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At least 199 records · Page 11

Globus platform-as-a-service for collaborative science applications

Globus, developed as Software-as-a-Service (SaaS) for research data management, also provides APIs that constitute a flexible and powerful Platform-as-a-Service (PaaS) to which developers can outsource data management activities such as transfer and sharing, as well as identity, profile and group management. By providing these frequently important but always challenging capabilities as a service, accessible over the network, Globus PaaS streamlines web application development and makes it easy for individuals, teams, and institutions to create collaborative applications such as science gateways for science communities. We introduce the capabilities of this platform and review representative applications.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

The Deep Impact Network Experiment Operations Center Monitor and Control System

The Interplanetary Overlay Network (ION) software at JPL is an implementation of Delay/Disruption Tolerant Networking (DTN) which has been proposed as an interplanetary protocol to support space communication. The JPL Deep Impact Network (DINET) is a technology development experiment intended to increase the technical readiness of the JPL implemented ION suite. The DINET Experiment Operations Center (EOC) developed by JPL's Protocol Technology Lab (PTL) was critical in accomplishing the experiment. EOC, containing all end nodes of simulated spaces and one administrative node, exercised publish and subscribe functions for payload data among all end nodes to verify the effectiveness of data exchange over ION protocol stacks. A Monitor and Control System was created and installed on the administrative node as a multi-tiered internet-based Web application to support the Deep Impact Network Experiment by allowing monitoring and analysis of the data delivery and statistics from ION. This Monitor and Control System includes the capability of receiving protocol status messages, classifying and storing status messages into a database from the ION simulation network, and providing web interfaces for viewing the live results in addition to interactive database queries.

Delay/Disruption Tolerant Network (DTN)↗

LSE-319: LSST Science Platform Vision Document

This document defines and describes the "LSST Science Platform," a set of integrated web applications and services deployed at the LSST Data Access Centers (DACs) through which the scientific community will access, visualize, subset, and perform next-to-the-data analysis of the data collected by the Large Synoptic Survey Telescope (LSST). These services can be broken down to three different "Aspects": a web Portal, designed to provide essential data access and visualization services through a simple-to-use website, a Notebook environment, that will provide a Jupyter Notebook-like interface, based on JupyterLab, enabling next-to-the-data analysis, and an extensive set of Web APIs that the users will be able to use to remotely examine the LSST data set using tools they're already familiar with. This document lays out the high-level vision for the aforementioned Aspects and some associated backend services. It is intentionally brief, and meant to generally guide the flow-down of requirements and development of product specifications, prioritization, and plans for the Agile development of the relevant elements of the DM system.

79 ASTRONOMY AND ASTROPHYSICS↗

Dual Context: Leveraging Structured Application Context for Code Generation and Runtime Feature Activation via Chat Interfaces

Integrating artificial intelligence (AI) capabilities into software applications typically involves two common paths. For developers, AI assists in generating and documenting source code and other related software engineering efforts. For users, AI assists them through question-and-answer exchanges via chatbots. Both approaches have their value, but neither effectively leverages the modularity of component-based architectures that modern web application frameworks offer. We implement a proof of concept within a centralized suite of applications used for the Atmospheric Radiation Measurement (ARM) Data Center Operational Tools, where we introduce a third integration path through the ARM Context Engine (ACE). ACE is a context driven system that uses structured contextual specifications to enable Large Language Models (LLMs) to render interactive and feature-rich user interface (UI) components directly within chat responses, alongside or in place of conventional text outputs. These specifications serve two important purposes across what we call code context and UI context. Code context provides AI-assisted development tools with structured application knowledge beyond raw code, including component relationships, architectural patterns and schematic information, enabling the generation of consistent, well-structured code. UI context defines the rules for enabling and rendering component features at runtime based on the user's natural language input, allowing end users to activate capabilities such as data export, filtering, and pagination within chat responses, without requiring code changes or redeployment. We demonstrate, through a comparative evaluation against general-purpose AI chatbots, that context-driven component rendering provides interactive capabilities that text-based responses cannot replicate, including deterministic component behavior, application-consistent design language, and on-demand feature activation. A development effort comparison further shows that features that traditionally require multi-step development cycles can be activated with a single naturallanguage request. In this ongoing work, we present ACE as an emerging approach to AI integration that positions modular, well-documented software architecture as the foundation for AI-ready applications. ACE treats context as a shared resource across both development and user-facing AI, bringing cohesion to conventionally disconnected efforts, bridging developer tooling and end-user capabilities within a single framework.

