<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20260826</CreaDate>
<CreaTime>10433000</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>Production</keyword>
<keyword>Infrastructure</keyword>
<keyword>Platforms</keyword>
<keyword>Gulf</keyword>
</searchKeys>
<idPurp>Select platforms with connections to production wells. 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>Select_Platforms_to_Wells_052826</resTitle>
</idCitation>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">iVBORw0KGgoAAAANSUhEUgAAAMgAAACFCAYAAAAenrcsAABDpklEQVR4Xu2dd4BV1bn2zzRmmGEY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=</Data>
</Thumbnail>
</Binary>
</metadata>
