Rock physics inversion workflow on reservoir parameters: A case study of seismic hydrocarbon detection in large-area tight dolomite reservoirs

Hao, Z., Ba, J., Zhang, L., Zeng, Q., Jiang, R., Liu, J., Qian, W, Tan, W. and Cheng, W., 2016. Rock physics inversion workflow on reservoir parameters: A case study of seismic hydrocarbon detection in large-area tight dolomite reservoirs. Journal of Seismic Exploration, 25: 561-588. Lateral heterogeneities of the geological characteristics in hydrocarbon reservoirs pose a major challenge for the wide application of rock physics modeling and relevant hydrocarbon detection techniques. In the application of 3D seismic inversion in a large work area, studies on improving hydrocarbon seismic prediction accuracy by effectively utilizing multiple-well log data and multi-scale wave responses is still a hotspot and difficulty in the research area of quantitative seismic interpretation. By combining the rock physics model with the pre-stack seismic inversion, quantitative estimate of reservoir properties can be performed. However, due to the different observation scales of seismic, well log and laboratory observation, the rock physics model established at each scale is different and the data between different scales cannot be effectively related in a combined application. This paper probes into the dolomite gas reservoirs with low porosity and low permeability in the MX work area. We consider the reservoir environment, lithology and pore fluid to predict the wave response dispersions on the basis of poroelasticity theory, and produce the multi-scale rock physics models to relate wave data between different scales. By analyzing the models and the well production reports, we adjust the log interpretation results and perform fluid sensitivity analysis on rock physics parameters at acoustic and ultrasonic scales, respectively. Comparison shows that the pattern and sequence of sensitivity parameters from the two scales are basically consistent. The parameters which are the most sensitive to porosity and gas saturation are selected. Based on the single-well rock physics templates which is built in the analysis of each key reference wells, optimization is made to output the standard template for the work area. The standard template takes into account the general geological and petrophysical characteristics of the target stratum. By analyzing the lateral variation and heterogeneity of reservoir geological characteristics in the large work area, the input parameters of rock physics modeling at each well coordinates are adjusted according to the gas production reports, and optimization is made in the 3D work area to establish the 3D data volume of rock physics template. In combination with the pre-stack seismic inversion, the porosity and saturation are estimated in the target stratum, and the estimate results are smoothed to output the final inversion data volume. By comparing with the log interpretation and production testing results, it is proved that the prediction results are correct and the methodology is effective.
- Avseth, P., Mukerji, T. and Mavko, G., 2005. Quantitative Seismic Interpretation: Applying Rock
- Physics Tools to Reduce Interpretation Risk. Cambridge University Press, Cambridge.
- Ba, J., Carcione, J.M. and Nie, J.X., 2011. Biot-Rayleigh theory of wave propagation in
- double-porosity media. J. Geophys. Res., 116(B6): B06202.
- Ba, J., Carcione, J.M., Cao, H., Da, Q.Z., Yuan, Z.Y. and Lu, M.H., 2012. Velocity dispersion
- and attenuation of P waves in partially-saturated rocks: Wave propagation equations in
- double-porosity medium. Chin. J. Geophys., 55: 219-231.
- Ba, J., Cao, H., Carcione, J.M., Tang, G., Yan, X., Sun, W. and Nie, J., 2013a. Multiscale
- tock-physics templates for gas detection in carbonate reservoirs. J. Appl. Geophys., 93:
- 77-82.
- Ba, J., Yan, X.Y., Chen, Z.Y., Xu, G.C., Bian, C.S., Cao, H., Yao, F.C. and Sun, W.T., 2013b.
- Rock physics model and gas saturation inversion for heterogeneous gas reservoirs. Chin. J.
- Geophys., 56: 1696-1706.
- Ba, J., Zhao, J., Carcione, J.M. and Huang, X., 2016. Compressional wave dispersion due to rock
- matrix stiffening by clay squirt flow. Geophys. Res. Lett., 43: 6186-6195.
