IMEDEA Calendar | ![]() |
When | What | Where |
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Mié 15th Ene 11:00 am 12:00 pm | “Rugulopteryx okamurae: origin, impacts, biology and management” by María Altamirano Sala Seminarios | |
Jue 16th Ene 9:00 am 3:30 pm | IV Think Tank científico IMEDEA "Invasoras en Baleares" Casa Esment | |
Vie 17th Ene 12:00 pm 12:30 pm | AbstractSubsurface uncertainty poses a serious difficulty in deploying geo-energy applications, owing to its complexity and our limited access to it. Reducing such uncertainty is essential to enhance the reliability of simulation results that define safe operating conditions. Ground deformation analysis is capable of contributing to reducing subsurface uncertainty. For example, a double-lobe ground deformation shape revealed a vertical fault zone at depth in the CO2 storage project at In Salah, Algeria. The aim of this work is to outline a process for reducing subsurface uncertainty by correlating subsurface characteristics with ground deformation data. The workflow begins with training of a supervised gradient boosting-based machine learning regression model that predicts ground deformation caused by reservoir pressurization. We utilize a verified analytical solution (Wu, Rutqvist, and Vilarrasa, 2024) to assess ground displacement in response to pressurization of a reservoir intersected by either an impermeable or permeable fault to train the machine learning model. The instantaneous solution provided by the analytical solution enables us to generate an extensive dataset for training the model, encompassing fault and reservoir geometry as well as mechanical properties and operation conditions, i.e., reservoir pressurization. Simultaneously, principal component analysis and a simplified parametric space analysis are also performed. The results indicate that the pore pressure buildup and reservoir depth have the most significant impact on ground displacement. This study highlights that an appropriately trained machine learning model can effectively predict ground deformation and provide valuable information about the corresponding subsurface characteristics. Sala de Seminarios del IMEDEA, Esporles | |
Vie 24th Ene 12:00 pm 12:30 pm | AbstractIn situ beach monitoring is a costly and hazardous task, which can be improved using remote sensing. Specifically, X-band radar can measure the nearshore wave field and bathymetry, although virtually only pulsed systems have been used to this end. This seminar describes the application of a continuous-wave radar and the analysis pipeline developed by our group to measure the spatial cross-shore distribution of amplitude wave spectrum and bathymetry at a sandy beach. Sala de Seminarios del IMEDEA, Esporles | |
Vie 31st Ene 12:00 pm 12:30 pm | AbstractIn the Western Mediterranean Sea, vast extensions of rhodolith beds hold significant ecological value. These habitats are composed of free-living species of red coralline algae which are ecosystem engineers. The calcareous composition of rhodolith species makes them susceptible to climate change impacts, mainly to seawater acidification. Mediterranean rhodolith beds are multispecific habitats found from 60 up to 100 m below the surface, a deeper distribution that likely provides a more stable environment with fewer fluctuations in warming. However, there are gaps of knowledge on the responses of this multi-specific habitat to different disturbances. In this regard, we have focused on untangle the performance of two genera of rhodoliths along a thermal gradient, specifically of Lithothamium spp. and Phymatholiton spp. Measurements of dissolved oxygen and total alkalinity during the experiment allowed the calculation of metabolic rates. The thermal patterns and optimal temperatures for metabolic rates displayed by both genera were similar. These genera inhabit areas with mean yearly temperatures of 15°C and little temperature variation. However, both genera seem to be acclimated to a warmer range of temperature. Our findings suggest that Mediterranean rhodoliths genera are likely to cope with ocean warming. Sala de Seminarios del IMEDEA, Esporles |