The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


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Abstract: Applying Machine Learning on Reflection Seismic and Well Logging Data to Identify Gas- and Brine-Saturated Reservoir Zones (AGU25)

Applying Machine Learning on Reflection Seismic and Well Logging Data to Identify Gas- and Brine-Saturated Reservoir Zones

Mohamed Hamdallah1,2 and William Harbert1, (1)University of Pittsburgh, Pittsburgh, United States, (2)Aswan University, Aswan, Egypt
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