SEISMIC LANDSTREAMER FOR URBAN UNDERGROUND INFRASTRUCTURE PLANNING PROJECTS – A CASE STUDY FROM VARBERG
2015 (English)Conference paper, Abstract (Refereed)
As a part of the TRUST (TRansparent Underground STructure), an industry-academia partnership project, a multicomponent broadband based on digital sensors, seismic landstreamer system has been developed. The system is particularly geared for noisy environments and areas where high-resolution images of the subsurface are needed. The streamer has been tested in various locations (e.g. parts of Stockholm Bypass project) and for various other targets one of which was the planned underground train tunnel in the city of Varberg, southwest Sweden. Potential targets were bedrock surface and weakness zones, such as fracture and shear zones. During nearly three weeks, 25 seismic profiles totally about 7.5 km long, using a source and receiver spacing of 2-4 m, were acquired. A novel approach in the data acquisition was to combine the landstreamer with wireless sensors in areas where accessibility was restricted and, to provide crucial information seismic sensors had to still be placed but not in the form of streamer. Although the area is highly noisy especially in the city center and areas close to the train station, the seismic data successfully allowed mapping the bedrock surface and its undulation and areas where potentially rocks have poor quality. Based on these results and modeling work conducted in the area, a detailed and complementary investigation has been recommended and optimal locations for a second phase drilling campaign have been identified. Complementary to this study, new approaches to quantify uncertainty in the seismic data, models and interpretations were developed and tested. The uncertainty estimates and the seismic results are currently being used in BIM (building information modeling) together with geotechnical and geological observations and serve as one of the main ingredients for the planning and construction of the tunnel.
Place, publisher, year, edition, pages
Stockholm: BeFo , 2015.
IdentifiersURN: urn:nbn:se:uu:diva-286581OAI: oai:DiVA.org:uu-286581DiVA: diva2:921759