Co-director of Reservoir Characterization Project
Department of Geophysics
Dr. Ge Jin is Assistant Professor of Geophysics and co-PI of Reservoir Characterization Project at Colorado School of Mines. His research focuses on Distributed Fiber-Optic Sensing (DFOS) applications in the fields of oil & gas, geothermal, CO2 sequestration, smart city, and earthquake hazard. He is also interested in machine-learning applications and seismic imaging. He obtained his Ph.D. in Geophysics from Columbia University in the City of New York, and dual B.S. in Geophysics and Computer Science from Peking University in Beijing. He worked as a research geophysicist in the oil industry for five years before joining Colorado School of Mines as a faculty member in 2019.
- B.S. in Geophysics, Peking University, 2006
- B.S. in Computer Science, Peking University, 2006
- M.S. in Geophysics, Peking University, 2009
- Ph.D. in Geophysics, Columbia University, 2014
- Distributed Fiber Optic Sensing Applications
- Machine learning
- Seismic imaging and interpretation
- GPGN436/536: Geophysical Computing/Advanced Geophysical Computing
- GPGN598C: Introduction to Distributed Fiber-Optic Sensing and Its Applications
- Offered in spring semesters
- GPGN598C: Reading Seminar
- Offered in fall semesters
Luo B., Jin, G., and Stanek, F., 2021. Near-field strain in DAS-based microseismic observation. Geophysics, 86(5), pp.1-49.
Jin, G., Ugueto, G., Wojtaszek, M., Guzik, A., Jurick, D. and Kishida, K., 2021. Novel Near-Wellbore Fracture Diagnosis for Unconventional Wells Using High-Resolution Distributed Strain Sensing during Production. SPE Journal, pp.1-10.
Luo, B., Lellouch, A., Jin, G., Biondi, B. and Simmons, J., 2021. Seismic inversion of shale reservoir properties using microseismic-induced guided waves recorded by distributed acoustic sensing (DAS). Geophysics, 86(4), pp.1-58.
Liu, Y., Jin, G., Wu, K., & Moridis, G., 2020, November. Hydraulic-Fracture-Width Inversion Using Low-Frequency Distributed-Acoustic-Sensing Strain Data – Part I: Algorithm and Sensitivity Analysis. Society of Petroleum Engineers. doi:10.2118/204225-PA
Titov, A., Binder, G., Liu, Y., Jin, G., Simmons, J., Tura, A., Monk, D., Byerley, G. and Yates, M., 2020. Modeling and interpretation of scattered waves in inter-stage DAS VSP survey. Geophysics, 86(2), pp.1-49.
Jin*, G., Friehauf*, K., Roy*, B., Constantine, J.J., Swan, H.W., Krueger, K.R. and Raterman, K.T., 2019, October. Fiber Optic Sensing-Based Production Logging Methods for Low-Rate Oil Producers. In Unconventional Resources Technology Conference, Denver, Colorado, 22-24 July 2019 (pp. 1183-1199). Unconventional Resources Technology Conference (URTeC); Society of Exploration Geophysicists.
Jin, G., Mendoza, K., Roy, B. and Buswell, D.G., 2019. Machine learning-based fracture-hit detection algorithm using LFDAS signal. The Leading Edge, 38(7), pp.520-524.
Jin, G. and Roy, B., 2017. Hydraulic-fracture geometry characterization using low-frequency DAS signal. The Leading Edge, 36(12), pp.975-980.
Jin, G. and Gaherty, J.B., 2015. Surface wave phase-velocity tomography based on multichannel cross-correlation. Geophysical Journal International, 201(3), pp.1383-1398.
Green Center 245A
1500 Illinois St
Colorado School of Mines
Golden, CO 80401