<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20260826</CreaDate>
<CreaTime>10340200</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
</Esri>
<dataIdInfo>
<idAbs>&lt;p&gt;The AIIM Dashboard provides a user-friendly interface to view, access, and query predictive data generated by the Advanced Infrastructure Integrity Model (AIIM). AIIM is a foundational, pre-trained AI model developed to evaluate the physical integrity of offshore energy infrastructure including pipelines, platforms, and wells in the U.S. Gulf.&lt;/p&gt;&lt;p&gt;As many offshore structures approach or exceed their original design life, understanding their structural health is critical. This application allows users – including researchers, regulators, and industry - to interact directly with AIIM’s data and predicted asset lifespan, helping them identify opportunities for infrastructure reuse, plan hazard prevention strategies, and target areas for remediation.&lt;/p&gt;&lt;p&gt;To forecast remaining operational lifespan of offshore oil and gas infrastructure assets, the underlying AIIM model conducts a comprehensive, multivariate machine learning assessment. The application allows users to query and visualize how various factors impact structural integrity, including:&lt;/p&gt;&lt;p&gt;• Operational Wear-and-Tear: Daily operational stressors.&lt;/p&gt;&lt;p&gt;• Environmental Loadings: Short- and long-term effects from waves, storms, and ocean currents.&lt;/p&gt;&lt;p&gt;• Geohazards: Specific environmental risks, such as submarine landslide likelihood.&lt;/p&gt;&lt;p&gt;• Asset Characteristics: Structural age, materials, and platform or well types.&lt;/p&gt;&lt;p&gt;• Incident Reports: Historical incident event data.&lt;/p&gt;&lt;p&gt;A recipient of the 2022 TechConnect National Innovation Award recipient, NETL’s AIIM framework bridges the gap between advanced machine learning and practical, strategic decision-making. More information on the method and applications of AIIM can be found at https://edx.netl.doe.gov/offshore/portfolio-items/assessing-current-and-future-infrastructure-hazards. &lt;/p&gt;&lt;p&gt;Dataset Citation:&lt;font color='#000000'&gt; &lt;/font&gt;&lt;font color='#2f4f4f' size='3'&gt;&lt;span style='margin:0px; padding:0px; line-height:14px; font-family:Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif; font-variant-ligatures:none !important;'&gt;&lt;span style='margin:0px; padding:0px;'&gt;Romeo, L., Dyer, A., Wenzlick, M., Duran, R., Nelson, J., Sabbatino, M., Wingo, P., Rose, K., and Bauer, J. 2021.&lt;/span&gt;&lt;span style='margin:0px; padding:0px;'&gt; Comprehensive GOM Federal Waters Platform, Incident, Metocean, and Geohazard Dataset, https://edx.netl.doe.gov/dataset/comprehensive-gom-federal-waters-platform-incident-metocean-and-geohazard-dataset, DOI: 10.18141/1779221&lt;/span&gt;&lt;/span&gt;&lt;span style='margin:0px; padding:0px; line-height:14px; font-family:Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;'&gt; &lt;/span&gt;&lt;/font&gt;&lt;/p&gt;</idAbs>
<searchKeys>
<keyword>AIIM</keyword>
<keyword>Infrastructure</keyword>
<keyword>Offshore</keyword>
<keyword>Platforms</keyword>
<keyword>Oil and Gas</keyword>
<keyword>Gulf</keyword>
<keyword>Production</keyword>
</searchKeys>
<idPurp>Existing platforms in the Gulf of America with machine learning prediction outputs to support the AIIM Dashboard. The Advanced Infrastructure Integrity Model (AIIM) is a foundational, pre-trained artificial intelligence (AI) developed to help evaluate the integrity of offshore energy infrastructure including pipelines, platforms, wells in the U.S Gulf. Using multiple, multivariate machine learning models, AIIM analyzes complex data systems to deliver predictive insights for hazard prevention, life extension, and infrastructure reuse. Because it is built as a foundational model, users can leverage its AI-ready data and pre-trained framework as a starting point, integrating their own proprietary or localized datasets to further train and customize the model for their specific operational needs. </idPurp>
<idCredit>Schooley, C., Romeo, L., Zaengle, D., Pfander, I., Duran, R., Sharma, M., Bauer, J., Rose, K., (2026) Advanced Infrastructure Integrity Modeling Dashboard, https://edx.netl.doe.gov/dataset/offshore-aiim-dashboard</idCredit>
<resConst>
<Consts>
<useLimit>&lt;div&gt;&lt;b&gt;Disclaimer: &lt;/b&gt;&lt;/div&gt;&lt;div&gt;This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. &lt;/div&gt;&lt;div&gt;&lt;b&gt;&lt;br /&gt;&lt;/b&gt;&lt;/div&gt;&lt;div&gt;&lt;b&gt;Acknowledgement:  &lt;/b&gt;&lt;/div&gt;&lt;div&gt;This work was performed in support of the U.S. Department of Energy's Hydrocarbon and Geothermal Energy Office Energy Production Innovations field work proposal, FE-1025020, and executed through the National Energy Technology Laboratory (NETL) Research &amp;amp; Innovation Center.&lt;/div&gt;&lt;div&gt;&lt;b&gt;&lt;br /&gt;&lt;/b&gt;&lt;/div&gt;&lt;div&gt;&lt;b&gt;Licensing:&lt;/b&gt; &lt;/div&gt;&lt;div&gt;Creative Commons Attribution (For more information see: https://opendefinition.org/licenses/cc-by/) &lt;/div&gt;&lt;div&gt;&lt;b&gt;&lt;br /&gt;&lt;/b&gt;&lt;/div&gt;&lt;div&gt;&lt;b&gt;Citation:&lt;/b&gt; &lt;/div&gt;&lt;div&gt;Schooley, C., Romeo, L., Zaengle, D., Pfander, I., Duran, R., Sharma, M., Bauer, J., Rose, K., (2026) Advanced Infrastructure Integrity Modeling Dashboard, https://edx.netl.doe.gov/dataset/offshore-aiim-dashboard&lt;/div&gt;&lt;div&gt;&lt;b&gt;&lt;br /&gt;&lt;/b&gt;&lt;/div&gt;&lt;div&gt;&lt;b&gt;Support: &lt;/b&gt;&lt;/div&gt;&lt;div&gt;Contact edxspatial@netl.doe.gov for support.  &lt;/div&gt;&lt;div&gt;&lt;br /&gt;&lt;/div&gt;</useLimit>
</Consts>
</resConst>
<idCitation>
<resTitle>Existing_Platforms_with_Pred_122023</resTitle>
</idCitation>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">iVBORw0KGgoAAAANSUhEUgAAAMgAAACFCAYAAAAenrcsAAA1fklEQVR4Xu19918bd7Z2fns/OBgQ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</Data>
</Thumbnail>
</Binary>
</metadata>
