Water in minerals? A peak in the infrared

The study of water in minerals with infrared spectroscopy is reviewed with emphasis on natural and synthetic quartz. Water can be recognized in minerals as fluid inclusions and as isolated molecules and can be distinguished from hydroxide ion. The distinction between very small inclusions and aggregates of structurally bound molecules is difficult. New studies of synthetic quartz using near-infrared spectroscopy are reported. These demonstrate that water molecules are the dominant hydrogen containing species in synthetic quartz but that this water is not in aggregates large enough to form ice when cooled

Solubility and diffusional uptake of hydrogen in quartz at high water pressures: Implications for hydrolytic weakening

Attempts to introduce molecular water into dry, natural quartz crystals by diffusive transport and thus weaken them hydrolytically at T = 700°–900°C and PH_2O = 400–1550 MPa have failed. Infrared spectroscopy of hydrothermally annealed single crystals of natural quartz reveals the diffusive uptake of interstitial hydrogen (resulting in hydroxyl groups) at rates similar to those previously proposed for intracrystalline water at high water pressures. The solubility of interstitial hydrogen at these conditions is independent of temperature and pressure; instead, it depends upon the initial aluminum concentration by the local charge neutrality condition [H_i·] = [Al_(Si)′]. The rate of interstitial hydrogen diffusion parallel to c is given by an Arrhenius relation with D_0 = 1.4 × 10^(−1) m^2/s and Q = 200 ± 20 kJ/mol, in close agreement with H diffusivities reported for much lower pressures (PH_2O = 2.5 MPa). Deformation experiments following hydrothermal annealing show no mechanical weakening, and the lack of any detectable broadband absorption associated with molecular water shows that the diffusion rates of structural water are much lower than those of hydrogen. These results are consistent with the available oxygen diffusion data for quartz and with the failure to observe weakening in previous studies of quartz deformation at pressures of 300–500 MPa; they call into question the rapid rates of diffusion originally suggested for the hydrolytic weakening defect. It is suggested that the observed weakening in many previous experiments was complicated by microcracking processes in response to nonhydrostatic stresses and low effective confining pressures. Extensive microcracking may provide a mechanism for molecular water to enter quartz and allow local plastic deformation to occur. It does not appear that molecular water can diffuse far enough into uncracked quartz to allow hydrolytic weakening over annealing times that are feasible in the laboratory

SITE CHARACTERIZATION USING JOINT RECONSTRUCTIONS OF DISPARATE DATA TYPES

Potential CO{sub 2} reservoirs are often geologically complex and possible leakage pathways such as those created. Reservoir heterogeneity can affect injectivity, storage capacity, and trapping rate. Similarly, discontinuous caprocks and faults can create risk of CO{sub 2} leakage. The characteristics of potential CO{sub 2} reservoirs need to be well understood to increase confidence in injection project success. Reservoir site characterization will likely involve the collection and integration of multiple geological, geophysical, and geochemical data sets. We have developed a computational tool to more realistically render lithologic models using multiple geological and geophysical techniques. Importantly, the approach formally and quantitatively integrates available data and provides a strict measure of probability and uncertainty in the subsurface. The method will characterize solution uncertainties whether they stem from unknown reservoir properties, measurement error, or poor sensitivity of geophysical techniques

Integrated Geothermal-CO2 Reservoir Systems: Reducing Carbon Intensity through Sustainable Energy Production and Secure CO2 Storage

AbstractLarge-scale geologic CO2 storage (GCS) can be limited by overpressure, while geothermal energy production is often limited by pressure depletion. We investigate how synergistic integration of these complementary systems may enhance the viability of GCS by relieving overpressure, which reduces pore-space competition, the Area of Review, and the risks of CO2 leakage and induced seismicity, and by producing geothermal energy and water, which can defray parasitic energy and water costs of CO2 capture

Joint reconstructions of CO2 plumes using a Markov Chain Monte Carlo approach

We describe a stochastic inversion method for mapping subsurface regions where CO{sub 2} saturation is changing. The technique combines prior information with measurements of injected CO{sub 2} volume, reservoir deformation and electrical resistivity. Bayesian inference and a Metropolis simulation algorithm form the basis for this approach. The method can (a) jointly reconstruct disparate data types such as surface or subsurface tilt, electrical resistivity, and injected CO{sub 2} volume measurements, (b) provide quantitative measures of the result uncertainty, (c) identify competing models when the available data are insufficient to definitively identify a single optimal model and (d) rank the alternative models based on how well they fit available data. We use measurements collected during CO{sub 2} injection for enhanced oil recovery to illustrate the method's performance. The stochastic inversions provide estimates of the most probable location, shape, volume of the plume and most likely CO{sub 2} saturation. The results suggest that the method can reconstruct data with poor signal to noise ratio

