20260826
18455200
1.0
TRUE
<p><font color='#2f4f4f' size='3'><span style='margin:0px; padding:0px; line-height:14px; font-family:Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif; font-variant-ligatures:none !important;'><span style='margin:0px; padding:0px;'>Series of well or wellbore records by surface hole (location of well or wellbore at seafloor) or bottomhole (location of the deepest point of the wellbore in the subsurface) for production wells and other wells. Production wells are defined as wells or wellbores the record of which has a type labeled as </span><span style='margin:0px; padding:0px;'>oil, gas, production, or hydrocarbon, or a production record exists that is associated with the well or wellbore record. </span><span style='margin:0px; padding:0px;'>Other wells are defined as wells or wellbores the record of which has a type labeled does not include oil, gas, production, or hydrocarbon. Additionally, other wells do not have an associated production record. </span></span><span style='margin:0px; padding:0px; line-height:14px; font-family:Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;'> </span></font></p><div style='margin:0px; padding:0px; overflow:visible; clear:both; font-family:"Segoe UI", "Segoe UI Web", Arial, Verdana, sans-serif;'><p style='margin:16px 0px 0px; padding:0px; font-kerning:none; background-color:transparent;'><font color='#2f4f4f' size='3'><span style='margin:0px; padding:0px; line-height:14px; font-family:Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif; font-variant-ligatures:none !important;'>Dataset Citations:</span></font></p><p style='margin:16px 0px 0px; padding:0px; font-kerning:none; background-color:transparent;'><font color='#2f4f4f' size='3'><span style='margin:0px; padding:0px; line-height:14px; font-family:Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif; font-variant-ligatures:none !important;'>Romeo, L., Schooley, C., Sharma, M., and J. Bauer. </span><span style='margin:0px; padding:0px; font-style:italic; line-height:14px; font-family:Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif; font-variant-ligatures:none !important;'>In Review.</span><span style='margin:0px; padding:0px; line-height:14px; font-family:Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif; font-variant-ligatures:none !important;'><span style='margin:0px; padding:0px;'> </span><span style='margin:0px; padding:0px;'>U.S. Gulf Wellbore Dataset. </span></span><span style='margin:0px; padding:0px; line-height:14px; font-family:Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;'> </span></font></p></div><div style='margin:0px; padding:0px; overflow:visible; clear:both; font-family:"Segoe UI", "Segoe UI Web", Arial, Verdana, sans-serif;'><p style='margin:16px 0px 0px; padding:0px; font-kerning:none; background-color:transparent;'><font color='#2f4f4f' size='3'><span style='margin:0px; padding:0px; line-height:14px; font-family:Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif; font-variant-ligatures:none !important;'><span style='margin:0px; padding:0px;'>Pfander</span><span style='margin:0px; padding:0px;'>, P.</span><span style='margin:0px; padding:0px;'>, Romeo</span><span style='margin:0px; padding:0px;'>, L., </span><span style='margin:0px; padding:0px;'>Sabbatino</span><span style='margin:0px; padding:0px;'>, M., </span><span style='margin:0px; padding:0px;'>Tetteh</span><span style='margin:0px; padding:0px;'>, D.A.</span><span style='margin:0px; padding:0px;'>, Cleaveland</span><span style='margin:0px; padding:0px;'>, C., </span><span style='margin:0px; padding:0px;'>Rich</span><span style='margin:0px; padding:0px;'>, M., </span><span style='margin:0px; padding:0px;'>Nelson</span><span style='margin:0px; padding:0px;'>, C., </span><span style='margin:0px; padding:0px;'>Sharma</span><span style='margin:0px; padding:0px;'>, M., </span><span style='margin:0px; padding:0px;'>Amrine</span><span style='margin:0px; padding:0px;'>, D.C., </span><span style='margin:0px; padding:0px;'>Bauer</span><span style='margin:0px; padding:0px;'>, J., and K. Rose. (2026).</span><span style='margin:0px; padding:0px;'> WELLS Database, </span></span><a href='https://edx.netl.doe.gov/dataset/wells_database' style='margin:0px; padding:0px; text-decoration:none;' target='_blank'><span style='margin:0px; padding:0px; text-decoration:underline; line-height:14px; font-family:Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif; font-variant-ligatures:none !important;'><span style='margin:0px; padding:0px;'>https://edx.netl.doe.gov/dataset/wells_database</span></span></a><span style='margin:0px; padding:0px; line-height:14px; font-family:Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif; font-variant-ligatures:none !important;'><span style='margin:0px; padding:0px;'>,</span><span style='margin:0px; padding:0px;'> </span><span style='margin:0px; padding:0px;'>DOI:10.18141/1964068</span></span><span style='margin:0px; padding:0px; line-height:14px; font-family:Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;'> </span></font></p></div><p>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.</p><p>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.</p><p>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:</p><p>• Operational Wear-and-Tear: Daily operational stressors.</p><p>• Environmental Loadings: Short- and long-term effects from waves, storms, and ocean currents.</p><p>• Geohazards: Specific environmental risks, such as submarine landslide likelihood.</p><p>• Asset Characteristics: Structural age, materials, and platform or well types.</p><p>• Incident Reports: Historical incident event data.</p><p>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. </p>
AIIM
Offshore
Wells
Production
Infrastructure
Merged production and non-production for the U.S. Gulf Region, only using fields from non-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.
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
<div><b>Disclaimer: </b></div><div>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. </div><div><b><br /></b></div><div><b>Acknowledgement: </b></div><div>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 & Innovation Center.</div><div><b><br /></b></div><div><b>Licensing:</b> </div><div>Creative Commons Attribution (For more information see: https://opendefinition.org/licenses/cc-by/) </div><div><b><br /></b></div><div><b>Citation:</b> </div><div>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</div><div><b><br /></b></div><div><b>Support: </b></div><div>Contact edxspatial@netl.doe.gov for support. </div><div><br /></div>
All_Wells_Simplified_0426_forApp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