Esri User Conference 2025 Highlights
Geonamic was excited to attend the 45th annual Esri User Conference held in San Diego, California from July 14-18. GIS professionals from more than 130 countries gathered to share and learn from each other. The conference featured technical demonstrations, expos, networking opportunities, workshops, and user presentations showcasing how GIS technology is being used in various sectors across the globe. Esri highlighted some key enhancements, including continued advancement of GeoAI, Spatial Analytics, and Large Language Models integration, which all have exciting implications for the future of the oil and gas pipeline industry.
The Esri AI framework is now extensible to support unique linear referencing and pipeline requirements. Geonamic has active plans to incorporate this development into our PipelineOffice Studio software platform. The rapidly evolving AI Assistants in the Esri platform have several potential benefits for our oil and gas pipeline customers:
- Streamline exploration of pipeline inspection or asset data.
- Quicker understanding of risk, HCA modeling, and ILI results.
- Support for new automated workflows for field data capture.
- Reduced workload and enhanced access to technical documentation.
- Simplification of pipeline integrity management reporting and complex queries.
Another conference highlight was learning about the vast improvements with the ArcGIS Pipeline Referencing (APR) platform, including enhancements to the reporting and analytics engine, data loading and editing improvements, and new Experience Builder Widgets. Geonamic is working with many clients to support data migration and consolidation to PODS 7 and UPDM and in customizing APR for unique client workflows and requirements. Our entire technology suite supports APR and the latest PODS and UPDM releases, including our advanced integrity and risk tools.
Geonamic sponsored the Energy Resources Social again this year, located at the scenic Coronado Terrace overlooking the San Diego Marina. We connected with old friends and new, swapping ideas and insights for the exciting future of the oil and gas pipeline industry.
The Esri UC was a remarkable week filled with knowledge sharing, exploration of the latest advancements in GIS technology/the Esri platform, networking with peers and industry experts, and overall GIS community building- Geonamic can’t wait to be back next year!
Want to learn more about our Esri UC experience? Connect with us at info@geonamic.com.
From left to right: Brad Schaaf (Geonamic), Jasim Al Balushi (OQGN), Saif Alsaadi (OQGN), Pradeep Shriyan (Esri Muscat), and Sujeet Shetty (Esri Muscat)
OQGN – Special Achievement in GIS (SAG) Award
OQGN successfully upgraded their pipeline data model to PODS 7, along with an ArcGIS Enterprise upgrade and deployment of highly successful ArcGIS mobile and portal applications. In addition, OQGN replaced legacy applications for alignment sheet generation, Gas class location, and data maintenance, and were in production in less than 4 months from project initiation.
Register for the Upcoming Geonamic PODScast!
Join us on September 10th!
The PODS 7 model provides an ideal system of record to support pipeline risk modeling including qualitative, semi-quantitative, and quantitative/probabilistic algorithms. This PODScast will review methods for managing key source asset and inspection data in PODS, including use of PODS views to manage pre-processed risk factors, geoprocessing, and publishing of risk model results to PODS. Geonamic will be joined by business partners and industry experts PipelineRisk and GCR Integrity to review risk algorithms based on PODS. The session will also include a review of the application of Machine Learning to risk model inputs and results to help identify threat drivers and mitigation opportunities.
Risk Model Improvement Initiative, Continued Conversations
Geonamic and Pipeline-Risk, both leading technology providers in the oil and gas midstream market, have partnered to sponsor a working group of forward-thinking pipeline operators and risk experts. The goal of the working group is to combine the experience, expertise and data of each participant to explore the practicality of adopting advanced and versatile machine-learned risk models. The project will focus on the efficacy of the models, validation of risk results, risk factor sensitivity, as well as model transparency and interpretability. At the end of the project, pipeline integrity managers and risk engineers will have a clear understanding of machine learning methods and whether machine learning risk assessment is suitable for their Integrity Management and Risk Assessment program.
