Kue Young Kim

Modeling of Spatiotemporal Thermal Response to CO 2 Injection in Saline Formations: Interpretation for Monitoring

We evaluated the thermal processes with numerical simulation models that include processes of solid NaCl precipitation, buoyancy-driven multiphase SCCO2 migration, and potential non-isothermal effects. Simulation results suggest that these processes—solid NaCl precipitation, buoyancy effects, JT cooling, water vaporization, and exothermic SCCO2 reactions—are strongly coupled and dynamic. In addition, we performed sensitivity studies to determine how geologic (heat capacity, brine concentration, porosity, the magnitude and anisotropy of permeability, and capillary pressure) and operational (injection rate and injected SCCO2 temperature) parameters may affect these induced thermal disturbances. Overall, a fundamental understanding of potential thermal processes investigated through this research will be beneficial in the collection and analysis of temperature signals collectively measured from monitoring wells.

A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data model

In this study, a data-driven method for predicting CO2 leaks and associated concentrations from geological CO2 sequestration is developed. Several candidate models are compared based on their reproducibility and predictive capability for CO2 concentration measurements from the Environment Impact Evaluation Test (EIT) site in Korea. Based on the data mining results, a one-dimensional solution of the advective-dispersive equation for steady flow (i.e., Ogata-Banks solution) is found to be most representative for the test data, and this model is adopted as the data model for the developed method. In the validation step, the method is applied to estimate future CO2 concentrations with the reference estimation by the Ogata-Banks solution, where a part of earlier data is used as the training dataset. From the analysis, it is found that the ensemble mean of multiple estimations based on the developed method shows high prediction accuracy relative to the reference estimation. In addition, the majority of the data to be predicted are included in the proposed quantile interval, which suggests adequate representation of the uncertainty by the developed method. Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model. The proposed method is not confined to estimations of CO2 concentration and may be applied to various real-time monitoring data from subsurface sites to develop automated control, management or decision-making systems.

Two-phase flow visualization under reservoir conditions for highly heterogeneous conglomerate rock: A core-scale study for geologic carbon storage

Geologic storage of carbon dioxide (CO2) is considered a viable strategy for significantly reducing anthropogenic CO2 emissions into the atmosphere; however, understanding the flow mechanisms in various geological formations is essential for safe storage using this technique. This study presents, for the first time, a two-phase (CO2 and brine) flow visualization under reservoir conditions (10 MPa, 50 °C) for a highly heterogeneous conglomerate core obtained from a real CO2 storage site. Rock heterogeneity and the porosity variation characteristics were evaluated using X-ray computed tomography (CT). Multiphase flow tests with an in-situ imaging technology revealed three distinct CO2 saturation distributions (from homogeneous to non-uniform) dependent on compositional complexity. Dense discontinuity networks within clasts provided well-connected pathways for CO2 flow, potentially helping to reduce overpressure. Two flow tests, one under capillary-dominated conditions and the other in a transition regime between the capillary and viscous limits, indicated that greater injection rates (potential causes of reservoir overpressure) could be significantly reduced without substantially altering the total stored CO2 mass. Finally, the capillary storage capacity of the reservoir was calculated. Capacity ranged between 0.5 and 4.5%, depending on the initial CO2 saturation.

Dynamic Behavior of CO2 in a Wellbore and Storage Formation: Wellbore-Coupled and Salt-Precipitation Processes during Geologic CO2 Sequestration

For investigating the wellbore flow process in CO2 injection scenarios, coupled wellbore-reservoir (WR) and conventional equivalent porous media (EPM) models were compared with each other. In WR model, during the injection, conditions for the wellbore including pressure and temperature were dynamically changed from the initial pressure (7.45–8.33 MPa) and temperature (52.0–55.9°C) of the storage formation. After 3.35 days, the wellbore flow reached the steady state with adiabatic condition; temperature linearly increased from the well-head (35°C) to the well-bottom (52°C). In contrast, the EPM model neglecting the wellbore process revealed that CO2 temperature was consistently 35°C at the screen interval. Differences in temperature from WR and EPM models resulted in density contrast of CO2 that entered the storage formation (~200 and ~600 kg/m3, resp.). Subsequently, the WR model causing greater density difference between CO2 and brine revealed more vertical CO2 migration and counterflow of brine and also developed the localized salt-precipitation. Finally, a series of sensitivity analyses for the WR model was conducted to assess how the injection conditions influenced interplay between flow system and the localized salt-precipitation in the storage formation.

Un método regresión por submuestreo para estimar el estado cualitativo y cuantitativo del agua subterránea

