Comparison of Pore Pressure Prediction Using Conventional Seismic Velocity and Acoustic Impedance-Based Methods

In this research, pore pressure and its creation mechanism in one of oil fields in the southwest of Iran was first estimated using: 1) the velocity of seismic inversion, and 2) direct use of seismic acoustic impedance (AI) methods, and their results were then compared. At first, the cube of AI data was produced by inversion of seismic data, and the seismic velocity was then resulted accordingly. Following that, by fitting the effective pressure data with seismic velocity and AI data, the relationships between them were obtained and their initial models were construed. Next, by doing some correction on both models, their calibration coefficients were finalized and used to convert the seismic velocity and the AI data into effective pressure data. The effective pressure cubes of both models were then converted into pore pressure cubes. The results of this research in terms of separation of reservoir layers and high correlation coefficients between the predicted data and wells pressure test (0.91 for seismic velocity method and 0.925 for AI method) together with low standard error indicate the capability of both methods to predict pore pressure in carbonate reservoirs. Finally, the results of both methods were compared, and it has been found out that the direct use of seismic AI data for pore pressure prediction, which is being done for the first time in this study for carbonate reservoirs, has noticeable improvement for separation of the reservoir layers in comparison with the conventional velocity method. Finally, the results of AI method show a better resolution for Sarvak and Ilam reservoirs. Also, the thin Bourgan as well as the Fahliyan reservoirs, where have not been identified precisely by velocity method, have been correctly identified by this new method with pore pressure more than those the above and under layers.