• Energy Research

The safety case for a radioactive waste repository relies heavily on results obtained by numerical models that assess the long-term performance of the engineered and natural barrier systems. Given that important engineering and public policy decisions are based on these models, it is essential that we critically evaluate their abilities and limitations, and thus justify the level of confidence we have in the inferences drawn from the modeling. In this article, we discuss some of the issues surrounding the modeler’s attempts to test, corroborate, confirm, and verify numerical models—a process sometimes referred to as model validation. This wide-ranging topic is approached by first examining its deep roots in the philosophy of science and hypothesis testing. However, the application of these principles to radioactive waste isolation calls for a more pragmatic approach, which has the narrower goal of corroborating site-specific models and their usefulness for a specific purpose. We focus on the practical aspects of validating hydrogeological models that are used to understand the evolution of the repository system. We will make the case that the responsible use of numerical models requires a sufficient understanding of the quality and robustness of the simulation results, with direct implications for how these results need to be interpreted, and how they can (or cannot) be used in support of important policy decisions.

The post-closure performance of a generic horizontal drillhole repository for the disposal of spent nuclear fuel (SNF) is quantitatively evaluated using a physics-based numerical model that accounts for coupled thermal-hydrological flow and radionuclide transport processes. The model incorporates most subcomponents of the repository system, from individual waste canisters to the geological far field. The main performance metric is the maximum annual dose to an individual drinking potentially contaminated water taken from a well located above the center of the repository. Safety is evaluated for a wide range of conditions and alternative system evolutions, using deterministic simulations, sensitivity analyses, and a sampling-based uncertainty propagation analysis. These analyses show that the estimated maximum annual dose is low (on the order of 10−4 mSv yr−1, which is 1000 times smaller than a typical dose standard), and that the conclusions drawn from this dose estimate remain valid even if considerable changes are made to key assumptions and property values. The depth of the repository and the attributes of its configuration provide the main safety function of isolation from the accessible environment. Long-term confinement of radionuclides in the waste matrix and slow, diffusion-dominated transport leading to long migration times allow for radioactive decay to occur within the repository system. These preliminary calculations suggest that SNF can be safely disposed in an appropriately sited and carefully constructed and sealed horizontal drillhole repository.

The disposal of spent nuclear fuel and other high-level radioactive waste in deep horizontal drillholes is an innovative system. Canisters of highly corrosion-resistant nickel-chromium-molybdenum (Ni-Cr-Mo) alloys are specified for the disposal of this nuclear waste. The canisters are emplaced along a steel casing in a horizontal drillhole that is one to three kilometers deep into or below a low-permeability geologic formation. The drillhole is in fully saturated rock with anoxic and reducing pore waters. A time-interval analysis method was used to track the evolution of the environment and to analyze corrosion performance of a representative engineered barrier system (EBS) configuration. In this analysis, the canisters remained perforation-free for tens of thousands of years. The amounts of hydrogen and metal oxides formed as by-products of the metal corrosion process were determined. These by-products are of interest, because both hydrogen and metal oxides can affect the chemical composition of the environment and the transport and sorption behavior of radionuclides and other species. Beneficial attributes that contribute to the extraordinarily long life of the canisters were identified. Several inherent characteristics of the horizontal drillhole disposal system reduced the complexities and uncertainties of the analysis.

