A series of catastrophic floods that have occurred over the last twenty years in Poland brought an urgent need for taking preventive steps to monitor river embankment conditions. The main problem seems to be the development of efficient (i.e. fast and economical) measurements for controlling the condition of river embankments, because the execution of the full range of geotechnical measurements is both lengthy and costly. In this situation, a cheap and quick geophysical survey has been proposed to undertake this purpose. In this article the results of geophysical surveys are described which were performed using geoelectric and electromagnetic methods along a section of the Vistula embankment, located near the Maniów area in the Małopolska province. According to the archival data, this region is situated in a high-risk flooding zone. Three geophysical methods were used to recognize conditions of the levee: (i) Electrical Resistivity Tomography (ERT), (ii) Induced Polarization (IP) and (iii) Electromagnetic Conductivity (EMC). Geoelectrical measurement results were presented in the form of resistivity and polarization cross-sections. Results of conductivity measurement were presented in the form of plots. These parameters effectively supplement geotechnical testing, providing spatial information about the changes within the embankment and its substrate. It allows the prediction of potentially vulnerable areas to water percolation during flooding.
Artificial neural networks method (ANNs) is a common estimation tool used for geophysical applications. Considering borehole data, when the need arises to supplement a missing well log interval or whole logging—ANNs provide a reliable solution. Supervised training of the network on a reliable set of borehole data values with further application of this network on unknown wells allows creation of synthetic values of missing geophysical parameters, e.g., resistivity. The main assumptions for boreholes are: representation of similar geological conditions and the use of similar techniques of well data collection. In the analyzed case, a set of Multilayer Perceptrons were trained on five separate chronostratigraphic intervals of borehole, considered as training data. The task was to predict missing deep laterolog (LLD) logging in a borehole representing the same sequence of layers within the Lublin Basin area. Correlation between well logs data exceeded 0.8. Subsequently, magnetotelluric parametric soundings were modeled and inverted on both boreholes. Analysis showed that congenial Occam 1D models had better fitting of TM mode of MT data in each case. Ipso facto, synthetic LLD log could be considered as a basis for geophysical and geological interpretation. ANNs provided solution for supplementing datasets based on this analytical approach.
This article presents the results of an integrated interpretation of measurements made using Audio-Magnetotellurics and Seismic Reflection geophysical methods. The obtained results were used to build an integrated geophysical model of shallow subsurface cover consisting of Cenozoic deposits, which then formed the basis for a detailed lithological and tectonic interpretation of deeper Mesozoic sediments. Such shallow covers, consisting mainly of glacial Pleistocene deposits, are typical for central and northern Poland. This investigation concentrated on delineating the accurate geometry of Obrzycko Cenozoic graben structure filled with loose deposits, as it was of great importance to the acquisition, processing and interpretation of seismic data that was to reveal the tectonic structure of the Cretaceous and Jurassic sediments which underly the study area. Previously, some problems with estimation of seismic static corrections over similar grabens filled with more recent, low-velocity deposits were encountered. Therefore, a novel approach to estimating the exact thickness of such shallow cover consisting of low-velocity deposits was applied in the presented investigation. The study shows that some alternative geophysical data sets (such as magnetotellurics) can be used to significantly improve the imaging of geological structure in areas where seismic data are very distorted or too noisy to be used alone
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.