--> Modeling Sonic Velocity in Carbonates Using Thin Sections, by Gregor Baechle, Arnout Colpaert, Gregor P. Eberli, and Ralf J. Weger, #40313 (2008)
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Modeling Sonic Previous HitVelocityNext Hit in Carbonates Using Thin Sections*

By

Gregor Baechle1, Arnout Colpaert2, Gregor P. Eberli1, and Ralf J. Weger1

 

Search and Discovery Article #40313 (2008)

Posted July 25, 2008

 

*Adapted from oral presentation at AAPG Annual Convention, San Antonio, Texas, April 20-23, 2008

1Comparative Sedimentology Laboratory, University of Miami, Miami, FL ([email protected]) 

2Statoil Research Center, Trondheim, Norway

Abstract

The differential effective medium theory (DEM) is used to model high frequency (1MHz) laboratory Previous HitvelocityNext Hit measurements of carbonates under dry and water-saturated conditions. Previous HitVelocityNext Hit-porosity data from laboratory experiments show that micropores have a strong softening effect on the sonic Previous HitvelocityNext Hit of carbonates. Quantitative image analysis of 250 thin sections enables us to quantify the concentration of micropores and macropores, which forms the base of our rock physics modeling study. We model the effect of the varying stiffness of those two pore populations on Previous HitvelocityNext Hit: (a) compliant micropores and (b) stiff macropores.

To verify the model results, we compare the elastic moduli derived from ultrasonic velocities and density information with elastic moduli obtained by DEM modeling of the same samples. This DEM model that uses measured input parameters from quantitative digital image analysis of the pore structure results in an excellent prediction of acoustic properties of carbonates. The Previous HitvelocityNext Hit predictions also show significant improvement compared to Previous HitvelocityNext Hit prediction using other empirical equations; e.g., the Wyllie times average equation. In addition, we show how a low rock stiffness identifies carbonates of low permeability, indicating the potential of improved reservoir characterization from acoustic data.

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Selected Figures

 
Figure 1 Dataset: 250 samples water saturated, 160 samples under dry conditions from CSL database
Figure 2 Pore type effects.
Figure 3 Percentage microporosity of total porosity.
Figure 4

Effect of microporosity: decrease in rock stiffness. 

 
Figure 5

Differential effective medium (DEM) model.

 
Figure 5

New dual porosity DEM model.
Figure 5

Industry standard (left) and new approach (right), showing Previous HitvelocityNext Hit as a function of porosity (upper) and porosity-permeability relationships (lower).

Key Points

    ·         Laboratory data shows that compliant micropores have a strong softening effect on the sonic Previous HitvelocityNext Hit of carbonates.

    ·         Macroporosity causes data scatter in Previous HitvelocityNext Hit-porosity space.

    ·         Dual porosity DEM model that incorporates micro- and macroporosity predicts very well elastic properties.

Workflow for Dual DEM Model

 

 (1) Quantitative image analysis on thin sections:

     (a) Fraction of macroporosity and microporosity.

     (b) Average aspect ratio of macroporosity.

(2) Determine average aspect ratio of microporosity by best fit multiple model runs using different aspect ratios of microporosity fraction.

(3) Use fraction of macroporosity and microporosity to model both, shear and bulk moduli (and Previous HitvelocityNext Hit) from thin sections.

Conclusions

    ·         Laboratory data shows that compliant micropores have a strong softening effect on the sonic Previous HitvelocityTop.

    ·         Digital image analysis of thin sections provides pore structure descriptions (fraction of micro- and macroporosity).

    ·         Dual porosity DEM model incorporates micro- and macroporosity and enables Vs and Vp predictions.

     

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