Estimating the 3-D spatial distribution of mechanical properties of rock by seismic data and well logs

The rock mechanical properties influence the selection of drilling parameters, optimized drilling trajectory, and appropriate hydraulic fracturing intervals. Estimating the 3-D spatial distribution of these geomechanical properties at the reservoir scale is a challenging task, especially in the case of limited data only at the well locations. Advanced geostatistical techniques can be utilized to represent a reservoir's inherent spatial variation more realistically. In this study, we investigate the spatial variability of rock mechanical properties, including Young's modulus, shear modulus, bulk modulus, and Poisson's ratio, as major constituents of the reservoir geomechanical model. The data are extracted from a hydrocarbon field located southwest of Iran and consist of forty wells. We first build a 1-D model of rock elastic moduli at each well by integrating petrophysical and core-based laboratory measurements and then develop a corresponding 3-D model using geostatistical simulation techniques. Thereafter, 3-D seismic data are employed to optimize the geomechanical model. Results show that the integration of well logs with seismic data increases the accuracy of field-wise 3-D elastic moduli models. Furthermore, we used various co-simulation techniques to demonstrate the improving effect of complementary data in constructing a more realistic reservoir geomechanical model.

Automated summary

In this study, advanced geostatistical techniques were used to investigate the spatial variability of rock mechanical properties at a reservoir scale. A 1-D model was built at each well using well log data, and a corresponding 3-D model was developed using geostatistical simulation techniques. 3-D seismic data were then used to optimize the geomechanical model. Results showed that the integration of well logs with seismic data increased the accuracy of field-wise 3-D elastic moduli models, and various co-simulation techniques demonstrated the improving effect of complementary data in constructing a more realistic reservoir geomechanical model.