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Modeling Investigation of Correlations between Elastic Properties Predicted by Rock Physics Model with Seismic Data (Case Study of an Iranian Oil Field)

DOI: 10.4236/mnsms.2018.83003, PP. 47-63

Keywords: Carbonate Reservoir, Rock Physics Model, Elastic Property, Seismic Data

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Abstract:

Accurate characterization of seismic properties in the prediction of P-wave and S-wave velocities through carbonate reservoirs is necessary due to their intrinsic heterogeneity. Moreover, both the waves velocities mentioned above are applied to the uncertainty analysis as well as the complexity investigation presented in the carbonate reservoirs. In this study, three wells of an Iranian oil field which its formation is the upper part of the Sarvak (Mishrif) has been studied. In accordance with the petrophysical interpretation of this oil field using Geo-log software, a rock physics model has been constructed based on Xu-Payne model (2009) using Hampson-Russel software to predict the elastic properties like P-wave and S-wave velocities as well as density. In the following, some synthetic seismic traces have been created based on the rock physics model using Hampson-Russel software to obtain the correlation coefficients of the seismic data with both the predicted and measured elastic properties. As results, the obtained correlation coefficients show that the predicted elastic properties by the rock physics model have higher quality than the measured elastic properties. In addition, the correlation coefficients of the predicted elastic properties in the well number 1, 2, and 3 have approximately increased by 19.6, 21.3, and 18.2 percent, respectively, in comparison to the correlation coefficients of the measured elastic properties. Therefore, the predicted elastic properties can be replaced with the low-quality measured elastic properties. Eventually, some templates have been created to accurate characterization the carbonate reservoir based on the rock physics model and also show the high-quality correlations between the rock physics model and the measured data.

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