The aim of this project was to study the leakage of CO2 in a Geological Carbon Sequestration (GCS) system. To define the GCS system, a tool that is known as an FEP database was used. FEPs are the features, processes and events that develop scenarios for the goal of the study. Combinations of these FEPs can produce thousands of scenarios. However, among all of these scenarios, some are more important than others for leakage. The FEPs that were used as scenario developers were the formation of the liquid flow, the salinity of the formation liquid, diffusion as a process for gas bubble transport and the depth of the reservoir layer. In this study, the leakage path is considered as the presence of a fracture in sealed caprock. The fractures can be modeled using various approaches. Here, I represented the influence of fracture modeling by applying the Equivalent Continuum Method (ECM) and the Dual-Porosity and Multi-continuum methods to leakage. This study suggests that considering groundwater in the aquifer would reduce the leakage of CO2 and that a shallower formation leads to higher leakage. This study can be expanded to future studies by including external FEPs that are related to the FEPs that were used in this study.

Geological carbon dioxide (CO2) sequestration (GCS) in deep saline aquifers is viewed as a viable solution to dealing with the impact of anthropogenic CO2 emissions on global warming. The trapping mechanisms that control GCS include capillary trapping, structural trapping, dissolution trapping, and mineral trapping. Wettability and density-driven convection play an important role in GCS, because wettability significantly affects the efficiency of capillary trapping, and density-driven convection greatly decreases the time scale of dissolution trapping. This work focuses on the role of wettability on multiphase flow in porous media, density-driven convection in porous media, and their implications for GCS in deep saline aquifers. Wettability is a critical control over multiphase fluid flow in porous media. However, our understanding on the wettability heterogeneity of a natural rock and its effect on multiphase fluid flow in a natural rock is limited. This work innovatively models the heterogeneous wettability of a rock as a correlated random field. The realistic wetting condition of a natural rock can be reconstructed with in-situ measurements of wettability on the internal surfaces of the rock. A Bentheimer sandstone was used to demonstrate the workflow to model and reconstruct a wettability field. Relative permeability, capillary pressure-water saturation relation are important continuum-scale properties controlling multiphase flow in porous media. This work employed lattice Boltzmann method to simulate the displacement process. We found that pore-scale surface wettability heterogeneity caused noticeable local scCO2 and water redistributions under less water-wet conditions at the pore scale. At the continuum scale, the capillary pressure-water saturation curve under the heterogeneous wetting condition was overall similar to that under the homogeneous wetting condition. This suggested that the impact of local wettability heterogeneity on the capillary pressure-water saturation curve was averaged out at the entire-sample scale. The only difference was that heterogeneous wettability led to a negative entry pressure at the primary drainage stage under the intermediate-wet condition. The impact of pore-scale wettability heterogeneity was more noticeable on the relative permeability curves. Particularly, the variation of the scCO2 relative permeability curve in the heterogeneous wettability scenario was more significant than that in the homogenous wettability scenario. Results showed that higher wettability heterogeneity (i.e., higher standard deviation and higher correlation length) increased the variations in the CO2/brine relative permeability curves. Dissolution of CO2 into brine is a primary mechanism to ensure the long-term security of GCS. CO2 dissolved in brine increases the CO2-brine solution density and thus can cause downward convection. Onset of density-driven instability and onset of convective dissolution are two critical events in the transition process from a diffusion-dominated regime to a convection-dominated regime. In the laboratory, we developed an empirical correlation between light intensity and in-situ solute concentration. Based on the novel and well-controlled experimental methods, we measured the critical Rayleigh-Darcy number and critical times for the onset of density-driven instability and convective dissolution. To further investigate the impact of permeability heterogeneity on density-driven convection, a three-dimensional (3D) fluidics method was proposed to advance the investigation on density-driven convection in porous media. Heterogeneous porous media with desired spatial correlations were efficiently built with 3D-printed elementary porous blocks. In the experiments, methanol-ethylene-glycol (MEG), was used as surrogate fluid to CO2. The heterogeneous porous media were placed in a transparent tank allowing visual