Skip to main content
SpringerLink
Log in

Nonlinear simultaneous inversion of pore structure and physical parameters based on elastic impedance

  • Research Paper
  • Published:
Science China Earth Sciences Aims and scope Submit manuscript

Abstract

Carbonate reservoirs have complex pore structures, which not only significantly affect the elastic properties and seismic responses of the reservoirs but also affect the accuracy of the prediction of the physical parameters. The existing rock-physics inversion methods are mainly designed for clastic rocks, and the inversion objects are generally porosity and water saturation The data used are primarily based on the elastic parameters, and the inversion methods are mainly linear approximations To date, there has been a lack of a simultaneous pore structure and physical parameter inversion method for carbonate reservoirs. To solve these problems, a new Bayesian nonlinear simultaneous inversion method based on elastic impedance is proposed. This method integrates the differential effective medium model of multiple-porosity rocks, Gassmann equation, Amplitude Versus Offset (AVO) theory, Bayesian theory, and a nonlinear inversion algorithm to achieve the simultaneous quantitative prediction of the pore structure and physical parameters of complex porous reservoirs. The forward modeling indicates that the contribution of the pore structure, i.e., the pore aspect ratio, to the AVO response and elastic impedance is second only to that of porosity and is far greater than that of water saturation. The application to real data shows that the new inversion method for determining the pore structure and physical parameters directly from pre-stack data can accurately predict a reservoir’s porosity and water saturation and can evaluate the pore structure of the effective reservoir.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Aki K, Richards P G. 1980. Quantitative Seismology. San Francisco: W. H. Freeman & Co

    Google Scholar 

  • Anselmetti F S, Eberli G P. 1993. Controls on sonic velocity in carbonates. Pure Appl Geophys, 141: 287–323

    Article  Google Scholar 

  • Avseth P, Mukerji T, Mavko G. 2005. Quantitative Seismic Interpretation: Applying Rock Physics Tools to Reduce Interpretation Risk. Cambridge: Cambridge University Press

    Book  Google Scholar 

  • Ba J, Xu W H, Fu L Y, Carcione J M, Zhang L. 2017. Rock anelasticity due to patchy saturation and fabric heterogeneity: A double double-porosity model of wave propagation. J Geophys Res-Solid Earth, 122: 1949–1976

    Google Scholar 

  • Bachrach R. 2006. Joint estimation of porosity and saturation using stochastic rock-physics modeling. Geophysics, 71: O53–O63

    Article  Google Scholar 

  • Baechle G T, Colpaert A, Eberli G P, Weger R J. 2008. Effects of microporosity on sonic velocity in carbonate rocks. Leading Edge, 27: 1012–1018

    Article  Google Scholar 

  • Biot M A. 1956a. Theory of propagation of elastic waves in a fluid-saturated porous solid. I. Low-frequency range. J Acoust Soc Am, 28: 168–178

    Article  Google Scholar 

  • Biot M A. 1956b. Theory of propagation of elastic waves in a fluid-saturated porous solid. II. Higher frequency range. J Acoust Soc Am, 28: 179–191

    Article  Google Scholar 

  • Bosch M, Carvajal C, Rodrigues J, Torres A, Aldana M, Sierra J. 2009. Petrophysical seismic inversion conditioned to well-log data: Methods and application to a gas reservoir. Geophysics, 74: O1–O15

    Article  Google Scholar 

  • Brie A, Pampuri F, Marsala A, Meazza O. 1995. Shear sonic interpretation in gas-bearing sands. SPE Annual Technical Conference and Exhibitionn. Society of Petroleum Engineers. 701–710

  • Connolly P. 1999. Elastic impedance. Leading Edge, 18: 438–452

    Article  Google Scholar 

  • Dou Q, Sun Y, Sullivan C. 2011. Rock-physics-based carbonate pore type characterization and reservoir permeability heterogeneity evaluation, Upper San Andres reservoir, Permian Basin, west Texas. J Appl Geophys, 74: 8–18

    Article  Google Scholar 

  • Dvorkin J, Nur A. 1993. Dynamic poroelasticity: A unified model with the squirt and the Biot mechanisms. Geophysics, 58: 524–533

    Article  Google Scholar 

  • Fang Z L, Yang D H. 2015. Inversion of reservoir porosity, saturation, and permeability based on a robust hybrid genetic algorithm. Geophysics, 80: R265–R280

    Article  Google Scholar 

  • Gassmann F. 1951. Über die elastizität poröser medien. Vier der Natur Gesellschaft Zürich, 96: 1–23