Tadimeti, Vijay [ORNL]↗

Evapotranspiration-Based Irrigation Scheduling in Cool-Season Vegetables

Crop evapotranspiration (ETc) is strongly linked with photosynthetically active vegetation fraction (Fc). Estimation of ETc may support efficiency gains in irrigation water management, which in turn can mitigate nitrate leaching, promote water supply sustainability, and reduce energy costs associated with water pumping or transport. The University of California Cooperative Extension operates the CropManage (CM) model as a freely-available web-application for growers and consultants to support irrigation and nitrogen scheduling decisions. CM accounts for the rapid growth and typically brief cycle of cool-season vegetables, where Fc and crop coefficient (fraction of reference ET) can change daily during canopy development. Daily weather conditions are inherently accounted for by use of grass reference ETo data imported from the California Dept. Water Resources. Crop water requirement calculations are output in terms of irrigation system runtime. Empirical equations are used to estimate daily Fc time-series for a given crop type, primarily as a function of planting date and expected harvest. An applications programming interface (API) enables CM to import satellite-based Fc observations from NASA's Satellite Irrigation Management Support, which uses Landsat imagery to monitor about eight million irrigation acres statewide. The API is intended to provide a check on internal CM predictions of Fc and to facilitate expansion of the web-app to new crops and regions. A replicated irrigation trial was performed on cauliflower during spring/summer 2018 at the USDA Agricultural Research Station in Salinas, CA. The crop was established by sprinkler irrigation, and CropManage was then used to guide a series of drip irrigation treatments at 50%, 75%, 100%, and 150% of ETc replacement levels. Results will be presented with respect to water use efficiency, nitrogen use efficiency, biomass yield, and marketable yield. Additional findings will be presented for a celery trial harvested during autumn 2018.

Johnson, Lee↗

PSpecteR: A User-Friendly and Interactive Application for Visualizing Top-Down and Bottom-Up Proteomics Data in R

Visual examination of mass spectrometry data is necessary to assess data quality and to facilitate data exploration. Graphics provide the means to evaluate spectral properties, test alternative peptide/protein sequence matches, prepare annotated spectra for publication, and fine-tune parameters during wet lab procedures. Visual inspection of MS data is hindered by proprietary proteomics visualization software designed for particular workflows and academic software that lack visualization tools. We built PSpecteR, an open-source and interactive R Shiny web application to address these issues, with support for several steps of proteomics data processing, including: reading various mass spectrometry files, running open-source database search tools, labelling spectra with fragmentation patterns, testing post-translational modifications, plotting where identified fragments map to reference sequences, and visualizing algorithmic output and metadata. All figures, tables, and spectra are exportable within one easy-to-use graphical user interface. Our current software provides a flexible and modern R framework to support fast implementation of additional features. The open source code is readily available (https://github.com/EMSL-Computing/PSpecteR), and a PSpecteR Docker container (https://hub.docker.com/r/emslcomputing) is available for easy local installation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Providing Long-term Solar and Meteorological Resource Information from NASA Research through the GIS-Enabled POWER Web Services Portal

