Date of Award

Winter 2-2015

Embargo Period

7-26-2020

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Civil and Environmental Engineering

Advisor(s)

Mitchell Small

Second Advisor

Athanasios Karamalidis

Abstract

Geological carbon sequestration is considered a promising initial option to slow or reduce global atmospheric CO2 concentrations. To demonstrate that the implementation of carbon sequestration is safe and effective as a greenhouse gas control technology, characterization and monitoring of geochemical and geophysical effects of CO2 leakage from sequestration reservoirs is crucial. A multimodel predictive system (MMoPS) has been developed to predict CO2 solubility in brine more accurately, so that storage capacity and cost estimates could be improved. The CO2 leakage level is characterized through an assessment of the integrity and permeability of the caprock inferred from pressure measurements in the injection zone using a Bayesian approach. The detection power of pressure monitoring is evaluated using the expected distribution of pressure increases in the injection zone for permeable vs. impermeable caprock cases. The distributions of detection power using seismic travel time measurements at different CO2 leakage levels are obtained using a statistical analysis and test. The methodology and results in this work should improve our ability to understand the storage reservoir chemistry and the statistical performance of the sole pressure or seismic monitoring, which could be integrated into a monitoring network, combining multiple monitoring techniques for CO2 leakage detection.

Available for download on Sunday, July 26, 2020

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