Getting the most out of a large data set: A case study for a large 3D seismic interpretation project in the Carnarvon Basin, NW Australia

Abstract

A case study is presented for the seismic interpretation of a 3D seismic reprocessing project covering approximately 7200 km2 within a rift basin setting on the Northwest Shelf of Australia. The area includes two main petroleum plays: the Cretaceous Barrow Group Delta and the fluvio-deltaic Triassic Mungaroo Formation. Multiple 3D surveys of varying vintages were reprocessed to provide a unified continuous data set over the area. Seismic amplitude variation with offset inversions were conducted in time and depth domains to produce acoustic impedance and VP/VS volumes. The use of depth-domain inversion enabled more accurate inversion products to be developed with a large lateral and vertical zone of interest to assist in prospectivity assessments. Project time and cost constraints indicated a traditional seismic interpretation process would be ineffective and inefficient. The workflows applied included optimizations of the initial horizon interpretation to improve efficiency, machine learning (ML)-based automatic fault interpretation to save time, and bulk horizon interpretation for time savings and rapid stratal slicing. Utilizing ML and automated interpretation processes in conjunction with seismic inversion products enabled a full prospectivity assessment to be developed within six months. In addition to completing the work within the available time, the applied workflows allowed for significantly more time to be spent on prospectivity assessment rather than structural and stratigraphic interpretations.