Abstract One way to reduce the effects of anthropogenic greenhouse gases on climate is to inject carbon dioxide (CO2) from industrial sources into deep geological formations such as brine aquifers or depleted oil or gas reservoirs. Research is being conducted to improve understanding of factors affecting particular aspects of geological CO2 storage (such as storage performance, storage capacity, and health, safety and environmental (HSE) issues) as well as to lower the cost of CO2 capture and related processes. However, there has been less emphasis to date on system-level analyses of geological CO2 storage that consider geological, economic, and environmental issues by linking detailed process models to representations of engineering components and associated economic models. The objective of this study is to develop a system-level model for geological CO2 storage, including CO2 capture and separation, compression, pipeline transportation to the storage site, and CO2 injection. Within our system model we are incorporating detailed reservoir simulations of CO2 injection into a gas reservoir and related enhanced production of methane. Potential leakage and associated environmental impacts are also considered. The platform for the system-level model is GoldSim [GoldSim User’s Guide. GoldSim Technology Group; 2006, http://www.goldsim.com ]. The application of the system model focuses on evaluating the feasibility of carbon sequestration with enhanced gas recovery (CSEGR) in the Rio Vista region of California. The reservoir simulations are performed using a special module of the TOUGH2 simulator, EOS7C, for multicomponent gas mixtures of methane and CO2. Using a system-level modeling approach, the economic benefits of enhanced gas recovery can be directly weighed against the costs and benefits of CO2 injection.

Single-well experimental design for studying residual trapping of supercritical carbon dioxide Yingqi Zhang 1 , Barry Freifeld 1 , Stefan Finsterle 1 , Martin Leahy 2,3 , Jonathan Ennis-King 2,3 , Lincoln Paterson 2,3 , Tess Dance 2,3 Lawrence Berkeley National Laboratory, Berkeley, CA,USA CSIRO Petroleum, Clayton, Victoria, Australia Cooperative Research Centre for Greenhouse Gas Technologies, Australia Abstract The objective of our research is to design a single-well injection withdrawal test to evaluate residual phase trapping at potential CO 2 geological storage sites. Given the significant depths targeted for CO 2 storage and the resulting high costs associated with drilling to those depths, it is attractive to develop a single well test that can provide data to assess reservoir properties and reduce uncertainties in the appraisal phase of site investigation. The main challenges in a single-well test design include (1) difficulty in quantifying the amount of CO 2 that has dissolved into brine or migrated away from the borehole; (2) non-uniqueness and uncertainty in the estimate of the residual gas saturation (S gr ) due to correlations among various parameters; and (3)the potential biased S gr estimate due to unaccounted heterogeneity of the geological medium. To address each of these challenges, we propose (1) to use a physical-based model to simulation test sequence and inverse modeling to analyze data information content and to quantify uncertainty; (2) to jointly use multiple data types generated from different kinds of tests to constrain the S gr estimate; and (3) to reduce the sensitivity of the designed tests to geological heterogeneity by conducting the same test sequence in both a water-saturated system and a system with residual gas saturation. To perform the design calculation, we build a synthetic model and conduct a formal analysis for sensitivity and uncertain quantification. Both parametric uncertainty and geological uncertainty are considered in the analysis. Results show (1) uncertainty in the estimation of S gr can be reduced by jointly using multiple data types and repeated tests; and (2) geological uncertainty is essential and needs to be accounted for in the estimation of S gr and its uncertainty. The proposed methodology is applied to the design of a CO 2 injection test at CO2CRC’s Otway Project Site, Victoria, Australia. 1. Introduction and Objective The geologic sequestration of anthropogenic greenhouse gases to mitigate climate change is receiving increasing attention as a means to reduce atmospheric emissions and the related impacts as a result of continued use of fossil fuels. The ability of a host formation to effectively trap CO 2 determines the suitability of a proposed site for long-term CO 2 sequestration. Four trapping mechanisms have been identified (IPCC, 2005): structural trapping, residual phase trapping, solubility trapping and mineralization trapping. This study focuses on residual phase trapping, i.e., the immobilization of individual bubbles or relatively small blobs of the CO 2 -rich phase. TheCO 2 bubbles are either trapped by capillary forces or are stuck in local trapping structures or dead-end portions of the pore space, preventing further CO 2 migration in response to pressure gradients or buoyancy forces. (CO 2 saturation can be reduced below the residual value by processes other than viscous flow, e.g., by compression or dissolution.) A parameter referred to as residual gas saturation (S gr ) is used to characterize the tendency of a geologic formation to trap some of the non-wetting phase in its pore space. The residual gas saturation is a property of the interaction between the porous medium and the fluids, mostly reflecting the size and shape of its pores and their connectivity. However, residual gas saturation is not a static parameter; it depends on the sequence of hysteretic drainage and imbibition processes, i.e., it is history-dependent, with different values at each point in the storage formation as the fluid saturation changes during CO 2 injection and redistribution. Only its maximum value S grmax (associated with the primary imbibition curve) can be considered as a formation parameter independent of the dynamic system