observations. Results showed that permeability structure controlled the migration of MEG-rich water. Permeability heterogeneity caused noticeable uncertainty in dissolution rates and uncertainty in dissolution rates increases with correlation length. To sum up, this work comprehensively employed novel experimental methods and large-scale direct simulations to investigate the sequestration of CO2 in saline aquifers at a pore scale and a continuum scale. The findings advanced our understanding on the role of wettability heterogeneity and permeability heterogeneity on GCS in deep saline aquifers. / Doctor of Philosophy / Global warming caused by anthropogenic CO2 emissions is a pressing issue to address of our time. The storage of CO2 in deep saline aquifers is a promising solution because of saline aquifers' vast storage capacity. Property heterogeneity exists extensively in saline aquifers from a continuum scale to a pore scale. The implications of pore-scale wettability heterogeneity and continuum-scale permeability heterogeneity for the storage of CO2 in saline aquifers are not clear. This work is to employ novel experimental methods and powerful simulation tools to investigate the role of wettability heterogeneity and permeability heterogeneity on the storage of CO2 in saline aquifers. This work measured contact angles on the scanned micro-CT images of a Bentheimer sandstone after a CO2 flooding. A correlated lognormal wettability model was put forward with the statistical information of the contact angle measurements. Simulations on the CO2/brine flow in the Bentheimer sandstone were performed. Results showed that the wettability heterogeneity caused noticeable redistributions of CO2/brine compared to scenarios under homogeneous wettability. Impact of wettability on capillary pressure-water saturation curve was not noticeable because the effects were averaged out through the entire rock sample. The standard deviation and correlation length caused variations on the relative permeabilities. This means that we need to take them into consideration in simulating the migration of CO2 in saline aquifers at a reservoir scale. After CO2 pools beneath the impermeable cap rock, dissolution of CO2 into brine dominates the trapping process. Convection caused by CO2 dissolution can greatly accelerate the dissolution rate. The onset of convection is a critical issue and lack of experimental evidence. This work firstly determined the onset time of instability. To further investigate the heterogeneity on the convection, this work proposed a 3D-print-based method to efficiently build heterogeneous porous media with a designed permeability distribution. The experiments were conducted, and results showed that heterogeneity structure of porous media can cause great variations on the dissolution rate of CO2. The findings of this work advanced our understanding on the migration of CO2 in saline aquifers, provided solid basis for assessment and decision on the storage of CO2 into saline aquifers.

The equatorial Pacific is a dynamic region, characterized by zonal and meridional asymmetries in both the ocean and the atmosphere. The asymmetries in the eastern equatorial Pacific (EEP) reach a maximum in northern hemisphere fall, when southern hemisphere trade winds cross the equator and drive the upwelling of cold, CO₂ and nutrient-rich waters along a shallow thermocline, fueling marine primary production. Interannual perturbations in ocean heat content also result in El Niño or La Niña events, which diminish or amplify these asymmetries. In this dissertation, multi-proxy paleo-records derived from marine sediment cores are used to reconstruct fundamental aspects of the coupled ocean-atmosphere system in the EEP and to evaluate the hypothesis that changes in the seasonal distribution of equatorial insolation, which were primarily controlled by Earth’s precession, influenced the mean state and variability of the EEP in the late Pleistocene. EEP thermocline depth, reconstructed from the δ18O of multiple species of planktic foraminifera that lived at different depths in the water column, was found to oscillate between a La Niña-like and an El Niño-like state on precession timescales, in close phase with equatorial insolation during northern hemisphere late summer/early fall. EEP export production, reflected in sedimentary 231Pa/230Th, was influenced by changes in high latitude nutrient leakage and upwelling and, at times, varied on precession timescales. Glacial increases in EEP deep ocean carbon storage, reconstructed from sedimentary authigenic 238U, occurred independently of changes in local export production. Individual δ18O analyses of the surface-dwelling foraminifera Globigerinoides ruber were used to reconstruct EEP sea-surface variability during the last interglacial and penultimate glacial period. While sea-surface variance was not significantly different from that of the late Holocene, the paleo-record suggests that the strength and frequency of ENSO events varied with changes in equatorial insolation during northern hemisphere late summer/early fall and with EEP thermocline depth.

