Publications

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Dissolved CO2 in the subsurface resulting from geological CO2 storage may react with minerals in fractured rocks, confined aquifers, or faults, resulting in mineral precipitation and dissolution. The overall rate of reaction can be affected by coupled processes including hydrodynamics, transport, and reactions at the (sub) pore-scale. In this work pore-scale modeling of coupled fluid flow, reactive transport, and heterogeneous reactions at the mineral surface is applied to account for permeability alterations caused by precipitation-induced pore-blocking. This work is motivated by observations of CO2 seeps from a natural CO2 sequestration analog, Crystal Geyser, Utah. Observations along the surface exposure of the Little Grand Wash fault indicate the lateral migration of CO2 seep sites (i.e., alteration zones) of 10–50 m width with spacing on the order of ~100 m over time. Sandstone permeability in alteration zones is reduced by 3–4 orders of magnitude by carbonate cementation compared to unaltered zones. One granular porous medium and one fracture network systems are used to conceptually represent permeable porous media and locations of conduits controlled by fault-segment intersections and/or topography, respectively. Simulation cases accounted for a range of reaction regimes characterized by the Damköhler (Da) and Peclet (Pe) numbers. Pore-scale simulation results demonstrate that combinations of transport (Pe), geochemical conditions (Da), solution chemistry, and pore and fracture configurations contributed to match key patterns observed in the field of how calcite precipitation alters flow paths by pore plugging. This comparison of simulation results with field observations reveals mechanistic explanations of the lateral migration and enhances our understanding of subsurface processes associated with the CO2 injection. In addition, permeability and porosity relations are constructed from pore-scale simulations which account for a range of reaction regimes characterized by the Da and Pe numbers. The functional relationships obtained from pore-scale simulations can be used in a continuum scale model that may account for large-scale phenomena mimicking lateral migration of surface CO2 seeps.

Shales have small pore and throat sizes ranging from nano to micron scales, low porosity and limited permeability. The poor permeability and complex pore connectivity of shales pose technical challenges to (a) understanding flow and transport mechanisms in such systems and, (b) in predicting permeability changes under dynamic saturation conditions. This study presents quantitative experimental evidence of the migration of water through a generic shale core plug using micro CT imaging. In addition, in-situ measurements of gas permeability were performed during counter-current spontaneous imbibition of water in nano-darcy permeability Marcellus and Haynesville core plugs. It was seen that water blocks severely reduced the effective permeability of the core plugs, leading to losses of up to 99.5% of the initial permeability in experiments lasting 30 days. There was also evidence of clay swelling which further hindered gas flow. When results from this study were compared with similar counter-current gas permeability experiments reported in the literature, the initial (base) permeability of the rock was found to be a key factor in determining the time evolution of effective gas permeability during spontaneous imbibition. With time, a recovery of effective permeability was seen in the higher permeability rocks, while becoming progressively detrimental and irreversible in tighter rocks. These results suggest that matrix permeability of ultra-tight rocks is susceptible to water damage following hydraulic fracturing stimulation and, while shut-in/soaking time helps clearing-up fractures from resident fluid, its effect on the adjacent matrix permeability could be detrimental.

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Coupled reservoir and geomechanical simulations are significantly important to understand the long-term behavior of geologic carbon storage (GCS) systems. In this study, we performed coupled fluid flow and geomechanical modeling of CO₂ storage using available field data to (1) validate our existing numerical model and (2) perform parameter estimation via inverse modeling to identify the impact of key geomechanical (Young's modulus and Biot's coefficient) and hydrogeological (permeability and anisotropy ratio) properties on surface uplift and the pore pressure buildup at In Salah in Algeria. Furthermore, two sets of surface uplift data featuring low and high uplifts above two injection wells and the maximum change in the pore pressure due to CO₂ injection were used to constrain the inverse model.

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Multiphase flow in capillary regimes is a fundamental process in a number of geoscience applications. The ability to accurately define wetting characteristics of porous media can have a large impact on numerical models. In this paper, a newly developed automated three-dimensional contact angle algorithm is described and applied to high-resolution X-ray microtomography data from multiphase bead pack experiments with varying wettability characteristics. The algorithm calculates the contact angle by finding the angle between planes fit to each solid/fluid and fluid/fluid interface in the region surrounding each solid/fluid/fluid contact point. Results show that the algorithm is able to reliably compute contact angles using the experimental data. The in situ contact angles are typically larger than flat surface laboratory measurements using the same material. Wetting characteristics in mixed-wet systems also change significantly after displacement cycles.

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Characterizing subsurface properties is crucial for reliable and cost-effective groundwater supply management and contaminant remediation. With recent advances in sensor technology, large volumes of hydrogeophysical and geochemical data can be obtained to achieve high-resolution images of subsurface properties. However, characterization with such a large amount of information requires prohibitive computational costs associated with “big data” processing and numerous large-scale numerical simulations. To tackle such difficulties, the principal component geostatistical approach (PCGA) has been proposed as a “Jacobian-free” inversion method that requires much smaller forward simulation runs for each iteration than the number of unknown parameters and measurements needed in the traditional inversion methods. PCGA can be conveniently linked to any multiphysics simulation software with independent parallel executions. In this paper, we extend PCGA to handle a large number of measurements (e.g., 106 or more) by constructing a fast preconditioner whose computational cost scales linearly with the data size. For illustration, we characterize the heterogeneous hydraulic conductivity (K) distribution in a laboratory-scale 3-D sand box using about 6 million transient tracer concentration measurements obtained using magnetic resonance imaging. Since each individual observation has little information on the K distribution, the data were compressed by the zeroth temporal moment of breakthrough curves, which is equivalent to the mean travel time under the experimental setting. Only about 2000 forward simulations in total were required to obtain the best estimate with corresponding estimation uncertainty, and the estimated K field captured key patterns of the original packing design, showing the efficiency and effectiveness of the proposed method.

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