RESEARCH GOALS

I propose to use the comprehensive 3-D Amoco data set to estimate reservoir mechanical properties and their spatial variation in a true 3-D sense. This procedure will require sequential data processing steps involving: (1) P and S velocity analysis from 3-D $\grave{P}\!\acute{P}$ and 2-D $\grave{P}\!\acute{S}$ reflection data, (2) 3-D prestack migration images of reservoir structure, stratigraphy and fault geometry, (3) 3-D simultaneous prestack inversion of the $\grave{P}\!\acute{P}$ and $\grave{P}\!\acute{S}$ reflection data for P and S relative impedance contrasts within the reservoir zone, and (4) integration of the P and S velocity and impedance contrast information to make estimates of the P and S impedances I_P and I_S, in a 3-D spatial volume encompassing the reservoir block.

The most significant portion of this research effort is directed at the problem of estimating impedance contrasts from seismic reflection data. I will approach this problem in the following manner. Using a reliable estimate of the P and S migration velocity models resulting from the velocity analysis step (1), multiple constant offset elastic migrations will be performed for each of the $\grave{P}\!\acute{P}$ and $\grave{P}\!\acute{S}$ data sets. This procedure will result in four sequences of maps: $R_{PP}({\bf x};{\bf x}_h)$,$\Theta_{PP}({\bf x};{\bf x}_h)$, $R_{PS}({\bf x};{\bf x}_h)$ and $\Theta_{PS}({\bf x};{\bf x}_h)$, where R represents the angle-dependent elastic reflectivity estimate, and $\Theta$ represents the reflection angle estimate. The R and $\Theta$values make a direct mapping to $\grave{P}\!\acute{P}$ and $\grave{P}\!\acute{S}$ reflectivity as a function of reflection angle, which can subsequently be inverted for P and S impedance contrasts, using the Zoeppritz plane-wave response, as a function of subsurface position. The theory for making these reflectivity and angle estimates will be based on elastic Kirchhoff integrals and ray-theoretic WKBJ Green's functions (Lumley and Beydoun, 1991; and Lumley 1992, 1993a and 1993b.)

Once the impedance contrasts are estimated, they can be linearly combined with the P and S velocity estimates to make broadband impedance estimates. Spatial variations in I_P and I_S are useful in that they have physical correlations with: presence and saturation of gas in pore space (I_P low, I_S normal to high), fractured high permeability zones (both I_P and I_S are low), and can be combined to estimate 3-D variations in Poisson's Ratio, which can be a good discriminator of lithology (e.g., sandstone vs. shale vs. coal). I propose to correlate my I_P and I_S results with Amoco borehole, rock physics, and production engineering data. This correlation will be at the very least a qualitative integration of these multi-disciplinary data types, and may possibly extended to a quantitative integration using existing Markov-Bayes methods of spatial geostatistics.