mechanics shows that multimodal models provide a significantly better fit than unimodal ones. We identify patterns in the distributions of time between events and distances between events using multimodal Tsallis q-gamma distributions. In addition, we use the multimodal Sotolongo–Costa model to analyze the magnitude distribution, which effectively captures the complex interactions that may explain the observed lack of fractality in multimodal seismicity.

In mine planning, uncertainty assessment is essential to properly value a mining project. Geological, operational, and economical risks have to be considered to find the variable values that maximize the profit of the project. In this research, geological uncertainties are taken into account to assess the economic value of an underground gold mine. The scenarios considered are the tonnage-grade curves which are simulated by the Monte Carlo method. The decision variables are the cutoff grade (CoG), the Life of Mine (LoM), and operational variables, namely the mining and the processing capacity. In order to assess the economic value, we maximize the Net Present Value (NPV), which is carried out by a Genetic Algorithm (GA). This optimization, so-called implicit optimization, generates results of the probabilistic model which are compared with the deterministic one; the results found for a real underground gold mine show that, in the probabilistic case, the Net Present Value is higher and the time horizon is shorter than the results of the deterministic case, and the mining and the processing capacity are higher for the probabilistic case than the deterministic one.

To transition to carbon neutrality by the year 2050, copper, lithium, rare earths, cobalt, nickel, and silver are essential due to their use in the manufacture of electric cars, lithium batteries, wind turbines, solar panels, motors, and electrical wiring. The main goal of this study is to carry out a mining approach of the prospective areas of Colombia with strategic minerals for energy transition and climate change, analyzing the geospatial location, mining rights, mineral extraction, and royalty collection. Open data from SGC, ANM, and SIMCO geoportals were consulted. The prospective areas totaled 311,535.2 km², equivalent to 27.3% of Colombia, and were located mainly in the Andes Mountains. The total area of mining rights and applications with strategic minerals for the energy transition is 112,802.2 km² or 9.9% of Colombia, representing 5731 rights and 3939 applications. From 2012 to 2023, 448,330 tons of nickel, 172.9 tons of silver, and 171.6 tons of copper were mined in Colombia, which has contributed USD 513,140,286 as royalties to the state. No royalties have been earned from the extraction of rare earths, lithium, or cobalt. Fulfilling the Paris Agreement is possible with new sustainable mining projects of strategic minerals.

In order to characterize seismically the Coquimbo Region, Chile, data from 1943 to 2020 were considered. The region was divided into 30 zones of 0.5 • latitude and 0.5 • longitude and the non-extensive statistical physics was used. Both, the Sotolongo-Costa-Posadas and Mathai models were proposed to analyze the magnitude-frequency distribution. The subdivision into cells of the catalog allowed to demonstrate that systems with value of q ∼ 1 present exponential behavior, while with the superposition of subsystems it was expected to obtain q > 1, supporting the su-perstatistical model. Thus, by subdividing the Coquimbo region into the South and North regions, we find that in both the entropic index is greater than one, q > 1, however , according to the value obtained, in the southern sector the long-range effects are greater than in the northern sector. This means that both sectors ae well described by the nonextensive statistical model, either by SCP model or Mathai model; the entropic index is q > 1 and in both cases R 2 > 0.99. As the Coquimbo region is considered as a all, the nonextensive statistical distribution is the more adequated. With respect to the probabilistic seismic hazard assessment, we showed that the Mathai’s model has the better fit. Thus, in the frequency-interevent time distribution was used for different limite magnitudes values. Our analysis shows that the probability occurrence of an seismic event in the northern sector of the region is lower than in the southern sector for the same period; in the former the behavior is of Poissonian type. Thus, the region’s northern and southern zones show different behaviors in terms of earthquake occurrence probability.