Arctic Economics Model ...

AEM (Arctic Economics Model) for oil and gas was developed to provide an analytic framework for understanding the arctic area resources. It provides the capacity for integrating the resource and technology information gathered by the arctic research and development (R&D) program, measuring the b...

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Bibliographic Details
Main Author: None, None
Format: Article in Journal/Newspaper
Language:English
Published: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) 1995
Subjects:
Online Access:https://dx.doi.org/10.11578/dc.20180625.7
https://www.osti.gov/doecode/biblio/12466
id ftdatacite:10.11578/dc.20180625.7
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spelling ftdatacite:10.11578/dc.20180625.7 2023-08-27T04:06:52+02:00 Arctic Economics Model ... None, None 1995 https://dx.doi.org/10.11578/dc.20180625.7 https://www.osti.gov/doecode/biblio/12466 en eng Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) SoftwareSourceCode Arctic Economics Model Software article 1995 ftdatacite https://doi.org/10.11578/dc.20180625.7 2023-08-07T14:24:23Z AEM (Arctic Economics Model) for oil and gas was developed to provide an analytic framework for understanding the arctic area resources. It provides the capacity for integrating the resource and technology information gathered by the arctic research and development (R&D) program, measuring the benefits of alternaive R&D programs, and providing updated estimates of the future oil and gas potential from arctic areas. AEM enables the user to examine field or basin-level oil and gas recovery, costs, and economics. It provides a standard set of selected basin-specified input values or allows the user to input their own values. AEM consists of five integrated submodels: geologic/resource submodel, which distributes the arctic resource into 15 master regions, consisting of nine arctic offshore regions, three arctic onshore regions, and three southern Alaska (non-arctic) regions; technology submodel, which selects the most appropriate exploration and production structure (platform) for each arctic basin and ... Article in Journal/Newspaper Arctic Basin Arctic Alaska DataCite Metadata Store (German National Library of Science and Technology) Arctic
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
description AEM (Arctic Economics Model) for oil and gas was developed to provide an analytic framework for understanding the arctic area resources. It provides the capacity for integrating the resource and technology information gathered by the arctic research and development (R&D) program, measuring the benefits of alternaive R&D programs, and providing updated estimates of the future oil and gas potential from arctic areas. AEM enables the user to examine field or basin-level oil and gas recovery, costs, and economics. It provides a standard set of selected basin-specified input values or allows the user to input their own values. AEM consists of five integrated submodels: geologic/resource submodel, which distributes the arctic resource into 15 master regions, consisting of nine arctic offshore regions, three arctic onshore regions, and three southern Alaska (non-arctic) regions; technology submodel, which selects the most appropriate exploration and production structure (platform) for each arctic basin and ...
format Article in Journal/Newspaper
author None, None
spellingShingle None, None
Arctic Economics Model ...
author_facet None, None
author_sort None, None
title Arctic Economics Model ...
title_short Arctic Economics Model ...
title_full Arctic Economics Model ...
title_fullStr Arctic Economics Model ...
title_full_unstemmed Arctic Economics Model ...
title_sort arctic economics model ...
publisher Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
publishDate 1995
url https://dx.doi.org/10.11578/dc.20180625.7
https://www.osti.gov/doecode/biblio/12466
geographic Arctic
geographic_facet Arctic
genre Arctic Basin
Arctic
Alaska
genre_facet Arctic Basin
Arctic
Alaska
op_doi https://doi.org/10.11578/dc.20180625.7
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