Australia’s economy is heavily dependent on coal-based energy and greenhouse gas intensive natural resource extraction and processing industries. As part of an international climate change mitigation effort Australia will have to undergo a national transformation to a low emissions society by mid century. Federal and State Governments in Australia, like their counterparts in other major developed economies, have been persuaded that reliance on fossil fuels in stationary energy industries such as electricity generation and minerals processing will be able to continue with the deployment of a value chain of technologies fitted to these installations for capturing carbon dioxide, transporting it to a disposal site, and then injecting it into subsurface geological formations for permanent storage (carbon capture and storage, or CCS). Understanding the likely effectiveness of CCS for reducing greenhouse gas emissions from stationary energy industries is therefore critical to policy formulation for, and management of, Australia’s emissions mitigation effort and national transformation over the decades ahead. / This thesis aims to offer a clearer understanding of the practicalities, limitations and uncertainties surrounding future CCS use in Australia and of the contribution CCS can make to mitigating emissions from the Australian stationary energy sector in the period to 2050. It considers two central questions: Is CCS a realistic option for emissions mitigation in Australia? Are Australian climate policies formulated to facilitate CCS deployment and optimise its potential contribution? The criteria employed in this thesis for answering these questions are restricted to those having an ascertainable causal impact on the timing, pace and ultimate scale of CCS deployment within Australia. The methodology used for the research is grounded in critical approaches and integrated assessment within a holistic, trans-disciplinary paradigm. / This thesis finds that under Australia’s existing climate policy framework it is unrealistic to expect CCS can contribute more than 75 million tonnes of CO2 per annum to emissions mitigation by 2050. Australia does have sufficient potential geological storage resources to expect some environmentally safe CCS infrastructure could be engineered over time, but commencement of large scale build-out is not likely before 2025. When CCS will become a commercial mitigation option in Australia is unpredictable and dependent more on the political economy of climate change than on Australian research, development and demonstration activities. / The thesis also finds that the existing climate policy framework is increasing rather than decreasing the risks to timing and usefulness of CCS even to the level of 75 million tonnes of CO2 per annum by 2050. This thesis concludes that Australian Governments are not developing the institutional capability to oversee a holistic decarbonisation of the stationary energy sector. This capability is required not only to address the risks to CCS deployment but also to prevent market failures that foreclose an optimal contribution from all other potential mitigation technologies. The thesis proposes that an Australian national CCS company be created with responsibility for CCS integration, transport and storage services in order to develop Australian capability rather than that of international corporations.