- Berryman, J.G., 1980. Long-wavelength propagation in composite elastic media I]. Ellipsoidal
- inclusions. J. Acoust. Soc. Am., 68: 1820-1831.
- Biot, M.A., 1956. Theory of propagation of elastic waves in a fluid-saturated porous solid: I.
- Low-frequency range. J. Acoust. Soc. Am., 28: 168-178.
- Biot, M.A., 1962. Mechanics of deformation and acoustic propagation in porous media. J. Appl.
- Phys., 33: 1482-1498.
- Carcione. J.M. and Avseth, P., 2015. Rock-physics templates for clay-rich source rocks.
- Geophysics, 80: D481-D500.
- ROCK PHYSICS INVERSION WORKFLOW 587
- Caspari, E., Miiller, T.M. and Gurevich, B., 2011. Time-lapse sonic logs reveal patchy CO,
- saturation in-situ. Geophys. Res. Lett., 38: L13301.
- Chi, X.G. and Han, D.H., 2009. Lithology and fluid differentiation using a rock physics template.
- The Leading Edge, 28: 60-65.
- Deng, J.X., Wang, H., Zhou, H., Liu, Z.H., Song, L.T. and Wang, X.B., 2015. Microtexture,
- seismic rock physical properties and modeling of Longmaxi formation shale. Chin. J.
- Geophys., 58: 2123-2136.
- Dvorkin, J. and Nur, A., 1993. Dynamic poroelasticity: A unified model with the squirt and the Biot
- mechanisms. Geophysics, 58: 524-533.
- Gassmann, F., 1951. Uber die Elastizitat poréser Medien: Vier. der Natur. Gesellschaft in Ziirich,
- 96: 1-23.
- Gurevich, B., Makarynska, D., Paula, O.B.D. and Pervukhina, M., 2010. A simple model for
- squirt-flow dispersion and attenuation in fluid-saturated granular rocks. Geophysics, 75:
- N109-N120.
- He, H.B., You, J. and Chen, K.Y., 2011. Gas sand distribution prediction by prestack elastic
- inversion based on rock physics modeling and analysis. Appl. Geophys., 8: 197-205.
- Jin, M.D., Zeng, W., Tan, X.C., Li, L., Li, Z.Y., Luo, B., Zhang J.L. and Liu, J.W., 2014.
- Characteristics and controlling factors of beach-controlled karst reservoirs in Cambrian
- Longwangmiao Formation, Moxi-Gaoshiti area, Sichuan Basin, NW China. Petrol. Explor.
- Develop., 41: 712-723.
- Liu, Y.Q., 2014. Construction and Application of Fluid Identification Factors based on Porous
- Media. Jilin University, Changchun.
- Ly, Q.B. and Sun, Z.X., 2012. Application of rock physics chart to quantitative reservoir
- interpretation. Progr. Geophys. (in Chinese), 27: 610-618.
- Mavko, G. and Nur, A., 1975. Melt squirt in the asthenosphere. J. Geophys. Res., 80: 1444-1448.
- Nicolas-Lopez, R. and Valdiviezo-Mijangos, O.C., 2016. Rock physics templates for integrated
- analysis of shales considering their mineralogy, organic matter and pore fluids. J. Petrol.
- Sci. Engineer., 137: 33-41.
- Odegaard, E. and Avseth, P., 2004. Well log and seismic data analysis using rock physics templates.
- First Break, 22: 37-43.
- Papageorgiou, G. and Chapman, M., 2015. Multifluid squirt flow and hysteresis effects on the bulk
- modulus-water saturation relationship. Geophys. J. Internat., 203: 814-817.
- Pride, S.R. and Berryman, J.G., 2003. Linear dynamics of double-porosity dual-permeability
- materials. I: Governing equations and acoustic attenuation. Phys. Rev. E, 68: 036603.