A subsample aggregating (subagging) regression (SBR) method for the analysis of groundwater data pertaining to trend-estimation-associated uncertainty is proposed. The SBR method is validated against synthetic data competitively with other conventional robust and non-robust methods. From the results, it is verified that the estimation accuracies of the SBR method are consistent and superior to those of other methods, and the uncertainties are reasonably estimated; the others have no uncertainty analysis option. To validate further, actual groundwater data are employed and analyzed comparatively with Gaussian process regression (GPR). For all cases, the trend and the associated uncertainties are reasonably estimated by both SBR and GPR regardless of Gaussian or non-Gaussian skewed data. However, it is expected that GPR has a limitation in applications to severely corrupted data by outliers owing to its non-robustness. From the implementations, it is determined that the SBR method has the potential to be further developed as an effective tool of anomaly detection or outlier identification in groundwater state data such as the groundwater level and contaminant concentration.RésuméUne méthode de régression par sous-échantillonnage et agrégation (subbaging) (SBR) pour l’analyse des données relatives aux eaux souterraines se rapportant à l’évaluation des tendances associée à l’incertitude est proposée. La méthode SBR est validée en considérant des données synthétiques de manière compétitive vis-à-vis de méthodes conventionnelles robustes et non robustes. A partir des résultats, on vérifie que les précisions estimées de la méthode SBR sont cohérentes et supérieures à celles des autres méthodes, et que les incertitudes sont estimées de manière raisonnable : les autres ne disposent pas d’option d’analyse des incertitudes. Pour avancer dans le processus de validation, des données réelles relatives aux eaux souterraines sont utilisées et analysées en les comparant au processus gaussien de régression (GPR). Dans tous les cas, la tendance et les incertitudes associées sont estimées de manière raisonnable à la fois par SBR et par GPR, indépendamment des données gaussiennes ou non gaussiennes biaisées. Cependant, on s’attend à ce que le GPR ait une limitation dans ses applications à des données fortement entachées de valeurs aberrantes en raison de sa non-robustesse. A partir des mises en œuvre, on détermine que la méthode SBR a un potentiel pour faire l’objet de développement en tant qu’outil efficace de détection d’anomalies ou d’identification de valeurs aberrantes dans des données relatives à l’état des eaux souterraines telles que le niveau piézométrique ou la concentration en contaminants.ResumenSe propone un método de regresión de agregación de submuestreos (SBR) para el análisis de datos de agua subterránea relacionados con la incertidumbre asociada a la estimación de tendencias. El método SBR se valida competitivamente frente a los datos sintéticos de otros métodos robustos y no robustos convencionales. A partir de los resultados, se verifica que las precisiones de estimación del método SBR son consistentes y superiores a las de otros métodos, y las incertidumbres son razonablemente estimadas; los otros no tienen la opción del análisis de incertidumbres. Además para validar, se emplean los datos reales del agua subterránea y se analizan comparativamente con la regresión del proceso gaussiano (GPR). En todos los casos, la tendencia y las incertidumbres asociadas son razonablemente estimadas tanto por SBR como por GPR, independientemente de los datos gaussianos sesgados o no gaussianos. Sin embargo, se espera que GPR tenga una limitación en aplicaciones a datos gravemente corrompidos por valores atípicos debido a su no robustez. A partir de las implementaciones, se determina que el método SBR tiene el potencial de ser desarrollado como una herramienta eficaz de detección de anomalías o identificación de valores atípicos en datos de agua subterránea tales como el nivel de agua subterránea y la concentración de contaminantes.摘要本文提出了有关涉及趋势-估算不确定性分析地下水数据的子样品集聚(subagging) 回归法。相对于其它常规的强健的和非强健的方法,子样品集聚回归法经过了综合数据的验证。结果证实,子样品集聚回归法的估算精度始终如一,优于其它方法的估算精度,合理地估算了不确定性;其它方法没有不确定性选项。为了进一步进行验证,采用实际的地下水数据,并与高斯过程回归法对这些数据进行了对比分析。在所有情况中,无论是否高斯或者非高斯偏斜数据,利用子样品集聚回归法和高斯过程回归法对趋势和相关不确定性进行了合理估算。然而,预计高斯过程回归法在应用中对由于异常值的非-稳健性造成的严重损坏数据有局限。从实施的情况看,子样品集聚回归法作为地下水状况数据诸如地下水位和污染物含量异常探测或异常值识别的一个有效工具,具有进一步发展的潜力。ResumoUm método de regressão (RAS) por agregação de subamostra (subagging) foi proposto para a análise de dados de águas subterrâneas referentes à incerteza associada à estimativa de tendência. O método RAS foi validado contra dados sintéticos competitivamente com outros métodos convencionais robustos e não robustos. A partir dos resultados, verificou-se que as precisões de estimativa do método RAS foram consistentes e superiores às de outros métodos, e as incertezas foram razoavelmente estimadas; os demais não possuem opção de análise de incerteza. Para validar além, os dados de águas subterrâneas reais foram empregados e analisados comparativamente com a regressão de processo Gaussiano (RPG). Para todos os casos, a tendência e as incertezas associadas foram razoavelmente estimadas tanto pela RAS quanto pela RPG, independentemente de dados Gaussianos ou não Gaussianos. No entanto, espera-se que a RPG tenha uma limitação nas aplicações de dados gravemente corrompidos por dados discrepantes devido à sua não robustez. A partir das implementações, foi determinado que o método RAS tem potencial para ser desenvolvido como uma ferramenta eficaz de detecção de anomalias ou identificação de valores espúrios em dados de águas subterrâneas, tais como o nível das águas subterrâneas e a concentração de contaminantes.

Transport of Groundwater, Heat, and Radiogenic He in Topography‐Driven Basins

The goal of the study is to assess the feasibility of characterizing the caprock integrity by utilizing sampled helium (He) concentration in fluids and temperature measurement prior to CO2 injection. A series of simulations representing pre-CO2 injection phase was conducted to reveal the spatial distribution of groundwater, temperature, and He concentration under various geologic conditions of topographically driven basin. Then, their profiles in preinjection conditions were compared with dynamic signatures of both injection-induced pressure and leaked brine concentration at post-CO2 injection conditions. In the topographic basin, He and heat transports generally show analogous transport except the low-permeability basin where the conductive heat and diffusive solute transports are the primary transport mechanisms. The transition occurred at permeabilities between 10(-15) and 10(-14) m2. Inclusion of low-k layer (low-k layer: 10(-16) m2 and surrounding basin: 10(-13) m2) segregates shallow and deep groundwater system and creates a 3-km single large free convection of groundwater driven by unevenly distributed thermal profile of basin. Finally, He and temperature profiles with high-k pathways at pre-CO2 injection scenarios and NaCl mass fractions at post-CO2 injection showed systematic trends and relationships, suggesting that proper understanding of these trends will aid to identify the seal integrity.