The bioavailability of iron is limited by the solubility of Fe(III) at circumneutral pH. In the High Nutrient-Low Chlorophyll (HNLC) zones of the ocean, the natural or anthropogenic addition of iron stimulates primary productivity and consumes carbon dioxide. As a result, iron fertilization has been proposed to mitigate anthropogenic carbon emissions and lower global temperatures. The natural sources of iron to the ocean are not fully constrained and include eolian depositions as well as inputs from continental shelf sediments, rivers, hydrothermal vents, and icebergs. Regardless of their source, the effectiveness of iron additions in promoting carbon fixation depends on the presence of organic ligands either natural or produced by microorganisms that stabilize or solubilize Fe(III) at neutral pH. For example, siderophores are well known to be expressed extracellularly by prokaryotes in the photic zones of the oceans to increase the bioavailability of iron. In this dissertation, the production of iron nanoparticles is demonstrated in vent fluids from the 90 North hydrothermal system. These iron nanoparticles may either catalyze the oxidation of sulfide to thiosulfate and produce a potential electron acceptor for microbial respiration or provide a source of iron that stimulates primary production at great distances from the hydrothermal vents. In addition, dissolved iron under the form of soluble organic-Fe(III) complexes is demonstrated to constitute a significant source of iron in estuarine sediments that receive large amounts of particulate iron from flocculation and precipitation at the salinity transition of this estuary. A novel competitive ligand equilibration absorptive cathodic stripping voltammetry (CLE-ACSV) technique reveals that the speciation of iron changes from largely colloidal or particulate in the upper estuary to truly dissolved organic-Fe(III) in the lower estuary. It is also demonstrated that organic-Fe(III) complexes are produced far below the sediment-water interface, suggesting that dissimilatory iron-reducing bacteria may play an important role in their production. These complexes then diffuse across the sediment-water interface and provide a significant source of iron to the continental shelf. The mechanism of reduction of iron oxides by iron-reducing bacteria is not fully understood and presents a unique physiological problem for the organism, as the terminal reductase has to transfer electrons to a solid electron acceptor. In this dissertation, it is demonstrated for the first time using random mutagenesis that the respiration of solid Fe(III) oxides by Shewanella oneidensis, a model iron-reducing prokaryote, first proceeds through a non-reductive dissolution step involving organic ligands that are released extracellularly by the cells. These soluble complexes are then reduced by the organism to produce Fe(II) and recycle the ligand for additional solubilization. Incubations with deletion mutants of the proteins involved in the respiration of Fe(III) revealed that the type-II secretion system, which translocates proteins on the outer membrane of gram-negative bacteria, is involved in the production of organic-Fe(III) complexes by secreting an endogenous iron-solubilizing ligand or a protein involved in the biosynthesis of this ligand on the outer membrane. In addition, periplasmic decaheme cytochromes produced by Shewanella appear to be involved in the mechanism of production of the endogenous organic ligand either directly or through a sensing mechanism that controls its production. In turn, two decaheme cytochromes positioned on the outer-membrane and hypothesized to be involved in the electron transfer to the mineral surface do not appear to be involved in the solubilization mechanism, suggesting either that the cells regulate the ligand production via periplasmic sensing systems or that these cytochromes are not involved in the solubilization mechanism. Altogether this research shows the production of organic-Fe(III) complexes in sediments generates a significant flux of dissolved iron to support primary production in continental shelf waters and that these complexes may be partly produced by iron-reducing bacteria. Indeed, experiments with a model organism demonstrate dissimilatory iron reducing bacteria produce endogenous organic ligands with high iron-binding constants to non-reductively solubilize iron oxides during the anaerobic respiration of iron oxides. The organic ligand is apparently recycled several times to minimize the energy cost associated with its biosynthesis. These findings demonstrate that the solubilization of iron oxides by organic ligands may be an important, yet underappreciated process in aquatic systems.

Both physical circulation and biogeochemical characteristics are unique in the Southern Ocean (SO) region, and are fundamentally different from those of the northern hemisphere. Moreover, according to previous research, the oceanic response to the trend of the Southern Annual Mode (SAM) has profound impacts on the future oceanic uptake of carbon dioxide in the SO. In other words, the climate and circulation of the SO are strongly coupled to the overlying atmospheric variability. However, while we have understanding on the SO physical circulation and have the ability to predict the future changes of the SO climate and physical processes, the link between the SO physical processes, the air-sea carbon flux, and correlated climate variability remains unknown. Even though scientists have been studying the spatial and temporal variability of the SO carbon flux and the associated biogeochemical processes, the spatial patterns and the magnitudes of the air-sea carbon flux do not agree between models and observations. Therefore, in this study, we utilized a modified version of a general circulation model (GCM) to performed realistic simulations of the SO carbon on seasonal to interannual timescales, and focused on the crucial physical and biogeochemical processes that control the carbon flux. The spatial pattern and the seasonal cycle of the air-sea carbon dioxide flux is calculated, and is broadly consistent with the climatological observations. The variability of air-sea carbon flux is mainly controlled by the gas exchange rate and the partial pressure of carbon dioxide, which is in turn controlled by the compensating changes in temperature and dissolved inorganic carbon. We investigated the seasonal variability of dissolved inorganic carbon based on different regional processes. Furthermore, we also investigated the dynamical adjustment of the surface carbon flux in response to the different gas exchange parameterizations, and conclude that parameterization has little impact on spatially integrated carbon flux. Our simulation well captured the SO carbon cycle variability on seasonal to interannual timescales, and we will improve our model by employ a better scheme of nutrient cycle, and consider more nutrients as well as ecological processes in our future study.

