3D imaging of quarry materials using electrical soundings View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-11

AUTHORS

Abderrahmane Bouguern, Karim Allek, Mohamed Khalifa, Djamal Boubaya

ABSTRACT

In order to satisfy a need for aggregates required to build a section of the Algeria East–West Highway, a geophysical study was carried out. Seventy-five soundings were conducted in three different sectors, with twenty-five soundings per sector. The goal of the investigation is to study the deep limestone. The chosen method is sensitive to the formation types that characterize the area under investigation made of high-resistivity limestone and more conductive marls. The study site is located near Didouche Mourad city (eastern Algeria). Measurements were achieved using a Shlumberger device whose AB line length is equal to 650 m. Erroneous values were eliminated using the median filter. To invert the electrical sounding, the “smoothed model” technique was used. Based on the electrical sounding interpretation, we ended up with several conclusions. They can be summarized as follows: The electrical sounding method seems to have solved the problem raised from the beginning. Indeed, the electrical resistivity contrast between the limestone and the surrounding marl formations was very useful in precisely determining their geometry and evaluating their extension, depth and thickness. Sector 1 has an appreciable limestone thickness in its central part. Sector 2 indicates the presence of a substantially uniform limestone layer over almost the entire site. The layer’s small depth (a few meters) and its relative important thickness (50 m on average) make this sector very promising. Sector 3 is the least favorable in terms of limestone presence. Aggregate reserves in the first two sectors seem interesting. More... »

PAGES

9

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s41207-017-0047-4

DOI

http://dx.doi.org/10.1007/s41207-017-0047-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1093027985


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