    Google Scholar 

  • González E F, Mukerji T, Mavko G. 2008. Seismic inversion combining rock physics and multiple-point geostatistics. Geophysics, 73: R11–R21

    Article  Google Scholar 

  • Grana D. 2016. Bayesian linearized rock-physics inversion. Geophysics, 81: D625–D641

    Article  Google Scholar 

  • Grana D, Rossa E D. 2010. Probabilistic petrophysical-properties estimation integrating statistical rock physics with seismic inversion. Geophysics, 75: O21–O37

    Article  Google Scholar 

  • Ingber L. 1989. Very fast simulated re-annealing. Mathematical & Computer Modelling, 12: 967–973

    Article  Google Scholar 

  • Jin M, Zeng W, Tan X, Li L, Li Z, Luo B, Zhang J, Liu J. 2014. Characteristics and controlling factors of beach-controlled karst reservoirs in Cambrian Longwangmiao Formation, Moxi-Gaoshiti area, Sichuan Basin, NW China. Pet Exploration Dev, 41: 712–723

    Article  Google Scholar 

  • Kuster G T, Toksöz M N. 1974. Velocity and attenuation of seismic waves in two media, Part I. Theoretical considerations. Geophysics, 39: 587–606

    Article  Google Scholar 

  • Lang X, Grana D. 2018. Bayesian linearized petrophysical AVO inversion. Geophysics, 83: M1–M13

    Article  Google Scholar 

  • Li H B, Zhang J J. 2010. Modulus ratio of dry rock based on differential effective-medium theory. Geophysics, 75: N43–N50

    Article  Google Scholar 

  • Li H B, Zhang J J. 2011. Elastic moduli of dry rocks containing spheroidal pores based on differential effective medium theory. J Appl Geophys, 75: 671–678

    Article  Google Scholar 

  • Li H B, Zhang J J, Yao F C. 2013. Inversion of effective pore aspect ratios for porous rocks and its applications (in Chinese). Chin J Geophys, 56: 608–615

    Google Scholar 

  • Li H B, Zhang J J. 2014. A differential effective medium model of multiple-porosity rock and its analytical approximations for dry rock (in Chinese). Chin J Geophys, 57: 3422–3430

    Google Scholar 

  • Li H B, Zhang J J, Cai S J, Pan H J. 2019. Analysis of 3D rock physics template for reservoir with complex pore structure (in Chinese). Chin J Geophys, 62: 2711–2723

    Google Scholar 

  • Li H B, Zhang J J, Cai S J, Pan H J. 2020. A two-step method to apply Xu-Payne multi-porosity model to estimate pore type from seismic data for carbonate reservoirs. Pet Sci, 17: 615–627

    Article  Google Scholar 

  • Li K, Yin X, Zong Z. 2020. Facies-constrained prestack seismic probabilistic inversion driven by rock physics. Sci China Earth Sci, 63: 822–840

    Article  Google Scholar 

  • Liu H, Hou X. 2008. Research on the key parameters in the simulated Annealing algorithm. Computer Eng Sci, 30: 55–57

    Google Scholar 

  • Luo T, Feng X, Guo Z, Liu C, Liu X. 2019. Seismic Inversion of anisotropy parameters of fracture reservoirs by simulated annealing and particle swarm optimization. J Jilin Univ-Earth Sci Ed, 49: 1466–1476

    Google Scholar 

  • Mavko G, Mukerji T, Dvorkin J. 2009. The Rock Physics Handbook. Cambridge: Cambridge University Press

    Book  Google Scholar 

  • Mori T, Tanaka K. 1973. Average stress in matrix and average elastic energy of materials with misfitting inclusions. Acta Metall, 21: 571–574

    Article  Google Scholar 

  • Mukerji T, Jørstad A, Avseth P, Mavko G, Granli J R. 2001. Mapping lithofacies and pore-fluid probabilities in a North Sea reservoir: Seismic inversions and statistical rock physics. Geophysics, 66: 988–1001

    Article  Google Scholar 

  • Nie J X, Yang D H, Yang H Z. 2004. Inversion of reservoir parameters based on the BISQ model in partially saturated porous media (in Chinese). Chin J Geophys, 47: 1101–1105

    Article  Google Scholar 

  • Norris A N. 1985. A differential scheme for the effective moduli of composites. Mech Mater, 4: 1–16

