20 research outputs found

    Geologic Carbon Sequestration in the Illinois Basin: Numerical Modeling to Evaluate Potential Impacts

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    US Department of Energy via the Regional Partnership Program, DE-FC26-05NT42588 and USEPA STAR grant number 488220Ope

    RVA. 3-D Visualization and Analysis Software to Support Management of Oil and Gas Resources

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    A free software application, RVA, has been developed as a plugin to the US DOE-funded ParaView visualization package, to provide support in the visualization and analysis of complex reservoirs being managed using multi-fluid EOR techniques. RVA, for Reservoir Visualization and Analysis, was developed as an open-source plugin to the 64 bit Windows version of ParaView 3.14. RVA was developed at the University of Illinois at Urbana-Champaign, with contributions from the Illinois State Geological Survey, Department of Computer Science and National Center for Supercomputing Applications. RVA was designed to utilize and enhance the state-of-the-art visualization capabilities within ParaView, readily allowing joint visualization of geologic framework and reservoir fluid simulation model results. Particular emphasis was placed on enabling visualization and analysis of simulation results highlighting multiple fluid phases, multiple properties for each fluid phase (including flow lines), multiple geologic models and multiple time steps. Additional advanced functionality was provided through the development of custom code to implement data mining capabilities. The built-in functionality of ParaView provides the capacity to process and visualize data sets ranging from small models on local desktop systems to extremely large models created and stored on remote supercomputers. The RVA plugin that we developed and the associated User Manual provide improved functionality through new software tools, and instruction in the use of ParaView-RVA, targeted to petroleum engineers and geologists in industry and research. The RVA web site (http://rva.cs.illinois.edu) provides an overview of functions, and the development web site (https://github.com/shaffer1/RVA) provides ready access to the source code, compiled binaries, user manual, and a suite of demonstration data sets. Key functionality has been included to support a range of reservoirs visualization and analysis needs, including: sophisticated connectivity analysis, cross sections through simulation results between selected wells, simplified volumetric calculations, global vertical exaggeration adjustments, ingestion of UTChem simulation results, ingestion of Isatis geostatistical framework models, interrogation of joint geologic and reservoir modeling results, joint visualization and analysis of well history files, location-targeted visualization, advanced correlation analysis, visualization of flow paths, and creation of static images and animations highlighting targeted reservoir features.Department of Energy, DOE award number DE-FE0005961Ope

    The Geology of The Mt. Simon Sandstone Storage Complex at the Wabash #1 Well, Vigo Co., Indiana (Subtask 7.2, Technical Report)

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    The Wabash CarbonSAFE project drilled the Wabash #1 stratigraphic test well (ID# 168045) at the Wabash Valley Resources (WVR) IGCC facility in Vigo County, Indiana, to characterize and evaluate the basal Cambrian Mt. Simon Sandstone for commercial-scale CO2 storage near the site. This report presents an extensive geologic characterization of the Mt. Simon storage complex and relevant data collected from the Wabash #1 well, such as lithologic data collected from cuttings and core, geophysical logging, geomechanical analysis of core samples, and well testing and fluid sampling within the Mt. Simon Sandstone. The Mt. Simon storage complex comprises two major sections: the Mt. Simon Sandstone as the potential reservoir and the overlying Eau Claire Formation as its primary seal. Within the report, an extensive depositional, sedimentological, and geochronologic characterization of the Mt. Simon is included with supportive chapters on the regional geology and the geophysical, petrophysical, and petrologic data collected during the project. An overview of 2D seismic reflection data collected from and around the test well is presented. Also presented are chapters on the characterization of the sealing Eau Claire Formation, including a chapter on the capacity of the primary and secondary seals to the Mt. Simon as well as a chapter on geomechanical testing results of the Eau Claire Formation and Mt. Simon Sandstone. Some of the information discussed in this report was used in the development of static and dynamic geologic models of the Mt. Simon Sandstone storage complex. The static and dynamic modeling of CO2 injection in the Mt. Simon Sandstone are discussed in a separate report (Dessenberger et al., 2022) under the Wabash CarbonSAFE project

    The hr1 and Fusion Peptide Regions of the Subgroup B Avian Sarcoma and Leukosis Virus Envelope Glycoprotein Influence Low pH-Dependent Membrane Fusion