- Russell, B.H., Hedlin, K., Hilterman, F.J. and Lines, L.R., 2003. Fluid property discrimination
- with AVO: A Biot-Gassmann perspective. Geophysics, 68: 29-39.
- Russell, B.H., Gray, D. and Hampson, D.P., 2011. Linearized AVO and poroelasticity. Geophysics
- 76(3): C19-C29.
- Sun, W.T., Ba, J., Miiller, T.M., Carcione, J.M. and Cao, H., 2014. Comparison of P-wave
- attenuation models of wave-induced flow. Geophys. Prosp., 63: 378-390.
- Tang, J.W., 2008. Discussion on several issues about seismic rock physics. Geophys. Prosp. Petrol.,
- 47: 398-404.
- Tang, S.W., 2011. Research of image processing methods and technology in seismic interpretation.
- Ph.D. thesis. Northeast Petroleum University, Daqing.
- Vinci, C., Renner, J. and Steeb, H., 2014. On attenuation of seismic waves associated with flow
- : in fractures. Geophys. Res. Lett., 41: 7515-7523.
- White, J.E., 1975. Computed seismic speeds and attenuation in rocks with partial gas saturation.
- Geophysics, 40: 224-232.
- Yang, X.F., Wang, X.Z., Yang, Y.M., Li, X.Y., Jiang, N., Xie, J.R. and Luo, W.J., 2015.
- Diagenesis of the dolomite reservoir in lower Cambrian Longwangmiao formation in central
- Sichuan basin. Geol. Sci. Technol. Info., 34: 35-41.
- Yin, X.Y., Zhang, S.X., Zhang, F.C. and Hao, Q.Y., 2010. Utilizing Russell Approximation based
- elastic wave impedance inversion to conduct reservoir description and fluid identification.
- Oil Geophys. Prosp., 45: 373-380.
- 588 HAO, BA, ZHANG, ZENG, JIANG, LIU, QIAN, TAN & CHENG
- Yin, X.Y., Zhang, S.X. and Zhang, F., 2013. Delicate construction of fluid factor and its
- application based on two-phase media theory. Progr. Geophys. (in Chinese), 28: 2911-2918.
- Yin, X.Y., Cao, D.P., Wang, P.L. and Zong, Z.Y., 2014. Research progress of fluid discrimination
- with prestack seismic inversion. OGP, 49: 22-34.
- Yin, X.Y., Zong, Z.Y. and Wu, G.C., 2015. Research on seismic fluid identification driven by rock
- physics. Sci. China: Earth Sci., 58: 159-171.
- Yu, H., Ba, J., Carcione, J.M., Li, J.S., Tang, G., Zhang, X.Y., He, X.Z. and Ouyang, H., 2014.
- Rock physics modeling of heterogeneous carbonate reservoirs: porosity estimation and
- hydrocarbon detection. Appl. Geophys., 11: 9-22.
- Zhang, Z., Yin, X.Y. and Hao, Q.Y., 2014. Frequency-dependent fluid identification method based
- on AVO inversion. Chin. J. Geophys., 57: 4171-4184.
- Zhang, G.Z., Chen, J.J., Chen, H.Z., Zhang, J.Q. and Yin, X.Y., 2015. Quantitative interpretation
- of Carbonate gas reservoir based on rock physics template. J. Jilin Univ.: Earth Sci. Ed.,
- 45: 630-638.
- Zong, Z.Y., Yin, X.Y. and Zhang, F.C., 2011. Elastic impedance Bayesian inversion for lame
- parameters extracting. OGP, 46: 598-604.
- Zong, Z.Y., Yin, X.Y. and Wu, G.C., 2012. Fluid identification method based on compressional
- and shear modulus direct inversion. Chin. J. Geophys., 55: 284-292.
- Zong, Z.Y., Yin, X.Y. and Wu, G.C., 2015. Geofluid discrimination incorporating poroelasticity
- and seismic reflection inversion. Surv. Geophys., 36: 659-681.