Solar and other renewable energy systems are optimized using geophysical parameters describing information about the solar resource and meteorological environments and how those environments may be changing in time. The Prediction of Worldwide Renewable Energy Resource (POWER) team at the NASA LaRC Research Center deployed its first version of the revitalized POWER geophysical parameter website that employs Esri Geographic Information System (GIS) tools. This web application provides access to both time series and climatological data sets spanning from a few days behind real-time back to the early 1980’s with a spatial resolution of 0.5 x 0.5 degree, thus extending over 30 years. The GIS tools enable, generate and store climatological averages using spatial queries and calculations in a spatial database resulting in greater accessibility to government agencies, industry and individuals. There is an API that provides data through a URL coding and can also invoked inside user software packages. Output data formats now include ASCII, CSV, geoTiff, JSON and .netCDF. Since May 2018, over 10.4 TB of data have been delivered to fulfill over 110 million data requests from 240,000 unique user IPs (https://power.larc.nasa.gov). This presentation provides an overview of this project and the current version of the new POWER web capabilities through to the end usage. Surface solar parameters are adapted from both the NASA/GEWEX (Global and Energy Water Cycle Exchange) SRB (Surface Radiation Budget) project and the CERES (Clouds and Earth’s Radiant Energy System) data products. The meteorological parameters are adapted from NASA’s MERRA-2 (Modern Era Retrospective-analysis for Research and Applications). We review uncertainty of various basic parameters using surface measurements. After the introduction, we specifically discuss various clusters of parameters for equator pointing tilted surfaces that provide for the estimation of optimal tilt angle by month and year. The discussion will emphasize a few examples of how solar and building engineers are using the data products. We will then preview the capabilities of Version 2 featuring examples of hourly solar and meteorological data products, customized user reports and expanded web mapping services from CERES data products. The web services provide a unique, expandable resource for renewable energy systems engineers to design, evaluate and optimize to environments worldwide.

Solar Resource↗

National Ignition Facility and Managing Location, Component, and State

The National Ignition Facility (NIF) at the Lawrence Livermore National Laboratory is a stadium-sized facility that contains a 192-beam, 1.8-Megajoule, 500-Terawatt, ultraviolet laser system coupled with a 10-meter diameter target chamber. There are over 6,200 Line Replaceable Units (LRUs) comprised of more than 104,000 serialized parts that make up the NIF. Each LRU is a modular unit typically composed of a mechanical housing, laser optics (glass, lenses, or mirrors), and utilities. To date, there are more than 120,000 data sets created to characterize the attributes of these parts. Greater than 51,000 Work Permits have been issued to install, maintain, and troubleshoot the components. One integrated system is used to manage these data, and more. The Location Component and State (LoCoS) system is a web application built using Java Enterprise Edition technologies and is accessed by over 1,200 users. It is either directly or indirectly involved with each aspect of NIF work activity, and interfaces with ten external systems including the Integrated Computer Control System (ICCS) and the Laser Performance Operations Model (LPOM). Besides providing business functionality, LoCoS also acts as the NIF enterprise service bus. In this role, numerous integration approaches had to be adopted including: file exchange, database sharing, queuing, and web services in order to accommodate various business, technical, and security requirements. Architecture and implementation decisions are discussed.

42 ENGINEERING↗

Property Prediction of Organic Donor Molecules for Photovoltaic Applications Using Extremely Randomized Trees

Organic solar cells are an inexpensive, flexible alternative to traditional silicon-based solar cells but disadvantaged by low power conversion efficiency due to empirical design and complex manufacturing processes. This process can be accelerated by generating a comprehensive set of potential candidates. However, this would require a laborious trial and error method of modeling all possible polymer configurations. A machine learning model has the potential to accelerate the process of screening potential donor candidates by associating structural features of the compound using molecular fingerprints with their highest occupied molecular orbital energies. In this paper, extremely randomized tree learning models are employed for the prediction of HOMO values for donor compounds, and a web application is developed. Finally, the proposed models outperform neural networks trained on molecular fingerprints as well as SMILES, as well as other state-of-the-art architectures such as Chemception and Molecular Graph Convolution on two datasets of varying sizes.

