Zhenxue Dai

CO2 Accounting and Risk Analysis for CO2 Sequestration at Enhanced Oil Recovery Sites.

Using CO2 in enhanced oil recovery (CO2-EOR) is a promising technology for emissions management because CO2-EOR can dramatically reduce sequestration costs in the absence of emissions policies that include incentives for carbon capture and storage. This study develops a multiscale statistical framework to perform CO2 accounting and risk analysis in an EOR environment at the Farnsworth Unit (FWU), Texas. A set of geostatistical-based Monte Carlo simulations of CO2-oil/gas-water flow and transport in the Morrow formation are conducted for global sensitivity and statistical analysis of the major risk metrics: CO2/water injection/production rates, cumulative net CO2 storage, cumulative oil/gas productions, and CO2 breakthrough time. The median and confidence intervals are estimated for quantifying uncertainty ranges of the risk metrics. A response-surface-based economic model has been derived to calculate the CO2-EOR profitability for the FWU site with a current oil price, which suggests that approximately 31% of the 1000 realizations can be profitable. If government carbon-tax credits are available, or the oil price goes up or CO2 capture and operating expenses reduce, more realizations would be profitable. The results from this study provide valuable insights for understanding CO2 storage potential and the corresponding environmental and economic risks of commercial-scale CO2-sequestration in depleted reservoirs.

Improving Permeability Semivariograms with Transition Probability Models of Hierarchical Sedimentary Architecture Derived from Outcrop-Analog Studies

Received 21 July 2004; revised 22 February 2005; accepted 23 March 2005; published 30 July 2005. [1] As analogs for aquifers, outcrops of sedimentary deposits allow sedimentary units to be mapped, permeability to be measured with high resolution, and sedimentary architecture to be related to the univariate and spatial bivariate statistics of permeability. Sedimentary deposits typically can be organized into hierarchies of unit types and associated permeability modes. The types of units and the number of hierarchical levels defined on an outcrop might vary depending upon the focus of the study. Regardless of how the outcrop sediments are subdivided, a composite bivariate statistic like the permeability semivariogram is a linear summation of the autosemivariograms and cross semivariograms for the unit types defined, weighted by the proportions and transition probabilities associated with the unit types. The composite sample semivariogram will not be representative unless data locations adequately define these transition probabilities. Data reflecting the stratal architecture can often be much more numerous than permeability measurements. These lithologic data can be used to better define transition probabilities and thus improve the estimates of the composite permeability semivariogram. In doing so, bias created from the incomplete exposure of units can be reduced by a Bayesian approach for estimating unit proportions and mean lengths. We illustrate this ^

Probabilistic evaluation of shallow groundwater resources at a hypothetical carbon sequestration site

Carbon sequestration in geologic reservoirs is an important approach for mitigating greenhouse gases emissions to the atmosphere. This study first develops an integrated Monte Carlo method for simulating CO2 and brine leakage from carbon sequestration and subsequent geochemical interactions in shallow aquifers. Then, we estimate probability distributions of five risk proxies related to the likelihood and volume of changes in pH, total dissolved solids, and trace concentrations of lead, arsenic, and cadmium for two possible consequence thresholds. The results indicate that shallow groundwater resources may degrade locally around leakage points by reduced pH and increased total dissolved solids (TDS). The volumes of pH and TDS plumes are most sensitive to aquifer porosity, permeability, and CO2 and brine leakage rates. The estimated plume size of pH change is the largest, while that of cadmium is the smallest among the risk proxies. Plume volume distributions of arsenic and lead are similar to those of TDS. The scientific results from this study provide substantial insight for understanding risks of deep fluids leaking into shallow aquifers, determining the area of review, and designing monitoring networks at carbon sequestration sites.

Pre-site characterization risk analysis for commercial-scale carbon sequestration.

This study develops a probability framework to evaluate subsurface risks associated with commercial-scale carbon sequestration in the Kevin Dome, Montana. Limited knowledge of the spatial distribution of physical attributes of the storage reservoir and the confining rocks in the area requires using regional data to estimate project risks during the pre-site characterization analysis. A set of integrated Monte Carlo simulations are used to assess four risk proxies: the CO2 injectivity, area of review (AoR), migration rate into confining rocks, and a monitoring strategy prior to detailed site characterization. Results show a reasonable likelihood of reaching the project goal of injecting 1 Mt in 4 years with a single injection well (>58%), increasing to >70% if the project is allowed to run for 5 years. The mean radius of the AoR, based on a 0.1 MPa pressure change, is around 4.8 km. No leakage of CO2 through the confining units is seen in any simulations. The computed CO2 detection probability suggests that the monitoring wells should be located at less than 1.2 km away from the injection well so that CO2 is likely to be detected within the time frame of the project. The scientific results of this study will be used to inform the detailed site characterization process and to provide more insight for understanding operational and technical risks before injecting CO2.

