TITLE:
Research on Multi-Wave Pore Pressure Prediction Method Based on Three Field Velocity Fusion
AUTHORS:
Junlin Zhang, Huan Wan, Yu Zhang, Yumei He, Linlin Dan
KEYWORDS:
Velocity Field, Resolution, Machine Learning, AVO Inversion, Pore Pressure
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.12 No.6,
June
28,
2024
ABSTRACT: The optimization of velocity field is the core issue in reservoir seismic pressure prediction. For a long time, the seismic processing velocity analysis method has been used in the establishment of pressure prediction velocity field, which has a long research period and low resolution and restricts the accuracy of seismic pressure prediction; This paper proposed for the first time the use of machine learning algorithms, based on the feasibility analysis of wellbore logging pressure prediction, to integrate the CVI velocity inversion field, velocity sensitive post stack attribute field, and AVO P-wave and S-wave velocity reflectivity to obtain high-precision seismic P and S wave velocities. On this basis, high-resolution formation pore pressure and other parameters prediction based on multi waves is carried out. The pressure prediction accuracy is improved by more than 50% compared to the P-wave resolution of pore pressure prediction using only root mean square velocity. Practice has proven that the research method has certain reference significance for reservoir pore pressure prediction.