Seismic data play a crucial role in analyzing hydrocarbon distributions and characterizing reservoirs in the field of oil and gas exploration. While many advances have been made in conventional imaging techniques to obtain more accurate seismic data, ...
Seismic data play a crucial role in analyzing hydrocarbon distributions and characterizing reservoirs in the field of oil and gas exploration. While many advances have been made in conventional imaging techniques to obtain more accurate seismic data, there are still limitations. The main limitations of conventional imaging techniques include the inability to use the full wavefield, which means that only P-waves can be used, and the time-consuming sequential process of preprocessing, velocity model building, and migration. These limitations have increased the need for new approaches for more efficient and accurate data processing. To overcome these drawbacks of conventional imaging techniques, full-waveform inversion (FWI) and FWI imaging have been developed. FWI is a method that uses the full wavefield, including diving waves and multi-scattered waves, to predict subsurface properties. It uses an optimization method that iteratively updates the model to minimize the residual between the observed seismic data and the modeled seismic data. Moreover, FWI imaging is a technique that derives seismic images in a short time by taking the directional derivative of the FWI results. Compared with conventional imaging techniques, FWI imaging, since it is based on FWI, improves the signal-to-noise ratio and mitigates migration artifacts. In this study, a case study was conducted using 3D streamer data from a deepwater gas field to demonstrate the effectiveness of FWI imaging. As the gas field area contains scattered shallow gas, conventional imaging techniques have limitations in restoring the structure of subgas zones. To overcome this, FWI imaging was introduced, and to verify its effectiveness, reverse time migration (RTM), a representative example of conventional methods, was used for comparison. After the velocity model was updated by performing FWI up to 25 Hz, FWI imaging and RTM were applied based on the same velocity model, and the results were compared and analyzed. Compared with RTM, FWI imaging exhibited significant improvements in resolution and structural detail at various depths. Additionally, it improved the overall lateral resolution and structural continuity and effectively suppressed noise. In addition, FWI imaging does not require preprocessing or migration, which significantly reduces the processing time. These findings suggest that FWI imaging is a promising alternative to conventional methods because it provides high-quality subsurface information and reduces the processing time.