A novel directional-oriented method for predicting shear wave velocity through empirical rock physics relationship...

Area of Science:

• Geophysics
• Petrophysics
• Reservoir Engineering

Background:

• Shear wave velocity (Vs) is a critical parameter for characterizing rock properties and fluid content in hydrocarbon reservoirs.
• Traditional empirical rock physics relationships (ERR) often show limitations in accurately predicting Vs, especially in complex geological formations like carbonate reservoirs.
• Geostatistical methods (GM) offer a powerful framework for spatial modeling and prediction, potentially enhancing Vs estimation.

Purpose of the Study:

• To design and evaluate a novel direction-oriented geostatistical approach for estimating shear wave velocity (Vs) using density in carbonate reservoirs.
• To compare the performance of the developed geostatistical method against traditional empirical rock physics relationships.
• To assess the accuracy and robustness of the proposed method using various statistical benchmarks.

Main Methods:

• Estimation of Vs using four selected empirical rock physics relationships (ERR) in a target well (Well A).
• Application of geostatistical methods, including Ordinary Kriging (OKr), Cross-Validation (CVm), and Jack-knife (JKm), to improve Vs estimation using density.
• Utilizing geophysical log data, including density and existing Vs measurements, from three hydrocarbon wells (A, B, and C) in a carbonate reservoir.

Main Results:

• The Greenberg and Castagna ERR showed the best performance among the tested empirical methods (R²=0.8104, Correlation=0.90).
• The geostatistical approach, particularly Cross-Validation (CVm), demonstrated improved Vs estimation accuracy (R²=0.8865, Correlation=0.94) when trained with some original Vs data.
• The Jack-knife method (JKm), when applied without original Vs data from the target well, also yielded excellent results (R²=0.8503, Correlation=0.922), highlighting the method's robustness.

Conclusions:

• The developed direction-oriented geostatistical method significantly outperforms traditional empirical rock physics relationships for Vs estimation in the studied carbonate reservoir.
• Geostatistical methods, especially when incorporating density data, provide a more accurate and robust approach to Vs prediction compared to conventional techniques.
• This study confirms the substantial potential of geostatistical modeling to enhance shear wave velocity estimation in complex geological settings.