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Ge Jin

Ge Jin

Assistant Professor
Co-director of Reservoir Characterization Project
Department of Geophysics

Short Bio

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.

Education

  • 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

Research

  • Distributed Fiber Optic Sensing Applications
  • Machine learning
  • Seismic imaging and interpretation

Teaching

  • GPGN436/536: Geophysical Computing/Advanced Geophysical Computing
    • Offered in fall semesters
    • Co-teach with Jeff Shragge
    • Syllabus: GPGN436, GPGN536
  • GPGN598C: Introduction to Distributed Fiber-Optic Sensing and Its Applications
  • GPGN598C: Reading Seminar
    • Offered in fall semesters

 

Selected Publications

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. Geophysics86(2), pp.1-49.

Titov, A., Jin, G., Fan, Y., Tura, A., Kutun, K. and Miskimins, J., 2020, March. Distributed Fiber-optic Sensing Based Production Logging Investigation: Flowloop Experiments. In First EAGE Workshop on Fibre Optic Sensing (Vol. 2020, No. 1, pp. 1-5). European Association of Geoscientists & Engineers.

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 Edge38(7), pp.520-524.

Jin, G. and Roy, B., 2017. Hydraulic-fracture geometry characterization using low-frequency DAS signal. The Leading Edge36(12), pp.975-980.

Jin, G., Gaherty, J.B., Abers, G.A., Kim, Y., Eilon, Z. and Buck, W.R., 2015. Crust and upper mantle structure associated with extension in the Woodlark Rift, Papua New Guinea from Rayleigh‐wave tomography. Geochemistry, Geophysics, Geosystems16(11), pp.3808-3824.

Jin, G. and Gaherty, J.B., 2015. Surface wave phase-velocity tomography based on multichannel cross-correlation. Geophysical Journal International201(3), pp.1383-1398.

Contact

Green Center 245A
1500 Illinois St
Colorado School of Mines
Golden, CO 80401
303-273-3455
gjin@mines.edu