Show simple item record

dc.contributor.advisorWalton, Gabriel
dc.contributor.advisorTrainor-Guitton, Whitney
dc.contributor.authorBoyd, David Lane
dc.date.accessioned2019-10-15T17:46:37Z
dc.date.accessioned2022-02-03T13:18:08Z
dc.date.available2019-10-15T17:46:37Z
dc.date.available2022-02-03T13:18:08Z
dc.date.issued2019
dc.identifierBoyd_mines_0052E_11829.pdf
dc.identifierT 8815
dc.identifier.urihttps://hdl.handle.net/11124/173299
dc.descriptionIncludes bibliographical references.
dc.description2019 Fall.
dc.description.abstractTunneling projects in rock are characterized by a high degree of spatial uncertainty, which is due in part to the natural, random (aleatory) variability the rock possesses. Some degree of variability is intrinsic to all rock, and is present due to the complex nature of its deposition or emplacement and subsequent tectonics. This variability is present at multiple spatial scales, from heterogeneous grains to the project scale, where tectonics cause variability in discontinuity properties. As this variability contributes to overall uncertainty in tunneling projects, it is critical to understand and characterize this variability at multiple relevant scales. This research isolated the component of spatial uncertainty associated with aleatory geologic variability and evaluated statistical and geostatistical methods for quantification and characterization of this variability. Geostatistics has been commonly used in natural resource extraction and other data-sparse environments, and has been used extensively in this research as a means by which to better predict, characterize or quantify spatial uncertainty associated with aleatory geologic variability. As the first contribution of this thesis, 2-D covariance maps were generated for rock core specimen photos and were analyzed to identify the number of specimens required in order to adequately represent rock strength. This contribution identified a method by which to quantify this without testing large numbers of specimens at great cost. Next, sequential indicator cosimulation was used to integrate sparse borehole data with a geologist’s interpretation of subsurface lithology, identifying the value added by having a geologist’s interpretation over borehole data alone in uncertainty quantification. This identifies uncertainty in a geologist’s interpretation for use in tunneling projects, whereas geologist interpretations do not typically reflect spatial uncertainty besides boundary uncertainty (besides qualitative indications of confidence in specific parts of geologic boundaries). Finally, indicator kriging was used to quantify uncertainty in ground conditions both prior to and during excavation of the Caldecott Fourth Bore Tunnel in California, USA, demonstrating an approach by which engineers and geologists could quantify uncertainty to inform high-level decision making. The completion of these works provides valuable insight into aleatory variability at multiple spatial scales and demonstrates novel approaches to integrate different types of geotechnical data, including subjective and interpreted, into geostatistical algorithms to better understand spatial uncertainty in the context of tunneling.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado School of Mines. Arthur Lakes Library
dc.relation.ispartof2010-2019 - Mines Theses & Dissertations
dc.rightsCopyright of the original work is retained by the author.
dc.subjectgeostatistics
dc.subjectspatial variability
dc.subjectgeologist interpretation
dc.subjecttunneling
dc.subjectspatial uncertainty
dc.titleApplication of geostatistical methods for the quantification of multiple-scale uncertainty due to aleatory geologic variability, The
dc.typeText
dc.contributor.committeememberSanti, Paul M. (Paul Michael), 1964-
dc.contributor.committeememberMooney, Michael A.
dc.contributor.committeememberSmits, Kathleen M.
thesis.degree.nameDoctor of Philosophy (Ph.D.)
thesis.degree.levelDoctoral
thesis.degree.disciplineGeology and Geological Engineering
thesis.degree.grantorColorado School of Mines


Files in this item

Thumbnail
Name:
Boyd_mines_0052E_11829.pdf
Size:
8.562Mb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record