42 ENGINEERING↗

Advancing molecular machine learning representations with stereoelectronics-infused molecular graphs

Molecular representation is a critical element in our understanding of the physical world and the foundation for modern molecular machine learning. Previous molecular machine learning models have used strings, fingerprints, global features and simple molecular graphs that are inherently information-sparse representations. However, as the complexity of prediction tasks increases, the molecular representation needs to encode higher fidelity information. This work introduces a new approach to infusing quantum-chemical-rich information into molecular graphs via stereoelectronic effects, enhancing expressivity and interpretability. Learning to predict the stereoelectronics-infused representation with a tailored double graph neural network workflow enables its application to any downstream molecular machine learning task without expensive quantum-chemical calculations. We show that the explicit addition of stereoelectronic information substantially improves the performance of message-passing two-dimensional machine learning models for molecular property prediction. We show that the learned representations trained on small molecules can accurately extrapolate to much larger molecular structures, yielding chemical insight into orbital interactions for previously intractable systems, such as entire proteins, opening new avenues of molecular design. Finally, we have developed a web application (simg.cheme.cmu.edu) where users can rapidly explore stereoelectronic information for their own molecular systems.

Boiko, Daniil A↗

Spaceport Command and Control System - Support Software Development

The Information Architecture Support (IAS) Team, the component of the Spaceport Command and Control System (SCCS) that is in charge of all the pre-runtime data, was in need of some report features to be added to their internal web application, Information Architecture (IA). Development of these reports is crucial for the speed and productivity of the development team, as they are needed to quickly and efficiently make specific and complicated data requests against the massive IA database. These reports were being put on the back burner, as other development of IA was prioritized over them, but the need for them resulted in internships being created to fill this need. The creation of these reports required learning Ruby on Rails development, along with related web technologies, and they will continue to serve IAS and other support software teams and their IA data needs.

Information Architecture↗

ProteoSign: an end-user online differential proteomics statistical analysis platform

Profiling of proteome dynamics is crucial for understanding cellular behavior in response to intrinsic and extrinsic stimuli and maintenance of homeostasis. Over the last 20 years, mass spectrometry (MS) has emerged as the most powerful tool for large-scale identification and characterization of proteins. Bottom-up proteomics, the most common MS-based proteomics approach, has always been challenging in terms of data management, processing, analysis and visualization, with modern instruments capable of producing several gigabytes of data out of a single experiment. Here, we present ProteoSign, a freely available web application, dedicated in allowing users to perform proteomics differential expression/abundance analysis in a userfriendly and self-explanatory way. Although several non-commercial standalone tools have been developed for post-quantification statistical analysis of proteomics data, most of them are not end-user appealing as they often require very stringent installation of programming environments, third-party software packages and sometimes further scripting or computer programming. To avoid this bottleneck, we have developed a user-friendly software platform accessible via a web interface in order to enable proteomics laboratories and core facilities to statistically analyse quantitative proteomics data sets in a resource-efficient manner. ProteoSign is available at http://bioinformatics.med.uoc.gr/ProteoSign and the source code at https://github.com/yorgodillo/ ProteoSign.

59 BASIC BIOLOGICAL SCIENCES↗

Oyster Fisheries App

This project is creating a cloud‐enabled, HTML 5 web application to help oyster fishermen and state agencies apply Earth science to improve the management of this important natural and economic resource. The Oyster Fisheries app gathers and analyzes environmental and water quality information, and alerts fishermen and resources managers about problems in oyster fishing waters. An intuitive interface based on Google Maps displays the geospatial information and provides familiar interactive controls to the users. Alerts can be tailored to notify users when conditions in specific leases or public fishing areas require attention. The app is hosted on the Amazon Web Services cloud. It is being developed and tested using some of the latest web development tools such as web components and Polymer.

