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Kan Wu

Kan WuDr Kan Wu is an associate Professor and Class of '75 DVG Career Development Professor in Harold Vance department of petroleum engineering at Texas A&M University. Her research interests include data interpretation and forward modeling of Distributed iber Optic Strain Sensing, hydraulic fracture modeling, monitoring, and optimization, subsurface monitoring of Carbon storage and Enhanced Geothermal Systems, Hybrid physics and data-driven modeling, multi-scale and multi-physics modeling. Wu has authored or co-authored more than 100 technical papers, which have been cited more than 5000 times (Source: Google Scholar). Wu is a founder and director of Advanced Geomechanics Fracture & Reservoir Application Consortium (AGFRAC). This consortium is at the forefront of advancing subsurface monitoring techniques using distributed fiber optic strain sensing, aiming to optimize injection and production processes in oil and gas reservoirs, CO2 storage, and geothermal development and address critical energy and environmental challenges. Wu was honored with the Karen E. Olson ’87 and Louis H. Turner Faculty Award for Excellence in Research in 2023. Additionally, in 2022, she received the Award for Best Application Paper sponsored by the International Geomechanics Symposium. She is serving as a Distinguished Lecturer for the Society of Petroleum Engineers (SPE) for the 2023-2024 term. Wu holds a Ph.D. degree in petroleum engineering from The University of Texas at Austin. Read More Read Less

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Fertility and Childcare in East Asia29 %
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29 Aug 2025
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Researching Translator's Functional Style37 %
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Hydraulic fracture geometry characterization based on distributed fiber optic strain measurements45 %
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Fertility and Childcare in East Asia31 %
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Fertility and Childcare in East Asia
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03 Jun 2024
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Fertility and Childcare in East Asia
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03 Jun 2024
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New Results in Factory Physics - Insights from the Underlying Structures of Manufacturing Systems
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Hts Materials, Bulk Processing And Bulk Applications - Proceedings Of The 1992 Tcsuh Workshop25 % NR
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