Hydraulic fracture geometry characterization based on distributed fiber optic strain measurements
Autor: | Kan Wu, Yongzan Liu, Ge Jin, Aishwarya Srinivasan |
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EAN: | 9780323953610 |
eBook Format: | |
Sprache: | Englisch |
Produktart: | eBook |
Veröffentlichungsdatum: | 05.06.2024 |
Untertitel: | Modeling and Field Data for Unconventional and Geothermal Wells |
Kategorie: | |
Schlagworte: | Fiber optic fracture hits geothermal hydraulic fracturing reservoir characterization sensor strain sensing subsurface |
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Fiber optic-based measurements are innovative tools for the oil and gas industry to utilize in monitoring wells in a variety of applications including geothermal activity. Monitoring unconventional reservoirs is still challenging due to complex subsurface conditions and current research focuses on qualitative interpretation of field data. Hydraulic Fracture Geometry Characterization from Fiber Optic-Based Strain Measurements delivers a critical reference for reservoir and completion engineers to better quantify the propagation process and evolution of fracture geometry with a forward model and novel inversion model. The reference reviews different fiber optic-based temperature, acoustic, and strain measurements for monitoring fracture behaviors and includes advantages and limitations of each measurement, giving engineers a better understanding of measurements applied in all types of subsurface formations. Stress/strain rate responses on rock deformation are given a holistic approach, including guidelines and an automatic algorithm for identification of fracture hits. Last, a novel inversion model is introduced to show how fracture geometry can be used for optimization on well placement decisions. Supported by case studies, Hydraulic Fracture Geometry Characterization from Fiber Optic-Based Strain Measurements gives today's engineers better understanding of all complex subsurface measurements through fiber optic technology. - Examine the basics of distributed fiber optic strain measurements - Conduct a detailed analysis of strain responses observed in both horizontal and vertical monitoring wells - Present a systematic approach for interpreting strain data measured in the field - Highlight the significant insights and values that can be derived from the field measured strain dataset - Support monitoring and modeling for subsurface energy extraction and safe storage
Dr 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 Fiber 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.
Dr 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 Fiber 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.