Perez Guerrero, Geraldo A.↗

Safety Analytics Forecasting and Evaluation Reporting (SAFER)

The SAFER Sandbox is a web application for testing various types of data visualization tools that analyze safety data across national laboratories. By enabling the user to visualize this data through visual and textual analyses, the SAFER Sandbox helps to facilitate the research and support for the National Nuclear Security Administration (NNSA) Office of Safety, Infrastructure and Operations (NA-50). Safety data across the national laboratory complex is not currently analyzed in one location. This prohibits administrators from viewing safety data trends and making large scale decisions based on a holistic view of the data. By implementing data analytics web services such as representative text summary, noun phrase extraction and graph exploration, users can view and explore safety data based on search queries. The data visualizations in the SAFER Sandbox reveal trends and point to items of concern based on safety data. The SAFER Sandbox is a testing ground for these visualizations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Modeling CO 2 Sequestration in Saline Aquifer and Depleted Oil Reservoir To Evaluate Regional CO 2 Sequestration Potential of Ozark Plateau Aquifer System, South-Central Kansas

1. Drilled, cored, and logged three wells to the basement and collecting more than 2,700 ft of conventional core; obtained 20 m i2 of multicomponent 3D seismic imaging and merged and reprocessed more than 125 mi 2 of existing 3D seismic data for use in modeling CO 2 - EOR oil recovery and CO 2 storage in five oil fields in southern Kansas. 2. Determined the technical feasibility of injecting and sequestering CO 2 in a set of four depleted oil reservoirs in the Cutter, Pleasant Prairie South, Eubank, and Shuck fields in southwest Kansas; of concurrently recovering oil from those fields; and of quantifying the volumes of CO2 sequestered and oil recovered during the process. 3. Formed a consortium of six oil operating companies, five of which own and operate the four fields. The consortium became part of the Southwest Kansas CO 2 -EOR Initiative for the purpose of sharing data, knowledge, and interest in understanding the potential for CO 2 -EOR in Kansas. 4. Built a regional well database covering 30,000 mi 2 and containing stratigraphic tops from ~90,000 wells; correlated 30 major stratigraphic horizons; digitized key wells, including wireline logs and sample logs; and analyzed more than 3,000 drill stem tests to establish that fluid levels in deep aquifers below the Permian evaporites are not connected to the surface and therefore pressures are not hydrostatic. Connectivity with the surface aquifers is lacking because shale aquitards and impermeable evaporite layers consist of both halite and anhydrite. 5. Developed extensive web applications and an interactive mapping system that do the following: a. Facilitate access to a wide array of data obtained in the study, including core descriptions and analyses, sample logs, digital (LAS) well logs, seismic data, gravity and magnetics maps, structural and stratigraphic maps, inferred fault traces, earthquakes, Class I and II disposal wells, and surface lineaments. b. Provide real-time analysis of the project dataset, including automated integration and viewing of well logs, core, core analyses, brine chemistry, and stratigraphy using the Java Profile app. A cross-section app allows for the display of log data for up to four wells at a time. 6. Integrated interpretations from the project’s interactive web-based mapping system to gain insights to aid in assessing the efficacy of geologic CO 2 storage in Kansas and insights toward understanding recent seismicity to aid in evaluating induced vs. naturally occurring earthquakes. 7. Developed a digital type-log system, including web-based software to modify and refine stratigraphic nomenclature to provide stakeholders a common means for communication about the subsurface. 8. Contracted use of a nuclear magnetic resonance (NMR) log and ran it slowly to capture response and characterize larger pores common for carbonate reservoirs. Used NMR to extend core analyses to apply permeability, relative permeability to CO 2 , and capillary pressure to the major rock types, each uniquely expressed as a reservoir quality index (RQI), present in the Mississippian and Arbuckle rocks. 9. Characterized and evaluated the possible role of microbes in dense brines. Used microbes to compliment H/O stable isotopes to fingerprint brine systems. Used perforation/swabbing to obtain samples from multiple hydrostratigraphic units and confirmed equivalent results using less expensive drill stem tests (DST). 10. Used an integrated approach from whole core, logs, tests, and seismic to verify and quantify properties of vuggy, brecciated, and fractured carbonate intervals. 11. Used complex geocellular static and dynamic models to evaluate regional storage capacity using large parallel processing. 12. Carbonates are complex reservoirs and CO 2 -EOR needs to move to the next generation to increase effectiveness of CO 2 and efficiency and safety of the injection.