Under current technical levels and industrial systems, geological carbon sequestration (GCS) is a viable solution to maintain and further reduce carbon dioxide (CO2) concentration and ensure energy security simultaneously. The pre-injection formation characterization and post-injection CO2 monitoring, verification, and accounting (MVA) are two critical and challenging tasks to guarantee the sequestration effect. The tasks can be accomplished using core analyses and well-logging technologies, which complement each other to produce the most accurate and sufficient subsurface information for pore-scale and reservoir-scale studies. In recent years, the unprecedented data sources, increasing computational capability, and the developments of machine learning (ML) and deep learning (DL) algorithms provide novel perspectives for expanding the knowledge from data, which can capture highly complex nonlinear relationships between multivariate inputs and outputs. This work applied ML and DL methods to GCS-related studies at pore and reservoir scales, including digital rock physics (DRP) and the well-logging data interpretation and analysis. DRP provides cost-saving and practical core analysis methods, combining high-resolution imaging techniques, such as the three-dimensional (3D) X-ray computed tomography (CT) scanning, with advanced numerical simulations. Image segmentation is a crucial step of the DRP framework, affecting the accuracy of the following analyses and simulations. We proposed a DL-based workflow for boundary and small target segmentation in digital rock images, which aims to overcome the main challenge in X-ray CT image segmentation, partial volume blurring (PVB). The training data and the model architecture are critical factors affecting the performance of supervised learning models. We employed the entropy-based-masking indicator kriging (IK-EBM) to generate high-quality training data. The performance of IK-EBM on segmentation affected by PVB was compared with some commonly used image segmentation methods on the synthetic data with known ground truth. We then trained and tested the UNet++ model with nested architecture and redesigned skip connections. The evaluation metrics include the pixel-wise (i.e. F1 score, boundary-scaled accuracy, and pixel-by-pixel comparison) and physics-based (porosity, permeability, and CO2 blob curvature distributions) accuracies. We also visualized the feature maps and tested the model generalizations. Contact angle (CA) distribution quantifies the rock surface wettability, which regulates the multiphase behaviors in the porous media. We developed a DL-based CA measurement workflow by integrating an unsupervised learning pipeline for image segmentation and an open-source CA measurement tool. The image segmentation pipeline includes the model training of a CNN-based unsupervised DL model, which is constrained by feature similarity and spatial continuity. In addition, the over-segmentation strategy was adopted for model training, and the post-processing was implemented to cluster the model output to the user-desired target. The performance of the proposed pipeline was evaluated using synthetic data with known ground truth regarding the pixel-wise and physics-based evaluation metrics. The resulting CA measurements with the segmentation results as input data were validated using manual CA measurements. The GCS projects in the Illinois Basin are the first large-scale injection into saline aquifers and employed the latest pulsed neutron tool, the pulsed neutron eXtreme (PNX), to monitor the injected CO2 saturation. The well-logging data provide valuable references for the formation evaluation and CO2 monitoring in GCS in saline aquifers at the reservoir scale. In addition, data-driven models based on supervised ML and DL algorithms provide a novel perspective for well-logging data analysis and interpretation. We applied two commonly used ML and DL algorithms, support vector machine regression (SVR) and artificial neural network (ANN), to the well-logging dataset from GCS projects in the Illinois Basin. The dataset includes the conventional well-logging data for mineralogy and porosity interpretation and PNX data for CO2 saturation estimation. The model performance was evaluated using the root mean square error (RMSE) and R2 score between model-predicted and true values. The results showed that all the ML and DL models achieved excellent accuracies and high efficiency. In addition, we ranked the feature importance of PNX data in the CO2 saturation estimation models using the permutation importance algorithm, and the formation sigma, pressure, and