Mathematics > Optimization and Control
[Submitted on 30 Oct 2022 (v1), last revised 11 Jan 2023 (this version, v2)]
Title:Does 3D frequency-domain FWI of full-azimuth/long-offset OBN data feasible? The Gorgon case study
View PDFAbstract:Frequency-domain Full Waveform Inversion (FWI) is potentially amenable to efficient processing of full-azimuth long-offset stationary-recording seabed acquisition carried out with sparse layout of ocean bottom nodes (OBNs) and broadband sources because the inversion can be performed with a few discrete frequencies. However, computing efficiently the solution of the forward (boundary-value) problem in the frequency domain with linear algebra solvers remains a challenge for large computational domains involving tens to hundreds of millions of parameters. We illustrate the feasibility of 3D frequency-domain FWI with the 2015/16 Gorgon OBN case study in the NorthWestern shelf, Australia. We solve the forward problem with the massively-parallel multifrontal direct solver MUMPS, which includes four key features to reach high computational efficiency: An efficient parallelism combining message-passing interface and multithreading, block low-rank compression, mixed precision arithmetic and efficient processing of sparse sources. The Gorgon subdataset involves 650 OBNs that are processed as reciprocal sources and 400,000 sources. Mono-parameter FWI for vertical wavespeed is performed in the visco-acoustic VTI approximation with a classical frequency continuation approach proceeding from a starting frequency of 1.7 Hz to a final frequency of 13 Hz. The target covers an area ranging from 260 km2 (frequency > 8.5 Hz) to 705 km2 (frequency < 8.5 Hz) for a maximum depth of 8 km. Compared to the starting model, FWI dramatically improves the reconstruction of the bounding faults of the Gorgon horst at reservoir depths as well as several intra-horst faults and several horizons of the Mungaroo formation down to a depth of 7 km.
Submission history
From: Hossein Aghamiry [view email][v1] Sun, 30 Oct 2022 08:06:28 UTC (2,627 KB)
[v2] Wed, 11 Jan 2023 22:47:27 UTC (2,154 KB)
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