54 ENVIRONMENTAL SCIENCES↗

Modeling CO 2 Sequestration in Saline Aquifer and Depleted Oil Reservoir To Evaluate Regional CO 2 Sequestration Potential of Ozark Plateau Aquifer System, South-Central Kansas

1. Drilled, cored, and logged three wells to the basement and collecting more than 2,700 ft of conventional core; obtained 20 m i2 of multicomponent 3D seismic imaging and merged and reprocessed more than 125 mi 2 of existing 3D seismic data for use in modeling CO 2 - EOR oil recovery and CO 2 storage in five oil fields in southern Kansas. 2. Determined the technical feasibility of injecting and sequestering CO 2 in a set of four depleted oil reservoirs in the Cutter, Pleasant Prairie South, Eubank, and Shuck fields in southwest Kansas; of concurrently recovering oil from those fields; and of quantifying the volumes of CO2 sequestered and oil recovered during the process. 3. Formed a consortium of six oil operating companies, five of which own and operate the four fields. The consortium became part of the Southwest Kansas CO 2 -EOR Initiative for the purpose of sharing data, knowledge, and interest in understanding the potential for CO 2 -EOR in Kansas. 4. Built a regional well database covering 30,000 mi 2 and containing stratigraphic tops from ~90,000 wells; correlated 30 major stratigraphic horizons; digitized key wells, including wireline logs and sample logs; and analyzed more than 3,000 drill stem tests to establish that fluid levels in deep aquifers below the Permian evaporites are not connected to the surface and therefore pressures are not hydrostatic. Connectivity with the surface aquifers is lacking because shale aquitards and impermeable evaporite layers consist of both halite and anhydrite. 5. Developed extensive web applications and an interactive mapping system that do the following: a. Facilitate access to a wide array of data obtained in the study, including core descriptions and analyses, sample logs, digital (LAS) well logs, seismic data, gravity and magnetics maps, structural and stratigraphic maps, inferred fault traces, earthquakes, Class I and II disposal wells, and surface lineaments. b. Provide real-time analysis of the project dataset, including automated integration and viewing of well logs, core, core analyses, brine chemistry, and stratigraphy using the Java Profile app. A cross-section app allows for the display of log data for up to four wells at a time. 6. Integrated interpretations from the project’s interactive web-based mapping system to gain insights to aid in assessing the efficacy of geologic CO 2 storage in Kansas and insights toward understanding recent seismicity to aid in evaluating induced vs. naturally occurring earthquakes. 7. Developed a digital type-log system, including web-based software to modify and refine stratigraphic nomenclature to provide stakeholders a common means for communication about the subsurface. 8. Contracted use of a nuclear magnetic resonance (NMR) log and ran it slowly to capture response and characterize larger pores common for carbonate reservoirs. Used NMR to extend core analyses to apply permeability, relative permeability to CO 2 , and capillary pressure to the major rock types, each uniquely expressed as a reservoir quality index (RQI), present in the Mississippian and Arbuckle rocks. 9. Characterized and evaluated the possible role of microbes in dense brines. Used microbes to compliment H/O stable isotopes to fingerprint brine systems. Used perforation/swabbing to obtain samples from multiple hydrostratigraphic units and confirmed equivalent results using less expensive drill stem tests (DST). 10. Used an integrated approach from whole core, logs, tests, and seismic to verify and quantify properties of vuggy, brecciated, and fractured carbonate intervals. 11. Used complex geocellular static and dynamic models to evaluate regional storage capacity using large parallel processing. 12. Carbonates are complex reservoirs and CO 2 -EOR needs to move to the next generation to increase effectiveness of CO 2 and efficiency and safety of the injection.

