Orphan Basin, Canada
PGS, in partnership with TGS, has been acquiring modern 3D GeoStreamer data offshore Newfoundland and Labrador since 2015. The availability of such data has been a critical component in the success of the Call for Bids from 2015 through 2020. Access to 3D data provides confidence when bidding on prize blocks and the use of high-end technology shortens the time to first drill and potentially first oil. The PGS/TGS data library comprises approximately 35 000 sq. km of 3D data in the Eastern Newfoundland region defined under the Land Tenure System. The Call for Bids in this area closes in November 2022. High-end imaging technology, like PGS Ultima, and quantitative interpretation workflows clearly demonstrate significant prospectivity in the region, and particularly in the underexplored Orphan Basin.
Large-scale Paleogene marine fan systems align along the shelf margin off the northeast coast of Newfoundland. The shallow water, multiples and velocity contrasts in the upper section are the main challenges for derisking the main lead (yellow ellipse). The uplift from PGS Ultima improves the understanding of such prospects within the Blomidon survey.
In a traditional sequential imaging workflow, velocity and reflectivity are inverted separately. Exploration teams must wait until the end of the data processing phase to be able to generate a density attribute from the data. PGS Ultima implements Full Waveform Inversion (FWI) and Least Squares Migration (LSM) in a joint scheme and updates both velocity and reflectivity simultaneously at each iteration. It is a data-driven approach and can be run very quickly to deliver direct estimates of the subsurface velocity, reflectivity, and their derivatives, e.g., relative impedance and relative density.
PGS Ultima is a good solution when time is critical, for example, if processing overlaps with a bid round schedule and puts exploration teams under pressure to meet deadlines. It is a fast data-driven approach that delivers direct estimates of the subsurface velocity, reflectivity, and their derivatives, e.g., relative impedance and relative density. Depending on the geological setting and the target level, it can start from minimal pre-processed input data and can be run very effectively, enabling the technical teams to perform prospectivity and risk assessments in a shorter time frame.
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