Publication Date
8-2021
Date of Final Oral Examination (Defense)
4-1-2021
Type of Culminating Activity
Thesis
Degree Title
Master of Science in Geophysics
Department
Geosciences
Supervisory Committee Chair
Dylan Mikesell, Ph.D.
Supervisory Committee Member
Lee Liberty, M.S.
Supervisory Committee Member
Qifei Niu, Ph.D.
Abstract
Karst environments are characterized by voids, i.e. sinkholes and conduits of varying size that arise from the active dissolution of carbonate rock by acidic groundwater. These voids, whether air-, water-, or soil-filled, can be difficult to image using near-surface geophysical methods due to the limited investigation depths of most active-source methods. In addition, due to the significant effort it takes to collect active-source data, investigators are often unable to monitor spatio-temporal variations in the subsurface. The ability to detect, image, and monitor subsurface voids improves the understanding of processes that create and transform voids, a vitally important insight across a variety of scientifc disciplines and engineering applications, including hydrogeology, geotechnical engineering, planetary science and even issues of national security. Using a 54-element nodal array (1C and 3C sensors), I image the subsurface of the USF GeoPark with ambient noise surface wave tomography. I also use complementary active-source geophysical datasets (e.g. 2D ERT) collected at the GeoPark to constrain and/or validate the tomography results. I address two research questions with this study: (1) How do ambient seismic methods complement active-source near-surface methods? (2) Can ambient noise tomography resolve voids in the karst environment? In this thesis, I discuss my answers to these questions and present the current state of surface wave methods in the karst environment, including the feasibility for utilizing ambient noise methods to monitor spatio-temporal changes in sinkhole and conduit formation. In addition to the ability to use seismic methods for temporal monitoring, ambient noise provides lower frequencies than what are achievable with active-source seismic methods. Using frequencies from 5-28 Hz, ambient noise tomography is able to image deeper into the subsurface (up to 100 m at 5 Hz) than previous active-source seismic studies at the GeoPark field site. This study yields a more robust and simple method to image voids in covered karst environments and a long-term installation of ambient seismic nodes enables future investigations of spatio-temporal variations in void structures.
DOI
https://doi.org/10.18122/td.1832.boisestate
Recommended Citation
Paustian, John B., "Void Hunting: Ambient Noise Tomography for Spatio-Temporal Subsurface Imaging and Monitoring in Karst Environments" (2021). Boise State University Theses and Dissertations. 1832.
https://doi.org/10.18122/td.1832.boisestate