Abstract

FWI stability is a primary concern in building an accurate velocity model using seismic waveforms. This study discusses a stabilized workflow using two shallow marine seismic datasets: a conventional streamer dataset and an OBN dataset. The study optimizes the utilization of the two datasets, ensuring accuracy in the estimation process and efficiency in computation and disk space management. A comprehensive workflow is designed with a major focus on reducing cycle-skipping by low-frequency enhancements of the input data and extracted wavelet. The workflow uses refraction and reflection tomography to generate an initial model, a cascaded loop of FWI iterations to stabilize the velocity updates, and a joint traveltime-FWI for the final velocity model. The result indicates a successful delineation of carbonate mounds and compensation of pseudostructures in the pay zone. The study also unearths the possibility of a shallow, high anisotropic layer just below the seafloor, which resulted in potential mismatch of the depth markers in earlier imaging. This study highlights the importance of considering joint datasets and a combination of inversion methodologies to unravel mysteries from a well-acquainted area