    Article  Google Scholar 

  • Pride S R, Berryman J G. 2003. Linear dynamics of double-porosity dual-permeability materials. I. Governing equations and acoustic attenuation. Phys Rev E, 68: 036603

    Article  Google Scholar 

  • Russell B. 1988. Introduction to seismic inversion methods. SEG Course Notes Series

  • Sayers C M. 2008. The elastic properties of carbonates. Leading Edge, 27: 1020–1024

    Article  Google Scholar 

  • Spikes K, Mukerji T, Dvorkin J, Mavko G. 2007. Probabilistic seismic inversion based on rock-physics models. Geophysics, 72: R87–R97

    Article  Google Scholar 

  • Sun Y F. 2004. Pore structure effects on elastic wave propagation in rocks: AVO modelling. J Geophys Eng, 1: 268–276

    Article  Google Scholar 

  • Whitcombe D N. 2002. Elastic impedance normalization. Geophysics, 67: 60–62

    Article  Google Scholar 

  • Xu S, Payne M A. 2009. Modeling elastic properties in carbonate rocks. Leading Edge, 28: 66–74

    Article  Google Scholar 

  • Yang D, Zhang Z. 2002. Poroelastic wave equation including the Biot/Squirt mechanism and the solid/fluid coupling anisotropy. Wave Motion, 35: 223–245

    Article  Google Scholar 

  • Yin X Y, Cui W, Zong Z Y, Liu X J. 2014. Petrophysiccal property inversion of reservoirs based on elastic impedance (in Chinese). Chin J Geophys, 57: 4132–4140

    Google Scholar 

  • Yin X Y, Zong Z Y, Wu G C. 2015. Research on seismic fluid identification driven by rock physics. Sci China Earth Sci, 58: 159–171

    Article  Google Scholar 

  • Yuan S, Liu Y, Zhang Z, Luo C, Wang S. 2019. Prestack stochastic frequency-dependent velocity inversion with rock-physics constraints and statistical associated hydrocarbon attributes. IEEE Geosci Remote Sens Lett, 16: 140–144

    Article  Google Scholar 

  • Zhang B, Yang D, Cheng Y, Zhang Y. 2019. A unified poroviscoelastic model with mesoscopic and microscopic heterogeneities. Sci Bull, 64: 1246–1254

    Article  Google Scholar 

  • Zhang G, Zhao C, Tu Q, Liu J, Zhang J. 2018. Prestack stochastic inversion based on the quantum annealing Metropolis-Hastings algorithm (in Chinese). Oil Geophys Prospect, 53: 153–160

    Google Scholar 

  • Zhang J J, Yin X Y, Zhang G Z, Gu Y P, Fan X G. 2020. Prediction method of physical parameters based on linearized rock physics inversion. Petrol Explor Develop, 47: 57–64

    Article  Google Scholar 

  • Zhang T T, Zhang R F, Tian J Z, Lu L F, Qin F Q, Zhao X Z, Sun Y F. 2018. Two-parameter prestack seismic inversion of porosity and pore-structure parameter of fractured carbonate reservoirs: Part 2—Applications. Interpretation, 6: 1–36

    Article  Google Scholar 

  • Zhao L, Nasser M, Han D. 2013. Quantitative geophysical pore-type characterization and its geological implication in carbonate reservoirs. Geophys Prospect, 61: 827–841

    Article  Google Scholar 

Download references

Acknowledgements

We thank the editorial board members and anonymous reviewers for their valuable comments on this paper. This work was supported by the National Key Research and Development Program of China (Grant No. 2019YFC0605504) and the Scientific Research & Technology Development Project of China National Petroleum Corporation (Grant No. 2017D-3504).

Author information

Authors and Affiliations

  1. Research Institute of Petroleum Exploration and Development, PetroChina Company Limited, Beijing, 100083, China

    Hongbing Li & Qiang Gao

  2. School of Geosciences, China University of Petroleum (East China), Qingdao, 266580, China

    Jiajia Zhang

  3. College of Geophysics and Petroleum Resources, Yangtze University, Wuhan, 430100, China

    Haojie Pan

Authors
  1. Hongbing Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jiajia Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Haojie Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Qiang Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Hongbing Li or Jiajia Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, H., Zhang, J., Pan, H. et al. Nonlinear simultaneous inversion of pore structure and physical parameters based on elastic impedance. Sci. China Earth Sci. 64, 977–991 (2021). https://doi.org/10.1007/s11430-020-9773-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11430-020-9773-8

Keywords

Search

Navigation