54 ENVIRONMENTAL SCIENCES↗

Modeling CO 2 Sequestration in Saline Aquifer and Depleted Oil Reservoir To Evaluate Regional CO 2 Sequestration Potential of Ozark Plateau Aquifer System, South-Central Kansas

1. Drilled, cored, and logged three wells to the basement and collecting more than 2,700 ft of conventional core; obtained 20 m i2 of multicomponent 3D seismic imaging and merged and reprocessed more than 125 mi 2 of existing 3D seismic data for use in modeling CO 2 - EOR oil recovery and CO 2 storage in five oil fields in southern Kansas. 2. Determined the technical feasibility of injecting and sequestering CO 2 in a set of four depleted oil reservoirs in the Cutter, Pleasant Prairie South, Eubank, and Shuck fields in southwest Kansas; of concurrently recovering oil from those fields; and of quantifying the volumes of CO2 sequestered and oil recovered during the process. 3. Formed a consortium of six oil operating companies, five of which own and operate the four fields. The consortium became part of the Southwest Kansas CO 2 -EOR Initiative for the purpose of sharing data, knowledge, and interest in understanding the potential for CO 2 -EOR in Kansas. 4. Built a regional well database covering 30,000 mi 2 and containing stratigraphic tops from ~90,000 wells; correlated 30 major stratigraphic horizons; digitized key wells, including wireline logs and sample logs; and analyzed more than 3,000 drill stem tests to establish that fluid levels in deep aquifers below the Permian evaporites are not connected to the surface and therefore pressures are not hydrostatic. Connectivity with the surface aquifers is lacking because shale aquitards and impermeable evaporite layers consist of both halite and anhydrite. 5. Developed extensive web applications and an interactive mapping system that do the following: a. Facilitate access to a wide array of data obtained in the study, including core descriptions and analyses, sample logs, digital (LAS) well logs, seismic data, gravity and magnetics maps, structural and stratigraphic maps, inferred fault traces, earthquakes, Class I and II disposal wells, and surface lineaments. b. Provide real-time analysis of the project dataset, including automated integration and viewing of well logs, core, core analyses, brine chemistry, and stratigraphy using the Java Profile app. A cross-section app allows for the display of log data for up to four wells at a time. 6. Integrated interpretations from the project’s interactive web-based mapping system to gain insights to aid in assessing the efficacy of geologic CO 2 storage in Kansas and insights toward understanding recent seismicity to aid in evaluating induced vs. naturally occurring earthquakes. 7. Developed a digital type-log system, including web-based software to modify and refine stratigraphic nomenclature to provide stakeholders a common means for communication about the subsurface. 8. Contracted use of a nuclear magnetic resonance (NMR) log and ran it slowly to capture response and characterize larger pores common for carbonate reservoirs. Used NMR to extend core analyses to apply permeability, relative permeability to CO 2 , and capillary pressure to the major rock types, each uniquely expressed as a reservoir quality index (RQI), present in the Mississippian and Arbuckle rocks. 9. Characterized and evaluated the possible role of microbes in dense brines. Used microbes to compliment H/O stable isotopes to fingerprint brine systems. Used perforation/swabbing to obtain samples from multiple hydrostratigraphic units and confirmed equivalent results using less expensive drill stem tests (DST). 10. Used an integrated approach from whole core, logs, tests, and seismic to verify and quantify properties of vuggy, brecciated, and fractured carbonate intervals. 11. Used complex geocellular static and dynamic models to evaluate regional storage capacity using large parallel processing. 12. Carbonates are complex reservoirs and CO 2 -EOR needs to move to the next generation to increase effectiveness of CO 2 and efficiency and safety of the injection.