temperature are the three most significant factors in CO2 saturation estimation models. The major challenge for the CO2 storage field projects is the large-scale real-time data processing, including the pore-scale core and reservoir-scale well-logging data. Compared with the traditional data processing methods, ML and DL methods achieved accuracy and efficiency simultaneously. This work developed ML and DL-based workflows and models for X-ray CT image segmentation and well-logging data interpretations based on the available datasets. The performance of data-driven surrogate models has been validated regarding comprehensive evaluation metrics. The findings fill the knowledge gap regarding formation evaluation and fluid behavior simulation across multiple scales, ensuring sequestration security and effect. In addition, the developed ML and DL workflows and models provide efficient and reliable tools for massive GCS-related data processing, which can be widely used in future GCS projects. / Doctor of Philosophy / Geological carbon sequestration (GCS) is the solution to ease the tension between the increasing carbon dioxide (CO2) concentrations in the atmosphere and the high dependence of human society on fossil energy. The sequestration requires the injection formation to have adequate storage capability, injectivity, and impermeable caprock overlain. Also, the injected CO2 plumes should be monitored in real-time to prevent any migration of CO2 to the surface. Therefore, pre-injection formation characterization and post-injection CO2 saturation monitoring are two critical and challenging tasks to guarantee the sequestration effect and security, which can be accomplished using the combination of pore-scale core analyses and reservoir-scale well-logging technologies. This work applied machine learning (ML) and deep learning (DL) methods to GCS-related studies across multiple spatial scales. We developed supervised and unsupervised DL-based workflows to segment the X-ray computed-tomography (CT) image of digital rocks for the pore-scale studies. Image segmentation is a crucial step in the digital rock physics (DRP) framework, and the following analyses and simulations are conducted on the segmented images. We also developed ML and DL models for well-logging data interpretation to analyze the mineralogy and estimate CO2 saturation. Compared with the traditional well-logging analysis methods, which are usually time-consuming and prior knowledge-dependent, the ML and DL methods achieved comparable accuracy and much shorter processing time. The performance of developed workflows and models was validated regarding comprehensive evaluation metrics, achieving excellent accuracies and high efficiency simultaneously. We are at the early stage of CO2 sequestration, and relevant knowledge and tools are inadequate. In addition, the main challenge of CO2 sequestration field projects is the large-scale and real-time data processing for fast decision-making. The findings of this dissertation fill the knowledge gap in GCS-related formation evaluation and fluid behavior simulations across multiple spatial scales. The developed ML and DL workflows provide efficient and reliable tools for massive data processing, which can be widely used in future GCS projects.

The dependency on fossil fuels faces resource limitations and sustainability concerns. This situation requires new strategies for greenhouse gas emission management and the development of new sources of energy. This thesis explores fundamental concepts related to carbon geological storage, including CO2-CH4 replacement in hydrate-bearing sediments. In particular it addresses the following phenomena: - Interfacial tension and contact angle in CO2-water-mineral and CH4-water-mineral systems. These data are needed to upscale pore phenomena through the sediment porous network, to define multiphase flow characteristics in enhanced gas recovery operations, and to optimize the injection and storage CO2 in geological formations. - Coupled processes and potential geomechanical implications associated to CH4-CO2 replacement in hydrate bearing sediments. Results include physical monitoring data gathered for CH4 hydrate-bearing sediments during and after CO2 injection. - Performance of cap rocks as trapping structures for CO2 injection sites. This study focuses on clay-CO2-water systems and CO2 breakthrough through highly compacted fine-grained sediments. Long term experiments help evaluate different sediments according to their vulnerability to CO2, predict the likelihood and time-scale of breakthrough, and estimate consequent CO2 leaks.

