Post- and pre-stack attribute analysis and inversion of Blackfoot 3Dseismic dataset
The objective of this research is comparative analysis of several standard and one new seismic post- and pre-stack inversion methods and Amplitude Variation with Offset (AVO) attribute analysis in application to the CREWES Blackfoot 3D dataset. To prepare the data to the inversion, I start with processing the dataset by using ProMAX software. This processing, in general, includes static and refraction corrections, velocity analysis and stacking the data. The results show good quality images, which are suitable for inversion. Five types of inversion methods are applied to the dataset and compared. Three of these methods produce solutions for the post-stack Acoustic Impedance (AI) and are per-formed by using the industry-standard Hampson-Russell software. The fourth method uses our in-house algorithm called SILC and implemented in IGeoS seismic processing system. In the fifth approach, the pre-stack gathers are inverted for elastic impedance by range-limited stacking of the common-midpoint (CMP) gathers in offsets and/or angles and then performing independent inversion of angle stack. Further, simultaneous inversion is applied to pre-stack seismic data to invert for both the P- and S-wave impedances. These impedances are used to extract the Lamé parameters multiplied by density (LMR), and used to extract the ratios between the P- and S-wave velocities. In addition, CMP gathers are used to produce AVO attribute images, which are good indicators of gas reservoirs. Finally, the results of the different inversion techniques are interpreted and correlated with well-log data and used to characterize the reservoir. The different inversion results show clearly the reservoir with its related low impedance within the channel. The post-stack inversion gives the best results; in particular, the model-based inversion shows smoothed images of it while SILC provides a different, higher-resolution image. The elastic impedance also gives results similar to the post-stack inversion. Pre-stack inversion and AVO attributes give reasonable results in cross sections near the center of study area. In other areas, performance of pre-stack inversion is poorer, apparently because of reflection aperture limitations.
Master of Science (M.Sc.)