AbstractLeakage of CO2 and brine along faults at geologic carbon sequestration (GCS) sites is a primary concern for storage integrity. The focus of this study is on the estimation of the probability of leakage along faults or fractures. This leakage probability is controlled by the probability of a connected network of conduits existing at a given site, the probability of this network encountering the CO2 plume, and the probability of this network intersecting environmental resources that may be impacted by leakage. This work is designed to fit into a risk assessment and certification framework that uses compartments to represent vulnerable resources such as potable groundwater, health and safety, and the near-surface environment. The method we propose includes using percolation theory to estimate the connectivity of the faults, and generating fuzzy rules from discrete fracture network simulations to estimate leakage probability. By this approach, the probability of CO2 escaping into a compartment for a given system can be inferred from the fuzzy rules. The proposed method provides a quick way of estimating the probability of CO2 or brine leaking into a compartment. In addition, it provides the uncertainty range of the estimated probability.

AbstractResidual trapping is one of the four trapping mechanisms that have been identified for geological CO2 storage, a means to reduce atmospheric emissions and the related impacts as a result of continued use of fossil fuels. The objective of this research is to design a single-well injection-withdrawal test to estimate residual CO2 trapping (Sgr) in brine aquifers. Due to the high cost associated with drilling to depths of potential CO2 storage site, single-well test can cost-effectively provide data sets to assess reservoir properties and reduce uncertainties in the appraisal phase for finding commercial scale storage sites. The main challenges in the design are the following: (1) It is difficult to quantify the amount that is trapped using a mass balance approach; (2) correlations among various parameters leads to a highly uncertain or non-unique Sgr estimate; and (3) the Sgr estimate could be biased due to heterogeneity of the geological medium. We have proposed our design to address each of these challenges by (1) use a detailed reservoir model to simulate the relevant physical processes in the tests; (2) perform a test sequence that yields multiple types of complementary data to constrain the estimate of Sgr; (3) remove or reduce the bias caused by the heterogeneity of the storage formation by repeating the same test under different saturation conditions. The design will be applied to a practical field test that will be carried out as part of the CO2CRC Otway Project, at Victoria Australia.

Abstract Variance-based global sensitivity analysis (e.g., the Sobol’ sensitivity index) can be used to identify the important parameters over the entire parameter space. However, one often cannot afford the computational costs of sampling-based approaches in combination with expensive high-fidelity forward models. Reduced-order models (ROM) can substantially accelerate calculation of these sensitivities. However, it is usually difficult to determine what type of ROM should be used and how accurately the ROM represents the high-fidelity model (HFM) results. In this paper, we propose to concurrently use multiple ROMs as a way to assess the robustness of the model-reduction method. Two sets of HFM simulations are needed, one set for building ROMs and the other for validating ROMs. Our goal is to keep the total number of HFM simulations to a minimum. Ideally some of the HFM simulations in the first set can be shared by different ROMs. Based on validation results, the ROMs can be combined with different schemes. We demonstrate that we can achieve the goal by using four different ROMs and still considerably save computational time compared to using traditional HFM simulation for calculating sensitivity indices. We apply the approach to an example problem of a large-scale geological carbon dioxide storage system, in which the objective is to calculate a sensitivity index to identify important parameters. For this problem, the locally best ROM provides better estimates than the weighted average from all ROMs.