Indiana University-Purdue University Indianapolis (IUPUI) / The shale and mudstone directly superjacent to Desmoinesian coal seams of southern Indiana (Springfield, Houchin Creek, Survant, and Seelyville coals) were initially deposited under marine waters and are shown to exhibit high concentrations of organic carbon, sulfur and redox-sensitive metals (Mo, V, Ni, Fe, and U) that were sequestered during times of benthic anoxia and intermittent to sustained euxinia (anoxic and sulfidic). Strata upsection display geochemical signatures that indicate increasingly oxic and nearshore sedimentation that mirrors cyclothemic sequence stratigraphic trends Carbon source, nearshore and offshore proximity, freshwater and marine influence, and redox conditions of the epeiric sea overlying southern Indiana during the Late Middle Pennsylvanian were identified and tracked throughout the deposition of four drill cores of the Petersburg, Linton and Staunton Formations. Carbon, nitrogen, and sulfur data (total organic carbon [TOC], total nitrogen [TN], and total sulfur [TS]); paleoredox proxies ([Mo/Al], [V/Al], [Th/U], [Fetot/Al]); organic carbon isotopes (δ13Corg); and detrital influx concentrations (Zr) were all used in conjunction with lithological and paleontological interpretations to better understand the mode of deposition in this unique midcontinent ancient epeiric sea. Geochemical results when combined with lithologic and paleontologic interpretations reveal a dynamic environmental system where water column geochemistry varies with the influence of variable magnitudes of epeiric seawater flooding on the extensive peatlands of equatorial Late Middle Pennsylvanian southern Indiana.

With rising concentrations of CO₂ in the Earth's atmosphere causing concern about climate change, many solutions are being presented to decrease emissions. One of the proposed solutions is to sequester excess CO₂ in geological formations such as basalt. The deep subsurface is known to harbor much of the microbial biomass on earth and questions abound as to how this deep life is going to respond to the injection of CO₂. Many studies have used model microorganisms to demonstrate the ability of microbes to aid in the safe, permanent sequestration of CO₂ in the subsurface. The objective of this research is to characterize the microbial community present in the basalts at the Wallula pilot carbon sequestration well prior to the injection of CO₂ and then perform laboratory studies to determine how the native microbial community will respond to carbon sequestration conditions. Six samples were collected from the Wallula pilot well prior to the injection of CO₂ into the system. The microorganisms in these samples were characterized by pyrosequencing of 16S rRNA genes, revealing a community dominated by the Proteobacteria, Firmicutes, and Actinobacteria. The organisms detected were related to microbes known to metabolize hydrogen, sulfur, and single carbon compounds. These microorganisms may be stimulated in formations located at the fringe of the pool of injected CO₂. Laboratory studies revealed that the native microbial community suffered a two order of magnitude loss of population upon exposure to CO₂ under carbon sequestration conditions. The community also shifted from being dominated by Proteobacteria prior to CO₂ exposure to being dominated by Firmicutes after exposure. Specifically, the genus Alkaliphilus, which was previously undetected, appeared after CO₂ exposure and became dominant. The dominance of Alkaliphilus, along with other rare organisms which did not compose a majority of the population prior to the introduction of CO₂ to the system, indicates that members of the rare biosphere may be better adapted to changing environmental conditions specific to CO₂ sequestration than other indigenous cells. Thus, the rare biosphere should be examined closely as part of any environmental study, as these minority microorganisms may be the first indication of perturbation or impact. / Graduation date: 2013