An integrated approach for 3D seismic‐based reservoir characterization: An example of northern Chezhen Sag, Shengli Oilfield

Acoustic impedance (AI) estimated from seismic data has been a powerful tool for reservoir characterization for nearly three decades. However, because of the difficulty of building an accurate initial model and the restrictions of model updating, inverted AI often leads to false interpretation, especially for reservoirs with rapid lateral changes. To avoid that difficulty, we use an approach that starts with 3D seismic data and integrates AI inversion, spectral decomposition, and elastic impedance inversion for Poisson's ratio to simultaneously predict thickness and hydrocarbon‐bearing quality of the reservoir. We then apply this method to an area in the northern part of the Chezhen Sag, Shengli Oilfield, eastern China. The results of this study were used to locate and design three appraisal wells that were drilled and had hydrocarbon shows.