Identifying geochemical processes by inverse modeling of multicomponent reactive transport in the Aquia aquifer

Modeling reactive geochemical transport in the subsurface is a powerful tool for understanding and interpreting geochemical processes in aquifer systems. Different conceptual models can include different combinations of geochemical processes. A limitation of current inverse models is that they are based only on one conceptual model, which may lead to statistical bias and underestimation of uncertainty. We present a stepwise inverse modeling methodology that can include any number of conceptual models and thus consider alternate combinations of processes, and it can provide a quantitative basis for selecting the best among them. We applied the inverse methodology to modeling the geochemical evolution in the Aquia aquifer (Maryland, USA) over 105 yr. The inverse model accounts for aqueous complexation, acid-base and redox reactions, cation exchange, proton surface complexation, and mineral dissolution and precipitation; identifi es relevant geochemical processes; and estimates key reactive transport parameters from available hydrogeochemical data. Inverse modeling provides optimum estimates of transmissivities, leakage rates, dispersivities, cation exchange capacity (CEC), cation selectivities, and initial and boundary concentrations of selected chemical components. Inverse modeling with multiple conceptual models helps to identify the most likely physical and chemical processes in the paleohydrology and paleogeochemistry of the Aquia aquifer. Identifi cation criteria derived from information theory are used to select the best among ten candidate conceptual models. In the fi nal model, both proton surface complexation and methane oxidation are identifi ed as relevant geochemical processes.

Inverse Modeling of Water-Rock-CO2 Batch Experiments: Potential Impacts on Groundwater Resources at Carbon Sequestration Sites

This study developed a multicomponent geochemical model to interpret responses of water chemistry to introduction of CO2 into six water-rock batches with sedimentary samples collected from representative potable aquifers in the Gulf Coast area. The model simulated CO2 dissolution in groundwater, aqueous complexation, mineral reactions (dissolution/precipitation), and surface complexation on clay mineral surfaces. An inverse method was used to estimate mineral surface area, the key parameter for describing kinetic mineral reactions. Modeling results suggested that reductions in groundwater pH were more significant in the carbonate-poor aquifers than in the carbonate-rich aquifers, resulting in potential groundwater acidification. Modeled concentrations of major ions showed overall increasing trends, depending on mineralogy of the sediments, especially carbonate content. The geochemical model confirmed that mobilization of trace metals was caused likely by mineral dissolution and surface complexation on clay mineral surfaces. Although dissolved inorganic carbon and pH may be used as indicative parameters in potable aquifers, selection of geochemical parameters for CO2 leakage detection is site-specific and a stepwise procedure may be followed. A combined study of the geochemical models with the laboratory batch experiments improves our understanding of the mechanisms that dominate responses of water chemistry to CO2 leakage and also provides a frame of reference for designing monitoring strategy in potable aquifers.

Aquifer structure identification using stochastic inversion

This study presents a stochastic inverse method for aquifer structure identification using sparse geophysical and hydraulic response data. The method is based on updating structure parameters from a transition probability model to iteratively modify the aquifer structure and parameter zonation. The method is extended to the adaptive parameterization of facies hydraulic parameters by including these parameters as optimization variables. The stochastic nature of the statistical structure parameters leads to nonconvex objective functions. A multi-method genetically adaptive evolutionary approach (AMALGAM-SO) was selected to perform the inversion given its search capabilities. Results are obtained as a probabilistic assessment of facies distribution based on indicator cokriging simulation of the optimized structural parameters. The method is illustrated by estimating the structure and facies hydraulic parameters of a synthetic example with a transient hydraulic response.

