Estimation of Water Saturation from Seismic Attributes in One of the South Iranian Oil Fields

Estimation of water saturation is very important in oil and gas industry. This parameter plays an important role in reserve estimation. The prediction of water saturation for estimation of reservoir fluid volume and determination of reservoir properties is necessary. In this study, by using combination of wells and seismic data, the estimation of water saturation first in wells location, and then the distribution of this parameter in reservoir using different seismic attributes has been estimated. To do this, first, seismic inversion using model-based method was performed and acoustic impedance was computed. In the next step, the water saturation using seismic multiple attribute and artificial neural network methods has been estimated. The correlation of the seismic multiple attribute and artificial neural network methods between actual and predicted values were ۸۴ and ۹۰% in training data and ۶۸ and ۶۷% in validation data, respectively.

Keywords:

Water Saturation , Seismic Inversion , Acoustic Impedance , Seismic Attributes , Seismic multiple attribute method , Artificial Neural Network