This paper presents the spatial distribution of shallow gas structures and classifies them on the basis of two different data sets of CHIRP seismic records, one from the Conceição Lagoon (CL) and the other from North Bay (NB), both on Santa Catarina Island, Southern Brazil. Side scan sonar data from the CL were used to facilitate the understanding. The sub bottom (SB) seismic data were processed and interpreted by means of the SeisPrho software, the side scan sonar (SSS) data by SonarWiz5 software and the spatial extension being measured with the help of GIS. The shallow gas structures were defined in accordance with their shapes in the seismic recordings (echo-character). At the CL, shallow gas accumulations were found in the form of seepages and features presenting shallow gas structures between the surface and 8.20 ms (around 12.3 m). Accumulations of gas were found in the form of Acoustic Blanking with Acoustic Plume, and also Black Shadows. Pockmarks were found on the lagoon floor and associated with gas seepages (average size diameter 0.97 ± 0.19 m and density from 54 to 242 units per 50 m2). In the NB three types of shallow gas features were found in the seismic profile, namely Acoustic Blanking, Turbidity Pinnacles and Intra-sedimentary plumes. The depth varied from the surface to 12.10 ms (around 18.15 m). In both environments, the gas is escaping from the sediment into the water column. The Pockmarks in the CL and the Acoustic Plume features and sediment rich in total sulfur in the NB validate these findings.
This paper describes the procedures and results of an airborne magnetic survey using Unmanned Aerial Vehicle (UAV) conducted to support Search and Rescue (S&R) teams after the failure of a mining tailing dam at the Corrego do Feijão Mine, in the state of Minas Gerais, Southeast Brazil. The accident claimed 270 lives, practically destroying all the mine’s infrastructure. After the accident, the use of a fast, efficient, and cost-effective method to locate preferential sites for the rescue team to work was critical. Due to the difficulty of direct access to the impacted area, and since most of the affected infrastructure consisted of metallic materials, an airborne magnetometer was the logical choice. First, some performance tests were conducted in order to define the survey configurations, such as flight altitude, transect spacing and anomaly’s detectability threshold. After that, task priorities were set, and the survey area divided in small blocks according to their morphological characteristics using aerial photos of the impacted area. The results showed that the system was able to detect all relevant anomalies. The correlation of the anomalies with aerial photogrammetry helped to discard false anomalies, making the whole operation much more efficient. This increased the effectiveness of the S&R teams as well as the planning of the dredging operations by defining the preferential locations for the interventions.
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