Critical Dynamics of Gravito-Convective Mixing in Geological Carbon Sequestration

When CO2 is injected in saline aquifers, dissolution causes a local increase in brine density that can cause Rayleigh-Taylor-type gravitational instabilities. Depending on the Rayleigh number, density-driven flow may mix dissolved CO2 throughout the aquifer at fast advective time-scales through convective mixing. Heterogeneity can impact density-driven flow to different degrees. Zones with low effective vertical permeability may suppress fingering and reduce vertical spreading, while potentially increasing transverse mixing. In more complex heterogeneity, arising from the spatial organization of sedimentary facies, finger propagation is reduced in low permeability facies, but may be enhanced through more permeable facies. The connectivity of facies is critical in determining the large-scale transport of CO2-rich brine. We perform high-resolution finite element simulations of advection-diffusion transport of CO2 with a focus on facies-based bimodal heterogeneity. Permeability fields are generated by a Markov Chain approach, which represent facies architecture by commonly observed characteristics such as volume fractions. CO2 dissolution and phase behavior are modeled with the cubic-plus-association equation-of-state. Our results show that the organization of high-permeability facies and their connectivity control the dynamics of gravitationally unstable flow. We discover new flow regimes in both homogeneous and heterogeneous media and present quantitative scaling relations for their temporal evolution.

Upscaling of reactive mass transport in fractured rocks with multimodal reactive mineral facies.

[1] This paper presents a methodology for upscaling matrix‐material transport parameters in fractured‐flow dominated systems with multimodal reactive mineral facies. The upscaling method provides a theoretical and practical link between controlled experimental results at the laboratory/bench scale and multikilometer field scales at which contaminant remediation and risk assessment are actually conducted. As sorption reactions in matrix are in part determined by mineral properties, a new conceptual model is developed to reflect the hierarchical structure of reactive mineral facies at the microform, mesoform, and macroform scales. The conceptual model of hierarchical reactive matrix mineral facies is integrated with a dual‐porosity model for simulating diffusion of solutes out of fractures and sorption onto the matrix minerals. By assuming that sorption reactions primarily occur in the rock matrix, we develop a multimodal spatial random function for characterizing both the tortuosity (physical heterogeneity) and sorption coefficient (chemical heterogeneity) at different scales in the rock matrix. The effective tortuosity at the field scale is derived by volume averaging of mass transfer coefficient for a conservative species. Subsequently, using a sorbing species (e.g., uranium), we derive the equations for upscaling the sorption coefficients in a saturated, fractured‐rock system for field‐scale simulations. The effective field‐scale tortuosity and sorption coefficient are related to their mean, variance, integral scale, and domain size along a pathway through a three‐ dimensional flow field. The upscaled values increase with the integral scale and are larger than their geometric mean. Simulations conducted with upscaled sorption coefficients and tortuousities are compared very well with high‐resolution Monte Carlo simulations capturing the parameter spatial variations. Results of this study can be extended to explore scaledependenceofotherimportant transportparametersforfractured‐rocksolutetransport. Citation: Deng, H., Z. Dai, A. Wolfsberg, Z. Lu, M. Ye, and P. Reimus (2010), Upscaling of reactive mass transport in fractured rocks with multimodal reactive mineral facies, Water Resour. Res., 46, W06501, doi:10.1029/2009WR008363.

Upscaling retardation factor in hierarchical porous media with multimodal reactive mineral facies

Aquifer heterogeneity controls spatial and temporal variability of reactive transport parameters and has significant impacts on subsurface modeling of flow, transport, and remediation. Upscaling (or homogenization) is a process to replace a heterogeneous domain with a homogeneous one such that both reproduce the same response. To make reliable and accurate predictions of reactive transport for contaminant in chemically and physically heterogeneous porous media, subsurface reactive transport modeling needs upscaled parameters such as effective retardation factor to perform field-scale simulations. This paper develops a conceptual model of multimodal reactive mineral facies for upscaling reactive transport parameters of hierarchical heterogeneous porous media. Based on the conceptual model, covariance of hydraulic conductivity, sorption coefficient, flow velocity, retardation factor, and cross-covariance between flow velocity and retardation factor are derived from geostatistical characterizations of a three-dimensional unbounded aquifer system. Subsequently, using a Lagrangian approach the scale-dependent analytical expressions are derived to describe the scaling effect of effective retardation factors in temporal and spatial domains. When time and space scales become sufficiently large, the effective retardation factors approximate their composite arithmetic mean. Correlation between the hydraulic conductivity and the sorption coefficient can significantly affect the values of the effective retardation factor in temporal and spatial domains. When the temporal and spatial scales are relatively small, scaling effect of the effective retardation factors is relatively large. This study provides a practical methodology to develop effective transport parameters for field-scale modeling at which remediation and risk assessment is actually conducted. It does not only bridge the gap between bench-scale measurements to field-scale modeling, but also provide new insights into the influence of hierarchical mineral distribution on effective retardation factor.