Mining, water-reservoir impoundment, underground gas storage, geothermal energy exploitation and hydrocarbon extraction have the potential to cause rock deformation and earthquakes, which may be hazardous for people, infrastructure and the environment. Restricted access to data constitutes a barrier to assessing and mitigating the associated hazards. thematic Core Service anthropogenic Hazards (tCS aH) of the European Plate Observing System (EPOS) provides a novel e-research infrastructure. the core of this infrastructure, the IS-EPOS Platform (tcs.ah-epos.eu) connected to international data storage nodes offers open access to large grouped datasets (here termed episodes), comprising geoscientific and associated data from industrial activity along with a large set of embedded applications for their efficient data processing, analysis and visualization. The novel team-working features of the IS-EPOS Platform facilitate collaborative and interdisciplinary scientific research, public understanding of science, citizen science applications, knowledge dissemination, data-informed policymaking and the teaching of anthropogenic hazards related to georesource exploitation. tCS aH is one of 10 thematic core services forming EPOS, a solid earth science European Research Infrastructure Consortium (ERIC) (www.epos-ip.org).
The possibility to have results very quickly after, or even during, the collection of electromagnetic data would be important, not only for quality check purposes, but also for adjusting the location of the proposed flight lines during an airborne time-domain acquisition. This kind of readiness could have a large impact in terms of optimization of the Value of Information of the measurements to be acquired. In addition, the importance of having fast tools for retrieving resistivity models from airborne time-domain data is demonstrated by the fact that Conductivity-Depth Imaging methodologies are still the standard in mineral exploration. In fact, they are extremely computationally efficient, and, at the same time, they preserve a very high lateral resolution. For these reasons, they are often preferred to inversion strategies even if the latter approaches are generally more accurate in terms of proper reconstruction of the depth of the targets and of reliable retrieval of true resistivity values of the subsurface. In this research, we discuss a novel approach, based on neural network techniques, capable of retrieving resistivity models with a quality comparable with the inversion strategy, but in a fraction of the time. We demonstrate the advantages of the proposed novel approach on synthetic and field datasets.
Abstract. Studying the uppermost structure of the subsurface is a necessary part of solving many practical problems (exploration of minerals, groundwater studies, geoengineering, etc.). The practical application of active seismic methods for these purposes is not always possible for different reasons, such as logistical difficulties, high cost of work, and a high level of seismic and acoustic noise. That is why developing and improving passive seismic methods is one of the important problems in applied geophysics. In our study, we describe a way of improving the quality of empirical Green's functions (EGFs), evaluated from high-frequency ambient seismic noise, by using the advanced technique of cross-correlation function stacking in the time domain (in this paper we use term “high-frequency” for frequencies higher than 1 Hz). The technique is based on the global optimization algorithm, in which the optimized objective function is a signal-to-noise ratio of an EGF, retrieved at each iteration. In comparison to existing techniques, based, for example, on weight stacking of cross-correlation functions, our technique makes it possible to significantly increase the signal-to-noise ratio and, therefore, the quality of the EGFs. The technique has been tested with the field data acquired in an area with a high level of industrial noise (Pyhäsalmi Mine, Finland) and in an area with a low level of anthropogenic noise (Kuusamo Greenstone Belt, Finland). The results show that the proposed technique can be used for the extraction of EGFs from high-frequency seismic noise in practical problems of mapping of the shallow subsurface, both in areas with high and low levels of high-frequency seismic noise.
Drastic measures are required to meet the standards of the Paris Agreement and limit the increase of global average temperatures well below 2°C compared to pre-industrial levels. Mining activities are typically considered as unsustainable but, at the same time, metals such as cobalt and lithium are essential to sustain the energy transition. Several sustainability goals defined by the United Nations (UN) require large quantities of raw materials. Exploration and extractives activities are required in order to contribute to meeting sustainability standards. Future sourcing of metals will need to implement procedures that go well beyond current ecological, economic, and social requirements and practices. In this paper we assess the usual sustainability criteria and how they apply to the extractives sector. Sustainability can only be achieved if one accepts that the natural capital can be substituted by other forms of capital (so called weak concept of sustainability). Sourcing the raw materials increasingly demanded by our societies will need transparent and inclusive stakeholder participation as well as a holistic understanding of the impact of extractives activities to reach this weak sustainability status. Our analysis shows that the sustainability of mining cannot be reached without harmonized political instruments and investment policies that take the three pillars of environmental, economic, and social sustainability as a major priority.
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