Bureau of Economic Geology

Rebecca Gao

Rebecca Gao
Research Scientist Associate III
Bureau of Economic Geology
The University of Texas at Austin
University Station, Box X
Austin, Texas 78713-8924
Telephone
512-471-4874
Fax
512-471-0140

Research Interests

  • Integrated oil and gas reservoir analysis
  • Computer numerical modeling of multiphase fluid flow
  • Artificial intelligence and big data analysis

Researcher ID

Shuang Gao | Professional Profile

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Google Scholar

Education

M.S. Petroleum Engineering, The University of Texas at Austin, 2015

M.S. Electronic Engineering, Tsinghua University, China, 2004

B.S. Electronic Engineering, Tianjin University, China, 2001

Professional History

Research Scientist Associate, Bureau of Economic Geology, UT Austin, from 2017

Graduate Research Assistant, Bureau of Economic Geology, UT Austin, 2014 – 2015

Design Leader/Development Manager, Wisenergy Technology Co., Ltd, China, 2010 - 2011

Interpretation Engineer, Schlumberger Ltd, Beijing Geoscience Center, China, 2004 – 2010

Publications

Peer-reviewed articles

Chen, X, Gao, S., Kianinejad, A and DiCarlo, DA, 2017, Steady-state supercritical CO2 and brine relative permeability in Berea sandstone at different temperature and pressure conditions, Water Resources Research, v. 53, p. 6312-6321.

Gao, S., Sun, Y., Nicot, JP, 2016. Identification of a representative dataset for long-term monitoring at the Weyburn CO2-injection enhanced oil recovery site, Saskatchewan, Canada. International Journal of Greenhouse Gas Control, v. 54, p. 454-465.

Nicot, JP, Sun, Y.,Gao, S., 2016. Identification of a minimum dataset for CO2-EOR monitoring at Weyburn, Canada. 13th International Conference on Greenhouse Gas Control Technologies, GHGT-13, 14-18 November 2016, Lausanne, Switzerland.

Xu, C., Torres-Verdín, C., andGao, S., 2013. Interpretation of hydraulic rock types with resistivity logs in Tertiary deepwater turbidite reservoirs: pore-scale modeling verified with field observations in the Gulf of Mexico, U.S. SEG Interpretation, v. 1, I. 2, T177-T185.

Abstracts and Presentations

Nicot, JP, Gao, S., Dommisse, R., and Hennings, P., 2017, Basin-scale hydrogeological modeling of the Fort Worth Basin Ellenburger Group for pore pressure characterization, 2017 Fall Meeting, AGU, New Orleans, LA, 11-15 Dec.

Xu, C., Torres-Verdín, C., and Gao, S., 2013. Electrical vs. hydraulic rock types in Tertiary deepwater turbidite reservoirs: pore-scale modeling verified with field observations in the Gulf of Mexico, U.S. SEG 2013 Annual Conference, Houston.

Gao, S., Neville, T., Hochart, P., 2007. Reducing Petrophysical Uncertainty with Measurements, Schlumberger Asian-Pacific Reservoir Symposium, Oct 2007, Beijing, China.

Gao, S., Zhang, X.J., Sun, W.D., 2004. Lossless inter-array predictive coding for subpixelshifted satellite images based on texture analysis, Geoinformatics, June 2004, Gävle, Sweden.

Certificates

Coursera Certificate for Machine Learning of Stanford, Dec 2016

edX Certificate for CS1156x: Learning From Data (Machine Learning) of Caltech, Dec 2016

Computer Skills

CMG, COMSOL, Techlog, Interactive Petrophysics (IP), KAPPA Ecrin, GeoFrame, ECLIPSE Compositional Simulation&FrontSim, Insitu Pro, PETREL Reservoir Engineering, PVTSim, ELAN/LabVIEW, ImageJ/Tableau/SGEMS

C#/Java/C++/Fortran/Perl/Matlab/R/Python/Mathematica/MS SQL/ on Windows & Ubuntu Linux programming/Mindjet/UML/RUP