Model-based prediction of lithology, pore fluid, and porosity

Kyle T. Spikes; Jack P. Dvorkin

doi:10.1071/ASEG2004ab138

ISSN: 2202-0586
E-ISSN:

oa Model-based prediction of lithology, pore fluid, and porosity
Authors Kyle T. Spikes^a and Jack P. Dvorkin^b
View Affiliations Hide Affiliations

^a Stanford Rock Physics Laboratory, , USA, [email protected] ^b Stanford Rock Physics Laboratory, , USA, [email protected]
Publisher: Australian Society of Exploration Geophysicists
Source: ASEG Extended Abstracts, Volume 2004, Issue ASEG2004 - 17th Geophysical Conference, Dec 2004, p. 1 - 4
DOI: https://doi.org/10.1071/ASEG2004ab138
- Published online: 01 Dec 2004

Abstract

We present a deterministic methodology for mapping the lithology, pore fluid, and porosity from seismic data. The input is the P- and S-wave data volumes that may come, e.g., from acoustic and elastic impedance inversion or cross-well measurements. The output is the pore fluid type (hydrocarbon versus water), total porosity, and clay content. The key element of this methodology is a site-specific rock physics model that provides the needed transforms from the elastic rock properties to the reservoir properties. The model is established by comparing model-based predictions, such as impedance versus porosity, to the relations present in well log data. Once selected, the model is used to identify the presence of hydrocarbons from a combination of the P-wave impedance and Poisson’s ratio. Then the P-wave impedance is used to map porosity and clay content assuming that a deterministic relation exists between the latter two properties. All deterministic equations are calibrated at a well. These equations subsequently are applied to up-scaled well log data to confirm their validity at the seismic scale.

Article metrics loading...

/content/journals/10.1071/ASEG2004ab138

2004-12-01

2026-01-13

From This Site

/content/journals/10.1071/ASEG2004ab138

dcterms_title,dcterms_subject,pub_keyword

-contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution

10

5

Full text loading...

References

Avseth, P., Dvorkin, I, Mavko, G., and Rykkje, I, 2000, Rock physics diagnostic of North Sea sands: Link between micro structure and seismic properties: Geophysical Research Letters, 27, 2761-2764.
Backus, G. E., 1962, Long-wave elastic anisotropy produced by horizontal layering: Journal of Geophysical Research, 67, 4427-1440.
Castagna, J. P., Batzle, M. L., and Eastwood. R. L., 1985, Relationships between compressional-wave and shear-wave velocities in clastic silicate rocks: Geophysics, 50, 571-581.
Dvorkin, J., and Gutierrez, M. A., 2002, Grain sorting, porosity and elasticity: Petrophysics, 43, 185-196.
Dvorkin, J., and Nur., A, 1996, Elasticity of high-porosity sandstones: Theory for two North Sea datasets: Geophysics, 61,1363-1370.
Gassmann, F., 1951, Uber die Elastizitat poroser Medien: Vier. DerNatur. Gesellschaft in Zurich, 96, 1-23.
Greenberg, M. L., and Castagna, J. P., 1992, Shear-wave velocity estimation in porous rocks: Theoretical formulation, preliminary verification and applications: Geophysical Prospecting, 40, 195-209.
Han, D. -H., 1986, Effects of Porosity and Clay Content on Acoustic properties of Sandstones and Unconsolidated Sediments: Ph.D. dissertation, Stanford University.
Hill, R., 1952, The elastic behavior of crystalline aggregate: Proceedings of the Physical Society of London, A65, 349-372.
Marion, D., 1990, Acoustical, mechanical, and transport properties of sediments and granular materials: Ph.D. thesis, Stanford University.
Mavko, G., Chan, C, and Mukerji, T., 1995, Fluid substitution: Estimating changes in Vp without knowing Vs: Geophysics, 60, 1751-1755.
Mavko G., Mukerji, T., and Dvorkin, J., 1998, The rock physics handbook, Tools for seismic analysis in porous media: Cambridge University Press.
Nur, A., 1969, Effects of stress and fluid inclusions on wave propagation in rock: Ph.D. thesis, MIT.
Raymer, D. S., Hunt, E. R., and Gardner, J. S., 1980, An improved sonic transit time-to-porosity transform, 21st Meeting, SPWLA, Paper P.
Wyllie, M. R. J., Gregory. A. R., and Gardner, L. W., 1956, Elastic wave velocities in heterogeneous and porous media: Geophysics, 27, 569-589.
Yin, H., 1992, Acoustic velocity and attenuation of rocks: Isotropy, intrinsic anisotropy, and stress induced anisotropy: Ph.D. thesis, Stanford University.

/content/journals/10.1071/ASEG2004ab138

Article Type: Research Article

Keyword(s): Characterization; Prediction; Rock Physics

Most Cited This Month Most Cited RSS feed

- Inversion of data from electrical imaging surveys in water-covered areas
  
  Authors M. H. Loke and J. W. Lane
- Inversion of Magnetic Data from Remanent and Induced Sources
  
  Authors Robert G. Elllis, Barrry de Wet and Ian N. Macleod
- A comparison of smooth and blocky inversion methods in 2-D electrical imaging surveys
  
  Authors M. H. Loke, Ian Acworth and Torleif Dahlin
- Designing matched bandpass and azimuthal filters for the separation of potential-field anomalies by source region and source type
  
  Authors Jeffrey D. Phillips
- Bad Colour Maps Hide Big Features and Create False Anomalies
  
  Authors Peter Kovesi
- Practical 3D EM inversion – the P223F software suite
  
  Authors Art Raiche, Fred Sugeng and Glenn Wilson
- Estimating Noise Levels in AEM Data
  
  Authors Andy Green and Richard Lane
- Target delineation using Full Tensor Gravity Gradiometry data
  
  Authors Colm A. Murphy and James Brewster
- Transdimensional Monte Carlo Inversion of AEM Data
  
  Authors Ross C Brodie and Malcolm Sambridge
- The geotech VTEM time domain helicopter em system
  
  Authors Ken Witherly, Richard Irvine and Edward Morrison
More Less

oa Model-based prediction of lithology, pore fluid, and porosity

Abstract

Most Read This Month

Most Cited This Month Most Cited RSS feed