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Author ORCID Identifier

https://orcid.org/0000-0002-9632-1954

AccessType

Open Access Dissertation

Document Type

dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Civil and Environmental Engineering

Year Degree Awarded

2022

Month Degree Awarded

February

First Advisor

Guoping Zhang

Subject Categories

Geotechnical Engineering

Abstract

The exploration of oil/gas in the petroleum industry presents a lot of issues both during and after the drilling process, such as wellbore stability, formation clogging, and cementation. Understanding the chemo-mechanical alterations caused by drilling activities to the surrounding formations has been a crucial part of a successful drilling operation. However, as multi-phases, multi-scales, heterogeneous composites, the mechanical properties of rock can vary significantly with its diverse constituent minerals (e.g., quartz, feldspar, and clay minerals) and sometimes hard to be characterized due to the availability of rock samples (i.e., cylindrical core samples are arduous to acquired especially at deep formations). As such, a newly proposed cross-scaled mechanical characterization technique, big data nanoindentation, was introduced to characterize the mechanical properties of two sandstone samples with distinct morphologies and mineral compositions and investigate the potential factors that influence the mechanical performance of sandstones in the first phase of this research. For unconventional reservoirs (e.g., shale and tight sandstone), to extract the tight gas from the low permeability formations, hydraulic fracturing is a common and mature technique to artificially create flow channels for the tight gas extraction. However, the aqueous fracturing fluid will inevitably interact with clay-rich formations (e.g., shale) and thus weaken the mechanical performance of the shale formation. In the second phase of this study, the big data nanoindentation technique was used to characterize the softening behaviors of shale through a large volume (e.g., hundreds of microns) experimental setup via progressively polishing the softened layers of the sample to quantitively determine the softening rate of the tested shale sample. As such, a novel way to strengthen the mechanical properties of softened shale sample is injection of nanoparticles into the shale formation with drilling fluids. This in-situ injecting process was simulated by a newly developed infiltration setup and then characterized by the big data nanoindentation technique. The results show that the nanoparticles can effectively block the pores/cracks and strengthen the mechanical properties of the shale and the oil-based fluid can be more effective in strengthening the formation than the water-based fluid. Upon the finished drilling process, cement slurry is pumped into the annulus between the formation and casing to support the well wall and ensure the integrity of the wellbore. However, the brittleness of cement paste has been a critical issue as repeated loading-unloading cycles of tensile circumferential or hoop stress will be induced during the hydrofracturing process, which may lead to the failure of entire zonal isolation. As such, in the final phase of this study, a polymerized oilwell cement was characterized by the big data indentation technique. The results well elaborated the functions of emulsified and particulate elastomers in finely tuning the cross-scale properties of the oilwell cement.

DOI

https://doi.org/10.7275/26923770

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