Dynamic Data-Driven Event Reconstruction for Atmospheric Releases

Accidental or terrorist releases of hazardous materials into the atmosphere can impact large populations and cause significant loss of life or property damage. Plume predictions have been shown to be extremely valuable in guiding an effective and timely response. The two greatest sources of uncertainty in the prediction of the consequences of hazardous atmospheric releases result from poorly characterized source terms and lack of knowledge about the state of the atmosphere as reflected in the available meteorological data. In this report, we discuss the development of a new event reconstruction methodology that provides probabilistic source term estimates from field measurement data for both accidental and clandestine releases. Accurate plume dispersion prediction requires the following questions to be answered: What was released? When was it released? How much material was released? Where was it released? We have developed a dynamic data-driven event reconstruction capability which couples data and predictive models through Bayesian inference to obtain a solution to this inverse problem. The solution consists of a probability distribution of unknown source term parameters. For consequence assessment, we then use this probability distribution to construct a ''''composite'' forward plume prediction which accounts for the uncertainties in the source term. Since in most cases of practical significance it is impossible to find a closed form solution, Bayesian inference is accomplished by utilizing stochastic sampling methods. This approach takes into consideration both measurement and forward model errors and thus incorporates all the sources of uncertainty in the solution to the inverse problem. Stochastic sampling methods have the additional advantage of being suitable for problems characterized by a non-Gaussian distribution of source term parameters and for cases in which the underlying dynamical system is non-linear. We initially developed a Markov Chain Monte Carlo (MCMC) stochastic methodology and demonstrated its effectiveness by reconstructing a wide range of release scenarios, using synthetic as well as real-world data. Data for evaluation of our event reconstruction capability were drawn from the short-range Prairie Grass, Copenhagen, and Joint Urban 2003 field experiments and a continental-scale real-world accidental release in Algeciras, Spain. The method was tested using a variety of forward models, including a Gaussian puff dispersion model INPUFF, the regional-to-continental scale Lagrangian dispersion model LODI (the work-horse real-time operational dispersion model used by the National Atmospheric Release Advisory Center), the empirical urban model UDM, and the building-scale computational computational fluid dynamics code FEM3MP. The robustness of the Bayesian methodology was demonstrated via the use of subsets of the available concentration data and by introducing error into some of the measurements. These tests showed that the Bayesian approach is capable of providing reliable estimates of source characteristics even in cases of limited or significantly corrupted data. For more effective treatment of strongly time-dependent problems, we developed a Sequential Monte Carlo (SMC) approach. To achieve the best performance under a wide range of conditions we combined SMC and MCMC sampling into a hybrid methodology. We compared the effectiveness and advantages of this approach relative to MCMC using a set of synthetic data examples. Our dynamic data-driven event reconstruction capability seamlessly integrates observational data streams with predictive models, in order to provide the best possible estimates of unknown source term parameters, as well as optimal and timely situation analyses consistent with both models and data

Geochemical detection of carbon dioxide in dilute aquifers

<p>Abstract</p> <p>Background</p> <p>Carbon storage in deep saline reservoirs has the potential to lower the amount of CO₂emitted to the atmosphere and to mitigate global warming. Leakage back to the atmosphere through abandoned wells and along faults would reduce the efficiency of carbon storage, possibly leading to health and ecological hazards at the ground surface, and possibly impacting water quality of near-surface dilute aquifers. We use static equilibrium and reactive transport simulations to test the hypothesis that perturbations in water chemistry associated with a CO₂gas leak into dilute groundwater are important measures for the potential release of CO₂to the atmosphere. Simulation parameters are constrained by groundwater chemistry, flow, and lithology from the High Plains aquifer. The High Plains aquifer is used to represent a typical sedimentary aquifer overlying a deep CO₂storage reservoir. Specifically, we address the relationships between CO₂flux, groundwater flow, detection time and distance. The CO₂flux ranges from 10³to 2 × 10⁶t/yr (0.63 to 1250 t/m²/yr) to assess chemical perturbations resulting from relatively small leaks that may compromise long-term storage, water quality, and surface ecology, and larger leaks characteristic of short-term well failure.</p> <p>Results</p> <p>For the scenarios we studied, our simulations show pH and carbonate chemistry are good indicators for leakage of stored CO₂into an overlying aquifer because elevated CO₂yields a more acid pH than the ambient groundwater. CO₂leakage into a dilute groundwater creates a slightly acid plume that can be detected at some distance from the leak source due to groundwater flow and CO₂buoyancy. pH breakthrough curves demonstrate that CO₂leaks can be easily detected for CO₂flux ≥ 10⁴t/yr within a 15-month time period at a monitoring well screened within a permeable layer 500 m downstream from the vertical gas trace. At lower flux rates, the CO₂dissolves in the aqueous phase in the lower most permeable unit and does not reach the monitoring well. Sustained pumping in a developed aquifer mixes the CO₂-affected water with the ambient water and enhances pH signal for small leaks (10³t/yr) and reduces pH signal for larger leaks (≥ 10⁴t/yr).</p> <p>Conclusion</p> <p>The ability to detect CO₂leakage from a storage reservoir to overlying dilute groundwater is dependent on CO₂solubility, leak flux, CO₂buoyancy, and groundwater flow. Our simulations show that the most likely places to detect CO₂are at the base of the confining layer near the water table where CO₂gas accumulates and is transported laterally in all directions, and downstream of the vertical gas trace where groundwater flow is great enough to transport dissolved CO₂laterally. Our simulations show that CO₂may not rise high enough in the aquifer to be detected because aqueous solubility and lateral groundwater transport within the lower aquifer unit exceeds gas pressure build-up and buoyancy needed to drive the CO₂gas upwards.</p