54 ENVIRONMENTAL SCIENCES↗

Modeling CO 2 Sequestration in Saline Aquifer and Depleted Oil Reservoir To Evaluate Regional CO 2 Sequestration Potential of Ozark Plateau Aquifer System, South-Central Kansas

1. Drilled, cored, and logged three wells to the basement and collecting more than 2,700 ft of conventional core; obtained 20 m i2 of multicomponent 3D seismic imaging and merged and reprocessed more than 125 mi 2 of existing 3D seismic data for use in modeling CO 2 - EOR oil recovery and CO 2 storage in five oil fields in southern Kansas. 2. Determined the technical feasibility of injecting and sequestering CO 2 in a set of four depleted oil reservoirs in the Cutter, Pleasant Prairie South, Eubank, and Shuck fields in southwest Kansas; of concurrently recovering oil from those fields; and of quantifying the volumes of CO2 sequestered and oil recovered during the process. 3. Formed a consortium of six oil operating companies, five of which own and operate the four fields. The consortium became part of the Southwest Kansas CO 2 -EOR Initiative for the purpose of sharing data, knowledge, and interest in understanding the potential for CO 2 -EOR in Kansas. 4. Built a regional well database covering 30,000 mi 2 and containing stratigraphic tops from ~90,000 wells; correlated 30 major stratigraphic horizons; digitized key wells, including wireline logs and sample logs; and analyzed more than 3,000 drill stem tests to establish that fluid levels in deep aquifers below the Permian evaporites are not connected to the surface and therefore pressures are not hydrostatic. Connectivity with the surface aquifers is lacking because shale aquitards and impermeable evaporite layers consist of both halite and anhydrite. 5. Developed extensive web applications and an interactive mapping system that do the following: a. Facilitate access to a wide array of data obtained in the study, including core descriptions and analyses, sample logs, digital (LAS) well logs, seismic data, gravity and magnetics maps, structural and stratigraphic maps, inferred fault traces, earthquakes, Class I and II disposal wells, and surface lineaments. b. Provide real-time analysis of the project dataset, including automated integration and viewing of well logs, core, core analyses, brine chemistry, and stratigraphy using the Java Profile app. A cross-section app allows for the display of log data for up to four wells at a time. 6. Integrated interpretations from the project’s interactive web-based mapping system to gain insights to aid in assessing the efficacy of geologic CO 2 storage in Kansas and insights toward understanding recent seismicity to aid in evaluating induced vs. naturally occurring earthquakes. 7. Developed a digital type-log system, including web-based software to modify and refine stratigraphic nomenclature to provide stakeholders a common means for communication about the subsurface. 8. Contracted use of a nuclear magnetic resonance (NMR) log and ran it slowly to capture response and characterize larger pores common for carbonate reservoirs. Used NMR to extend core analyses to apply permeability, relative permeability to CO 2 , and capillary pressure to the major rock types, each uniquely expressed as a reservoir quality index (RQI), present in the Mississippian and Arbuckle rocks. 9. Characterized and evaluated the possible role of microbes in dense brines. Used microbes to compliment H/O stable isotopes to fingerprint brine systems. Used perforation/swabbing to obtain samples from multiple hydrostratigraphic units and confirmed equivalent results using less expensive drill stem tests (DST). 10. Used an integrated approach from whole core, logs, tests, and seismic to verify and quantify properties of vuggy, brecciated, and fractured carbonate intervals. 11. Used complex geocellular static and dynamic models to evaluate regional storage capacity using large parallel processing. 12. Carbonates are complex reservoirs and CO 2 -EOR needs to move to the next generation to increase effectiveness of CO 2 and efficiency and safety of the injection.

54 ENVIRONMENTAL SCIENCES↗