Skip to main content

Geostatistical History Matching Conditioned to Seismic Data

Part of the Lecture Notes in Earth System Sciences book series (LNESS)

Abstract

History matching is a highly non-linear inverse problem where by perturbing subsurface models (e.g. porosity, permeability models) one tries to match the dynamic responses of this Earth model with the observed production data of a given hydrocarbon reservoir. Geostatistical seismic inversion is a geophysical inverse problem where by creating a set of porosity or facies models one minimizes a mismatch function between the observed and the synthetic seismic data created from simulated acoustic and elastic impedance models. In spite of their different physical principles, both of these inverse problems have the same parameter and solution space. We propose herein a global geostatistical iterative inversion methodology, where the retrieved subsurface models match simultaneously the observed seismic reflection and the reservoir production data.

Keywords

  • History matching
  • Inverse problem
  • Seismic inversion
  • Uncertainty assessment.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-642-32408-6_16
  • Chapter length: 4 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   269.00
Price excludes VAT (USA)
  • ISBN: 978-3-642-32408-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Hardcover Book
USD   349.99
Price excludes VAT (USA)
Fig. 1

References

  1. Soares, A. (2001). Direct sequential simulation and cosimulation. Mathematical Geology, 33(8), 911–926.

    CrossRef  Google Scholar 

  2. Azevedo, L., Correia, P., Nunes, R., & Soares, A. (2013). Geostatistical AVO Direct Facies Inversion. In 15th Annual Conference of the International Association of Mathematical Geosciences. Madrid: Spain.

    Google Scholar 

  3. Shuey, R. T. (1985). A simplification of the Zoeppritz equations. Geophysics, 50(4), 609–614.

    CrossRef  Google Scholar 

  4. Avseth, P., Mukerji, T., & Mavko, G. (2005). Quantitative seismic interpretation. Cambridge: Cambrige University Press.

    Google Scholar 

  5. Mata-Lima, H. (2008). Reservoir characterization with iterative direct sequential co-simulation: Integrating fluid dynamic data into stochastic model. Journal of Petroleum Science and Engineering, 62(3–4), 59–72.

    CrossRef  Google Scholar 

Download references

Acknowledgments

The authors would like to thank CERENA/CMRP for supporting this work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Leonardo Azevedo .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Soares, A., Azevedo, L., Focaccia, S., Carneiro, J. (2014). Geostatistical History Matching Conditioned to Seismic Data. In: Pardo-Igúzquiza, E., Guardiola-Albert, C., Heredia, J., Moreno-Merino, L., Durán, J., Vargas-Guzmán, J. (eds) Mathematics of Planet Earth. Lecture Notes in Earth System Sciences. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32408-6_16

Download citation