Case history: Acoustic impedance inversion of the lower Permian carbonate Buildups in Permian Basin, Texas

Abstract

Acoustic impedance inversion provides a basis for the characterization and imaging of carbonate buildups using a 3D seismic data from the Midland Basin, located in the Permian Basin of West Texas. These carbonate buildups are the main reservoirs in this area. The bandwidth of the inverted acoustic impedance was the same as the input seismic data. From the geological model generated from well data, the low frequency content missing in seismic data is added to generate a broadband acoustic impedance volume. From the broadband data, high resolution maps of acoustic impedance distributions were obtained, facilitating the location of carbonate buildups. With the aid of well data, a correlation between acoustic impedance and porosity was extracted to estimate porosity of the carbonate buildups. Areas with high acoustic impedance have low porosity values, whereas high porosities were located in areas of low acoustic impedance. Theoretical analyses of these results using the Time‐Average equation and the Gassmann equation show how porosity distributions affect the acoustic impedance. Both equations predicted a decrease in acoustic impedance as porosity increases. Inversion results showed that average porosity values are 0.05 ± 0.05, typical for densely cemented rocks. Previous studies done in the same area indicate that rock grains are moderately to well‐sorted. This suggests that Time‐Average approximation will overestimate porosity values and the Gassmann approach predicts better the measured data. A comparison between measured data and the Gassmann equation suggests that rocks with low porosities (less than 5%) tend to have high acoustic impedance values. On the other hand, rocks with higher porosities (5% to 10%) have lower acoustic impedance. The inversion performed on well data also shows that fluid bulk modulus for reservoir rocks is lower than in non‐reservoir rocks, which can be correlated to oil and brine, respectively. This result is consistent with production data.