Abstract

Abstract

Abstract

Abstract

Abstract
In recent years some authors have given a certain amount of attention to towed seismic reflection acquisition systems. Based on some of these works we sought to design and test a system making use of currently available geophones instead of specifically designed sensors as employed in some previous works. Thus, bearing in mind that the geophone's characteristics are achieved in the conditions that they are originally designed to be employed in, i.e., coupled with a spike driven into the ground, we devoted our attention to some of the variables involved in the geophone's performance, namely the total weight, the effect of a spikeless geophone and the surfaces on which the geophone is placed. Previously, we had experimentally verified some variations in the signal response due to coupling geophones in different surface materials, such as hard soil, asphalt and concrete pavement and we noticed that these surface materials were in fact an important factor in the overall response. Hence, these materials, or as we also called them coupling agents, could be employed as a base material in the construction of a mobile seismic acquisition device composed of blocks of a certain size, on which the geophone would be then inserted and thus making it into a spikeless surface towable system. Therefore, various materials were tested in order to select one that could maintain a similar fidelity to that of the spike coupled geophone and thus contribute towards building a more time efficient and towable geophone and block system. Pinging tests revealed variations in the coupling frequency and damping characteristics of each coupling agent and from all of these tested materials one was selected for field comparative tests with the normally planted geophones with spike coupling. Finally a seismic reflection profile was acquired simultaneously with both systems, i.e., spike coupling versus cement block coupled geophones.

Abstract
Geophysical data represent subsoil structure in a specific area and can be used to extract subsoil information for various purposes. In this work we used this data type to detect anomalies/contamination in the subsoil. Our case study was based on data acquired around a landfill and the main objective is identifying contaminated areas as a result of leakage in landfill. This involves the application of statistical methods to detect anomalous values taking into account the whole data set, subdividing it in sublevels in relation to the surface, instead of using a single threshold (as usual). This work combines in the same software package the anomaly statistical analysis and several 3D representations of the results to validate and also helps understanding the final results of the analysis. Given that the original data used in the analysis, resistivity sections, is normally very sparse, a kriging geostatistical process was used to interpolate data in order to provide a volumetric representation of the subsoil in the area, providing a continuous spatial visualization. © 2012 IEEE.