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    The avian sarcoma and leukosis virus (ASLV) envelope glycoprotein (Env) is activated to trigger fusion by a two-step mechanism involving receptor-priming and low pH fusion activation. In order to identify regions of ASLV Env that can regulate this process, a genetic selection method was used to identify subgroup B (ASLV-B) virus-infected cells resistant to low pH-triggered fusion when incubated with cells expressing the cognate TVB receptor. The subgroup B viral Env (envB) genes were then isolated from these cells and characterized by DNA sequencing. This led to identification of two frequent EnvB alterations which allowed TVB receptor-binding but altered the pH-threshold of membrane fusion activation: a 13 amino acid deletion in the host range 1 (hr1) region of the surface (SU) EnvB subunit, and the A32V amino acid change within the fusion peptide of the transmembrane (TM) EnvB subunit. These data indicate that these two regions of EnvB can influence the pH threshold of fusion activation

    Internalised Values and Fairness Perception: Ethics in Knowledge Management

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    This chapter argues for ethical consideration in knowledge management (KM). It explores the effect that internalised values and fairness perception have on individuals’ participation in KM practices. Knowledge is power, and organisations seek to manage knowledge through KM practices. For knowledge to be processed, individual employees—the source of all knowledge—need to be willing to participate in KM practices. As knowledge is power and a key constituent part of knowledge is ethics, individuals’ internalised values and fairness perception affect knowledge-processing. Where an organisation claims ownership over knowledge, an individual may perceive being treated unfairly, which may obstruct knowledge-processing. Through adopting ethical KM practices, individual needs are respected, enabling knowledge-processing. Implications point towards an ethical agenda in KM theory and practice

    Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019

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    Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2•72 (95% uncertainty interval [UI] 2•66–2•79) in 2000 to 2•31 (2•17–2•46) in 2019. Global annual livebirths increased from 134•5 million (131•5–137•8) in 2000 to a peak of 139•6 million (133•0–146•9) in 2016. Global livebirths then declined to 135•3 million (127•2–144•1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2•1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27•1% (95% UI 26•4–27•8) of global livebirths. Global life expectancy at birth increased from 67•2 years (95% UI 66•8–67•6) in 2000 to 73•5 years (72•8–74•3) in 2019. The total number of deaths increased from 50•7 million (49•5–51•9) in 2000 to 56•5 million (53•7–59•2) in 2019. Under-5 deaths declined from 9•6 million (9•1–10•3) in 2000 to 5•0 million (4•3–6•0) in 2019. Global population increased by 25•7%, from 6•2 billion (6•0–6•3) in 2000 to 7•7 billion (7•5–8•0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58•6 years (56•1–60•8) in 2000 to 63•5 years (60•8–66•1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation: Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

    CO₂ storage and enhanced oil recovery : Sugar Creek Oil Field test site, Hopkins County, Kentucky

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    U.S. DOE Contract: DE-FC26-05NT42588Ope

    CO₂ storage and enhanced oil recovery : Bald Unit test site, Mumford Hills Oil Field, Posey County, Indiana

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    U.S. DOE Contract DE-FC26-05NT42588Ope

    Challenging Geostatistical Methods to Represent Heterogeneity in CO2 Reservoirs Under Residual Trapping

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    Geostatistical methods based on two-point spatial-bivariate statistics have been used to model heterogene­ity within computational studies of the dispersion of con­taminants in groundwater reservoirs and the trapping ofCO2 in geosequestration reservoirs. The ability of these methods to represent fluvial architecture, commonly oc­curring in such reservoirs, has been questioned. We challenged a widely used two-point spatial-bivariate sta­tistical method to represent fluvial heterogeneity in the context of representing how reservoir heterogeneity af­fects residual trapping of CO2 injected for geosequestra­tion. A more rigorous model for fluvial architecture was used as the benchmark in these studies. Both the geo-statistically generated model and the benchmark model were interrogated, and metrics for the connectivity of high-permeability preferential flow pathways were quan­tified. Computational simulations of CO2 injection were performed, and metrics for CO2 dynamics and trapping were quantified. All metrics were similar between the two models. The percentage of high-permeability cells in spanning connected clusters (percolating clusters) was similar because percolation is strongly dependent upon proportions, and the same proportion of higher per­meability cross-strata was specified in generating both models. The CO2 plume dynamics and residual trapping metrics were similar because they are largely controlled by the occurrence of percolating clusters. The bench­mark model represented more features of the fluvial ar­chitecture and, depending on context, representing those features may be quite important, but the simpler geosta­tistical model was able to adequately represent fluvialreservoir architecture within the context and within the scope of the parameters represented here
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