Generalised Survey Optimisation with Constraints

The ultra-long offset ocean-bottom node (OBN) acquisition technique to stabilise full-waveform inversion has already been used successfully in the deep-water US Gulf of Mexico (GoM) characterised by shallow salt bodies hindering accurate earth model building, which is critical for the imaging of otherwise obscured deep geologic structures. Multi-client data acquisition at a large scale in the US GoM are typical and provide a unique opportunity for emerging seismic technologies to be deployed, tested, and developed at scale. One such technology, full-waveform inversion (FWI), has delivered significant improvements in velocity and image quality but can be compromised due to the acquisition parameters and associated costs required to optimise FWI. To reduce the acquisition cost, simultaneous acquisition is preferable, which requires a source separation framework. We propose generating an optimal survey design using the spectral-gap-based rank minimisation, termed as generalised survey optimisation with constraints. The proposed technique is computationally efficient and uses realistic environmental and instrumental constraints to generate source and/or receiver locations, where the acquisition is constrained with random time dithers. Using both synthetic and real OBN data examples from the Gulf of Mexico, we demonstrate the efficacy of the proposed technology over the standard acquisition practices.