79 research outputs found

    Identification and Selection of Major Carbon Dioxide Stream Compositions

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    A critical component in the assessment of long-term risk from geologic sequestration of CO2 is the ability to predict mineralogical and geochemical changes within storage reservoirs due to rock-brine-CO2 reactions. Impurities and/or other constituents selected for co-sequestration can affect both the chemical and physical (e.g. density, viscosity, interfacial tension) behavior of CO2 in the deep subsurface. These impurities and concentrations are a function of both the industrial source(s) of the CO2, as well as the carbon capture technology used to extract the CO2 and produce a concentrated stream for geologic sequestration. This report summarizes the relative concentrations of CO2 and other constituents in exhaust gases from major non-energy related industrial sources of CO2. Assuming that carbon-capture technology would remove most of the incondensable gases N2, O2, and Ar, leaving SO2 and NOx as the main impurities, we selected four test fluid compositions for use in geochemical experiments. These included: 1) a pure CO2 stream representative of food grade CO2 used in most enhanced oil recovery projects: 2) a test fluid composition containing low concentrations (0.5 mole %) SO2 and NOx (representative of that generated from cement production), 3) a test fluid composition with higher concentrations (2.5 mole %) of SO2, and 4) and test fluid composition containing 3 mole % H2S

    Prototype Data Models and Data Dictionaries for Hanford Sediment Physical and Hydraulic Properties

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    The Remediation Decision Support (RDS) project, managed by the Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy (DOE) and the CH2M HILL Plateau Remediation Company (CHPRC), has been compiling physical and hydraulic property data and parameters to support risk analyses and waste management decisions at Hanford. In FY09 the RDS project developed a strategic plan for a physical and hydraulic property database. This report documents prototype data models and dictionaries for these properties and associated parameters. Physical properties and hydraulic parameters and their distributions are required for any type of quantitative assessment of risk and uncertainty associated with predictions of contaminant transport and fate in the subsurface. The central plateau of the Hanford Site in southeastern Washington State contains most of the contamination at the Site and has up to {approx}100 m of unsaturated and unconsolidated or semi-consolidated sediments overlying the unconfined aquifer. These sediments contain a wide variety of contaminants ranging from organic compounds, such as carbon tetrachloride, to numerous radionuclides including technetium, plutonium, and uranium. Knowledge of the physical and hydraulic properties of the sediments and their distributions is critical for quantitative assessment of the transport of these contaminants in the subsurface, for evaluation of long-term risks and uncertainty associated with model predictions of contaminant transport and fate, and for evaluating, designing, and operating remediation alternatives. One of the goals of PNNL's RDS project is to work with the Hanford Environmental Data Manager (currently with CHPRC) to develop a protocol and schedule for incorporation of physical property and hydraulic parameter datasets currently maintained by PNNL into HEIS. This requires that the data first be reviewed to ensure quality and consistency. New data models must then be developed for HEIS that are approved by the HTAG that oversees HEIS development. After approval, these new data models then need to be implemented in HEIS by the EDM before there is an actual repository for the data. This document summarizes modifications to previously developed data models, and new data models and data dictionaries for physical and hydraulic property data and parameters to be transferred to HEIS. A prototype dataset that conforms to the specifications of these recommended data models has been identified and processed, and is ready for transfer to CHPRC for inclusion in HEIS. Additional datasets are planned for transfer from PNNL to CHPRC in FY11
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