BUSINESS CASE: RAPID RESERVOIR CHARACTERISATION

Data preconditioning has traditionally been essential in linear workflows, aiming to align seismic gathers or angle stacks with our simplified data models. However, WEB-AVO inversion introduces a paradigm shift. This method provides a data model that aligns more closely with field data by comprehensively modeling all scattering and transmission effects occurring in the subsurface. The following example from the Central Sichuan Basin in onshore China underscores the advantages of this innovative approach.

In this case, WEB-AVO Inversion was deployed to characterize a reservoir situated at a depth of 5km. The primary challenge was the significant non-primary energy from the overburden, which obscured the reservoir’s weak primary signal. Traditional inversion methods, despite months of intensive data preconditioning to enhance the reservoir’s primary signal, failed to yield accurate pre-drill predictions.

Contrastingly, when WEB-AVO inversion was applied to both conditioned and unprocessed seismic data, it revealed that the preconditioning minimally impacted the removal of non-primary energy. This energy, previously seen as an obstacle, was effectively utilized by WEB-AVO. Moreover, preconditioning appeared to have distorted the primary energy’s amplitude and character, a conclusion drawn from the more geologically meaningful outcomes achieved with raw data.

The results of WEB-AVO inversion demonstrate that a thorough consideration of multiple scattering can significantly enhance seismic reservoir characterization in scenarios with intense scattering. Crucially, it also leads to substantial reductions in total turnaround times. By utilizing raw migrated data directly, this method circumvents the need for extensive and often ineffective seismic data conditioning. Such an approach not only saves time and costs but also markedly improves the accuracy and reliability of geological models.