Geostatistical and numerical analysis of flow in a crystalline rock mass
| dc.contributor.advisor | Neuman, Shlomo P. | en |
| dc.contributor.author | Kostner, Albert | |
| dc.creator | Kostner, Albert | en |
| dc.date.accessioned | 2018-02-26T21:15:20Z | |
| dc.date.available | 2018-02-26T21:15:20Z | |
| dc.date.issued | 1993 | |
| dc.identifier.uri | http://hdl.handle.net/10150/626836 | |
| dc.description.abstract | The stochastic continuum approach, as an alternative to the discrete fracture-network approach, is applied to hydraulic conductivity data from fractured crystalline rock at Fanay-Augeres, France. Small-scale measurements are transformed into binary indicator values. Viewing the transformed data as defined over a continuum, the statistical correlation structure of the stochastic process is determined. Estimates of hydraulic conductivity and its probability field are obtained using ordinary and median indicator kriging. Indicator kriging results are input into sequential conditional indicator simulation, generating equally likely sets of hydraulic conductivities. An adjoint-state, finite element inverse model is used to derive the effective hydraulic conductivity of an equivalent homogeneous porous medium. Stochastic realizations of hydraulic conductivities are input into a flow model to study their effect on the variability of resulting hydraulic heads and flow rates. Results show that flow in the fractured medium can be analyzed without any reference to geometric fracture data. | |
| dc.language.iso | en_US | en |
| dc.publisher | The University of Arizona. | en |
| dc.rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. | en |
| dc.title | Geostatistical and numerical analysis of flow in a crystalline rock mass | en_US |
| dc.type | text | en |
| dc.type | Thesis-Reproduction (electronic) | en |
| thesis.degree.grantor | University of Arizona | en |
| thesis.degree.level | masters | en |
| dc.contributor.committeemember | Neuman, Shlomo P. | en |
| thesis.degree.discipline | Graduate College | en |
| thesis.degree.discipline | Hydrology and Water Resources | en |
| thesis.degree.name | M.S. | en |
| dc.description.note | Digitized from paper copies provided by the Department of Hydrology & Atmospheric Sciences. | en |
| refterms.dateFOA | 2018-09-12T02:11:30Z | |
| html.description.abstract | The stochastic continuum approach, as an alternative to the discrete fracture-network approach, is applied to hydraulic conductivity data from fractured crystalline rock at Fanay-Augeres, France. Small-scale measurements are transformed into binary indicator values. Viewing the transformed data as defined over a continuum, the statistical correlation structure of the stochastic process is determined. Estimates of hydraulic conductivity and its probability field are obtained using ordinary and median indicator kriging. Indicator kriging results are input into sequential conditional indicator simulation, generating equally likely sets of hydraulic conductivities. An adjoint-state, finite element inverse model is used to derive the effective hydraulic conductivity of an equivalent homogeneous porous medium. Stochastic realizations of hydraulic conductivities are input into a flow model to study their effect on the variability of resulting hydraulic heads and flow rates. Results show that flow in the fractured medium can be analyzed without any reference to geometric fracture data. |
