From raw seismic data to quantitative interpretation via cloud-based FWI
Henry A. Debens
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Henry Debens has been working as a Geophysicist at Woodside Energy since 2016, primarily in the Technology & Innovation group and lately as part of the Global Wells & Seismic group. He joined Woodside after completing an MSci in geophysics and a PhD in petroleum geophysics at Imperial College London. Henry’s work involves all aspects of the seismic data life cycle, with projects ranging from acquisition through to interpretation, but chiefly concerns the development and application of novel approaches to seismic imaging and inversion. |
Abstract
Full-waveform inversion (FWI) has evolved in recent years from a technique for recovering long- to intermediate-wavelength updates of acoustic overburden velocities as part of a broader model building workflow to a standalone tool for high-fidelity seismic imaging using raw seismic data – with ever greater resolution and ever more sophisticated physics being sought. In doing so, it has moved notably closer to fulfilling the vision of its original inventors in the late 70s and early 80s. In this work, two novel approaches to FWI along with enabling technologies for their effective deployment are considered. The first of these allows for robust long-wavelength updates to be generated from raw seismic data in the absence of diving wave energy, providing reliable estimates of acoustic velocity at depths equivalent to or greater than the longest offsets available in the data – thereby enabling more effective imaging with data of limited quality. The second allows for the estimation of elastic amplitude-versus-angle behaviour while still using an acoustic wave equation, thereby mitigating the significant computational burden typically associated with elastic FWI. Finally, it is demonstrated that these approaches can be deployed in a reliable and cost-effective manner via the considered use of public cloud resources, with learnings relevant for analogous massively parallel scientific applications. Case studies from two marine environments are provided for discussion, one being from deep-water US Gulf of Mexico and the other from intermediate water depths offshore Western Australia.
Keywords: AVA, compression, FWI, HPC, public cloud, quantitative interpretation, seismic imaging.
Henry Debens has been working as a Geophysicist at Woodside Energy since 2016, primarily in the Technology & Innovation group and lately as part of the Global Wells & Seismic group. He joined Woodside after completing an MSci in geophysics and a PhD in petroleum geophysics at Imperial College London. Henry’s work involves all aspects of the seismic data life cycle, with projects ranging from acquisition through to interpretation, but chiefly concerns the development and application of novel approaches to seismic imaging and inversion. |
References
Debens HA, Knodel D, Umpleby A, Mavropoulos C (2023) Enabling technologies for economical and efficient cloud-based FWI. In ‘Proceedings of the Third International Meeting for Applied Geoscience & Energy’, 28 August–1 September 2023, Houston, USA. pp. 650–654. (Society of Exploration Geophysicists and American Association of Petroleum Geologists)
Frahm L, Bell R, Davy R, Morgan J, Warner M, Bangs N, Aria R, Kodaira S, Henrys S, Debens H (2023) AVA parameters from FWI: Field results. In ‘Proceedings of the Third International Meeting for Applied Geoscience & Energy’, 28 August–1 September 2023, Houston, USA. (Society of Exploration Geophysicists and American Association of Petroleum Geologists)
Lindstrom P (2014) Fixed-Rate Compressed Floating-Point Arrays. IEEE Transactions on Visualization and Computer Graphics 20(12), 2674-2683.
| Crossref | Google Scholar | PubMed |
McLeman J, Rayment T, Burgess T, Dancer K, Hampson G, Pauli A (2023) Superior resolution through multiparameter FWI imaging: A new philosophy in seismic processing and imaging. Geophysics 41(1), 34-43.
| Crossref | Google Scholar |
Shah N, Warner M, Umpleby A, Nangoo T, Debens HA (2023) Sub-salt model building and imaging with WAZ data: An FWI-based data-driven workflow. In ‘Proceedings of the Third International Meeting for Applied Geoscience & Energy’, 28 August–1 September 2023, Houston, USA. (Society of Exploration Geophysicists and American Association of Petroleum Geologists)
Tarantola A (1986) A strategy for nonlinear elastic inversion of seismic reflection data. Geophysics 51(10), 1893-1903.
| Crossref | Google Scholar |
Warner M, Guasch L (2016) Adaptive waveform inversion: Theory. Geophysics 81(6), R429-R445.
| Crossref | Google Scholar |
Zoeppritz K (1919) VII b. Über Reflexion und Durchgang seismischer Wellen durch Unstetigkeitsflächen. Nachrichten von der Königlichen Gesellschaft der Wissenscaften zu Göttingen – Mathematisch-Physikalische Klasse 1919, 66-84 [In German] https://eudml.org/doc/59042.
| Google Scholar |
