A Novel Approach of Frequency-Dependent Seismic Elastic Parameters Inversion for Fluid Prediction at Thin Sandstone Reservoirs - Miao, Fawei; He, Yan-Xiao; Ni, Jingyang; Yuan, Sanyi; Wang, Shangxu (IEEE geoscience and remote sensing letters, 2025)
One of the leading challenges in hydrocarbon recovery is predicting fluid distribution throughout the reservoir, using dispersion of seismic elastic parameters to solve this problem is a method with great potential. Previous studies reveal that predicting frequency-dependent seismic elastic parameters is difficult because of their sensitivity to seismic wave amplitude. The frequency-dependent AVO inversion schemes are widely used to estimate the dispersion gradient attributes for fluid prediction. However, these methods strongly depend on the advanced spectral decomposition and the wavelet overprint effect in time-frequency information. For this reason, this study presents an innovative technique that combines prestack AVO inversion and linear Bayesian inversion algorithm to predict directly frequency-dependent P-wave velocity of multilayered medium from seismic reflection data, which can quantitatively describe the change of P-wave velocity in seismic frequency band. Furthermore, frequency-dependent elastic parameters were used to define a dispersion factor for fluid prediction in thin sandstone reservoirs. The novelty of the study is that the proposed approach introduces prestack AVO inversion to provide reliable initial model and constructs dispersive P-wave velocity inversion framework of layered medium for the first time. Additionally, the dispersive elastic parameters have more potential applications than the dispersion gradient attributes. Tests on the synthetic and real data demonstrate that the frequency-dependent P-wave velocity of multilayered medium can be estimated reasonably and stably. In this application, we use a test well to assess locally the performance of the technique.