Search NASA⌕ Search

Engineering topics

Justman, Devin

Publications and source records attributed to Justman, Devin.

23 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Oklahoma structural complexity data

Zipped file contains raster data (TIF) files and thumbnail image (PNG) files associated with modeling known and predicting structural complexity (SC) for the state of Oklahoma, two SIMPA simulation files (.SIJN) and two README (.txt) files to run both the known SC and proxy SC models using the SIMPA tool, and a "Source data catalog.xlsx" file that provides information on the source data and how it was used to represent each raster Note: Metadata including processing steps can be viewed in ESRI's ArcCatalog software

raster↗
DOE OSTI2019

Cumulative Spatial Impact Layers: A Novel Multivariate Spatio-Temporal Analytical Summarization Tool

Scientific inquiry often requires analysis of multiple spatio-temporal datasets, ranging in type and size, using complex multi-step processes demanding an understanding of GIS theory and software. Cumulative Spatial Impact Layers (CSIL) is a GIS-based tool that summarizes spatio-temporal datasets based on overlapping features and attributes. Leveraging a recursive quadtree method, and applying multiple additive frameworks, the CSIL tool allows users to analyze raster and vector datasets by calculating data, record, or attribute density. Providing an efficient and robust method for summarizing disparate, multi-format, multi-source geospatial data, CSIL addresses the need for a new integration approach and resulting geospatial product. The built-in flexibility of the CSIL tool allows users to answer a range of spatially-driven questions. Example applications are provided in this paper to illustrate the versatility and variety of uses for this CSIL tool and method. Use cases include addressing regulatory decision-making needs, economic modeling, and resource management. Performance reviews for each use case are also presented, demonstrating how CSILs provides a more efficient and robust approach to assess a range of multivariate spatial data for a variety of uses.

58 GEOSCIENCES↗
DOE OSTI2018

Oklahoma Wellbore Rasters

Seven raster surfaces generated from wellbore information that are thought to influence fluid and or gas migration in the subsurface. Wellbore information was originally retrieved from the IHS Energy Group (current as of April 2015), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Processing of wellbore information into gridded cells was performed to provide a graphic solution to overcome the problem of displaying proprietary well data. No proprietary data are displayed or included in the cell maps. These rasters were developed to serve as inputs to the SIMPA (Spatially Weighted Multivariate Probabilistic Assessment) tool. Each raster surface is a derivative product of wellbore dataset. Each raster represents a single wellbore attribute or combination of attributes that speak to the following wellbore characteristics: number of recompletions, year spud, year abandoned, year completed, number of abandoned wells, hole direction, switch from production to injection. The original wellbore information, retrieved from the IHS Energy Group, are in the form of points – these derivative rasters aggregate point attributes to approximately 1,000-meter resolution grid cells. Each raster only includes cells that contain wellbores with the characteristics represented in each surface (i.e. if the wellbores in a given cell have no year abandoned data, the cell is not included in the raster). Since the raster cells combine data from multiple points in many cases, methods such as the average, minimum, and count are used to summarize the information in each cell. The specific operations used to develop each raster are detailed in its metadata.

Abandoned↗
DOE OSTI2018

Global Oil & Gas Infrastructure Features Database EDX Spatial Web Map

This submission offers a link to a web mapping application hosted instance of the Global Oil & Gas Features Database (GOGI), via EDX Spatial. This offers users with the ability to visualize, interact, and create maps with data of their choice, as well as download specific attributes or fields of view from the database. This data can also be downloaded as a File Geodatabse from EDX at https://edx.netl.doe.gov/dataset/global-oil-gas-features-database. Access the technical report describing how this database was produced using the following link: https://edx.netl.doe.gov/dataset/development-of-an-open-global-oil-and-gas-infrastructure-inventory-and-geodatabase” This data was developed using a combination of big data computing, custom search and data integration algorithms, and expert driven search to collect open oil and gas data resources worldwide. This approach identified over 380 data sets and integrated more than 4.8 million features into the GOGI database. Acknowledgements: This work was funded under the Climate and Clean Air Coalition (CCAC) Oil and Gas Methane Science Studies. The studies are managed by United Nations Environment in collaboration with the Office of the Chief Scientist, Steven Hamburg of the Environmental Defense Fund. Funding was provided by the Environmental Defense Fund, OGCI Companies (Shell, BP, ENI, Petrobras, Repsol, Total, Equinor, CNPC, Saudi Aramco, Exxon, Oxy, Chevron, Pemex) and CCAC.

gas↗