Characterizing, Testing and Modeling Of Highly Sensing Smart Spacer Fluids, Smart Cement And Smart Orthopedic Cast Materials For Multiple Applications

Simple item page
dc.contributor.advisorVipulanandan, Cumaraswamy
dc.contributor.committeeMemberMo, Yi-Lung
dc.contributor.committeeMemberLi, Hong-Yi
dc.contributor.committeeMemberWong, George K.
dc.contributor.committeeMemberMohan, Chandra
dc.creatorMaddi, Sai Anudeep Reddy
dc.date.accessioned2020-06-02T03:16:25Z
dc.date.createdMay 2020
dc.date.issued2020-05
dc.date.submittedMay 2020
dc.date.updated2020-06-02T03:16:26Z
dc.description.abstractThe main focus of this study was to make the fluids and cementitious materials highly sensing to be used for real time monitoring of changes during the installation and entire service life. For optimizing the well cementing, it is important to develop technology to monitor drilling and cementing operation in real time during the well installation to minimize operation delays, failures and ensure safety. In this study, the effects of pressure, temperature and magnetic field strength on the electrical resistivity and rheological properties of a sensing smart spacer fluid modified with iron oxide nanoparticles (nanoFe2O3) were investigated. The spacer fluid rheology was modelled using Bingham-plastic model, Herschel Bulkley model and Vipulanandan model. The electrical resistivity was used as sensing parameter to monitor the percentage of oil cleaning efficiency of the spacer fluid. In this spacer fluid study, the axial flow of the spacer fluid in the annulus was investigated analytically. The shear stresses, velocity profiles, strain profiles and pressure gradients were predicted using the Bingham- Plastic model and were compared to the new rheological model, Vipulanandan model. In this study, the potential of using the smart cement in installation of oil well was tested for real time monitoring using large laboratory models and a field model for a period of 6 years. The laboratory oil well models of 10 ft. deep and the field model of 40 ft. deep were instrumented and monitored for changes in electrical resistivity, curing and stresses over period of 5 years (2000 days). The piezoresistivity of the smart cement response was related to the casing pressure using a nonlinear relationship. The experimental results were also modeled using the artificial neural network (ANN) models, finite element models and compared to the Vipulanandan models. Plaster is the traditional cementious material used for orthopedic casting in the medical industry with need for real time monitoring of setting, strength gain and performance. In this study, electrical measurements are used to monitor and characterize the condition of the cast material in real time. The Orthopedic casting material was modified with conductive filler to make it sensitive and has been tested under various mechanical loadings, temperature and water seepage conditions.
dc.description.departmentCivil and Environmental Engineering, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/10657/6569
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectElectrical Resistivity, Sensing, Cement, Cast Material
dc.titleCharacterizing, Testing and Modeling Of Highly Sensing Smart Spacer Fluids, Smart Cement And Smart Orthopedic Cast Materials For Multiple Applications
dc.type.dcmiText
dc.type.genreThesis
local.embargo.lift2022-05-01
local.embargo.terms2022-05-01
thesis.degree.collegeCullen College of Engineering
thesis.degree.departmentCivil and Environmental Engineering, Department of
thesis.degree.disciplineCivil Engineering
thesis.degree.grantorUniversity of Houston
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
MADDI-DISSERTATION-2020.pdf
Size:
3.23 MB
Format:
Adobe Portable Document Format
Download

License bundle

Now showing 1 - 2 of 2
No Thumbnail Available
Name:
PROQUEST_LICENSE.txt
Size:
4.43 KB
Format:
Plain Text
Description:
Download
No Thumbnail Available
Name:
LICENSE.txt
Size:
1.82 KB
Format:
Plain Text
Description:
Download

Collections

Published ETD Collection