Characterization of the recent seismic activity in the mining region of Jacobina-BA
Anthropogenic seismicity, Mining-induced seismicity, Coda wave interferometry, Moment tensor inversion
The recent known seismic activity in the region of Jacobina-BA was first registered by the Brazilian Seismographic Network (RSBR) in 2018. After that, in 2021, we observed an increase in the seismic activity rate, which included some events that were felt by the local population. Therefore, in early 2022, the Seismological Laboratory from UFRN deployed a local temporary seismographic network in the area. The six 3C short-period station network remained active until July 2023 and recorded continuous data. Only one station has been active in the area ever since. Preliminary analysis has shown that many events present a very shallow hypocentral depth (< 2 km) and are concentrated on a gold mining operational complex at the Jacobina Ridge. This indicates that the mining activities are triggering earthquakes and, if confirmed, that the influence of the mine is limited to the exploration areas. This work aims to characterize the seismic activity in Jacobina-BA using the data provided for the local network employed in the area. The characterization comprises the event location (absolute and double-dif erence location methods), magnitude estimation, and source parameters determination. Besides that, to support the objective, we will integrate some existing methodologies that must be very useful to increase the capability of seismological data processing, especially when applied to studies on intraplate seismicity. These methodologies are described now: The first methodology is applied for the identification of the seismic signals embedded in the continuous data. For this purpose we are employing the tool Python Matching Phase Algorithm (PyMPA). It is an open-source seismological software created to increase the detection sensitivity to micro-seismic events. PyMPA is based on the Match Filter Template approach to look for earthquakes that resemble well-located reference events, termed templates. Since the background noise might hide such signals, we expect that the PyMPA will enhance the detection ef iciency of seismic events, especially the smaller ones. The second methodology is encouraged by the lack of information on the blasting locations and the necessity of developing a strategy to discriminate seismic signals associated with blasting from fault-related events. We will use a moment tensor inversion algorithm to estimate the ratios of isotropic explosive and double-couple components. This discrimination is essential to identify blasting induced events and exclude explosions of seismic hazard investigations. Another methodology will be used as a result of the small quantity of stations deployed in the area. We decided to apply a recent method for relative location based on distance estimates between events inside a cluster. The distances are estimated using Coda Wave Interferometry (CWI), while the location algorithm adopts an inversion scheme based on a probabilistic frame to deal with the bias observed in CWI estimations. The technique can be employed even with a single station. We expect to improve the event location results and to be able to locate a greater number of events. Finally, we will map the geological discontinuities (pre-existing faults, dykes, etc.) present in the region of interest in order to investigate the correlation between them, the mining activities, and the observed seismicity.