Shear wave velocity prediction during CO2-EOR and sequestration in the Gao89 well block of the Shengli Oilfield
- 15 Downloads
Shear-wave velocity is a key parameter for calibrating monitoring time-lapse 4D seismic data during CO2-EOR (Enhanced Oil Recovery) and CO2 sequestration. However, actual S-wave velocity data are lacking, especially in 4D data for CO2 sequestration because wells are closed after the CO2 injection and seismic monitoring is continued but no well log data are acquired. When CO2 is injected into a reservoir, the pressure and saturation of the reservoirs change as well as the elastic parameters of the reservoir rocks. We propose a method to predict the S-wave velocity in reservoirs at different pressures and porosities based on the Hertz–Mindlin and Gassmann equations. Because the coordination number is unknown in the Hertz–Mindlin equation, we propose a new method to predict it. Thus, we use data at different CO2 injection stages in the Gao89 well block, Shengli Oilfield. First, the sand and mud beds are separated based on the structural characteristics of the thin sand beds and then the S-wave velocity as a function of reservoir pressure and porosity is calculated. Finally, synthetic seismic seismograms are generated based on the predicted P- and S-wave velocities at different stages of CO2 injection.
Keywordscoordination number bulk modulus shear modulus Hertz–Mindlin shear wave CO2-EOR
Unable to display preview. Download preview PDF.
We wish to thank the staff of the Geophysical Research Institute of SINOPEC Shengli Oilfield for their cooperation and support. The authors are particularly grateful to Professor Huang Xuri and Chen Xiaohong for their guidance and comments.
- Brown, L. T., 2002, Integration of rock physics and reservoir simulation for the interpretation of time-lapse seismic data at Weyburn Field, Saskatchewan: MSc. Thesis, Colorado School of Mines.Google Scholar
- Lee, M. W., 2003, Velocity ration and its application to predicting velocities: U.S. Geological Survey Bulletin 2197, Denver, Colorado.Google Scholar
- Liu, Y. J., Li, Sh. J., Wang, Y. G., and Xia, Y. H., 2016, Reservoir prediction based on shear wave in Sulige Gas Field: China. Oil Geophysical Proepecting, 51(1), 165–173.Google Scholar
- Luo, H. M., Luo, X. R., Liu, S. H., et al., 2014, Physical features and influencing factors of elastic velocity of compacted sandy-conglomerates in northern steep slope, Dongying sag: Petroleum Geology and Recovery Efficiency, 21(2), 91–94.Google Scholar
- Luo, S. L., Yang, P. J., Hu, G. M., et al., 2016, S-wave velocity prediction based on the modified P-L model and matrix equation iteration: Chinese J. Geophys, 59(5), 1839–1848.Google Scholar
- Mavko, G., Mukerji, T., and Dvorkin, J. P., 1998, The Rock Physics Handbook: Cambridge University Press, 51–52.Google Scholar
- Mindlin, R. D., 1949, Compliance of elastic bodies in contact: Journal of Applied Mechanics, 16, 259–268.Google Scholar
- Murphy, W., 1982, Effects of microstructure and pore fluids on the acoustic properties of granular sedimentary materials: PhD Thesis, Stanford University.Google Scholar
- Qiu, G. Q., Ling Y., and Fan, H. H., 2003, The characteristics and distribution of abnormal pressure in the Paleogene source rocks of Dongying Sag: Petroleum Exploration and Development, 30(3), 71–75.Google Scholar
- Shi, H., 2008, Numerical simulation research on parameter optimization of CO2 miscible flooding of Gao89-1 Block in Zheng Lizhuang Oil field: Offshore Oil, 28(1), 68–73.Google Scholar
- Tan, M. Y., Zhang, J. N., and Xu, L., 2004, Prediction method of formation pressure in Jiyuan Depression: Oil Geophysical Prospecting, 39(3), 314–318.Google Scholar
- Wood, A. W., 1955, A textbook of sound: The MacMillan Co., New York.Google Scholar