In 2012, the canton of Geneva and the SIG (Services Industriels de Genève) started the Geothermie2020 program, aiming to exploit geothermal energy in the Greater Geneva Basin (GGB), Western Switzerland. Before the geothermal drilling operations start, it is key to know the local microseismicity, its relationship with local faults and their activation state. It is also important to ensure that the possible microseismicity can always be detected and located throughout the geothermal project. For this reason, a dense seismic network with sufficient sensitivity to monitor and control the seismicity levels in case of an unexpected event. In 2016, only two seismic stations were deployed in the basin, reaching a magnitude of completeness of 1.8-2.0. I deployed a temporary seismic network of 20 broadband stations around and within the Greater Geneva Basin for over 1.5 years (August 2016 - January 2018), lowering the magnitude of completeness to 0.5. This network served two purposes: to assess the seismotectonics of the basin and to perform an ambient-noise tomography study. We retrieved a new local 1D velocity model, with respective station corrections from the local earthquakes detected at the stations. The depth of the events increased after the relocation with the new model, indicating that the local faults might be deeper than expected. Newly computed focal mechanisms were used for a stress inversion. The stress inversion results show that the strike-slip faults that offset the basin are sub-parallel to the principal stress component, sigma 1, implying that these faults are currently active or prone to be re-activated. During the future exploitation of geothermal resources in the GGB, various types of microseimic events may be detected. Among them, weak emergent events with complex waveforms can occur (e.g., Larderello-Travale Geothermal Field, Italy). To locate such unconventional events, I developed a specifically designed location tool. The tool uses the cross-correlation of signals at different station pairs to provide a likelihood source location. The code was tested and applied to seismic signals associated with well-drilling operations in Larderello (Italy), LP events at magmatic volcanoes (Costa Rica) and drumbeat signals generated at mud volcanoes. I applied some of the previous techniques to identify, characterize and locate weak drumbeat signals at the at the Nirano Mud Volcano Field (Italy). I located the signals using the newly developed location tool and considering the seismic velocities that I locally retrieved with active seismic experiments. I used the drumbeat signals and V/H ratios to study the activity and evolution of the system. I found a correlation between the presence of the drumbeats and morphological changes, suggesting that the drumbeat signals can be used to access and monitor the evolution of the Nirano mud plumbing system.