Michie, E, Alaei, B and Braathen, A
(2022)
How Fault Interpretation Method May Influence the Assessment of a Fault-bound CO2 Storage Site.
In: Sixth International Conference on Fault and Top Seals.
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Abstract
Interpretation of faults in the subsurface hinges on utilising an optimum picking strategy, i.e. the seismic line spacing. Differences in line spacing lead to significant changes in subsequent fault analyses such as fault growth, fault seal and fault stability, all of which are crucial when analysing a fault-bound CO2 storage site. With the ever-advancing technologies, machine learning techniques, such as Deep Neural Networks (DNN), used for fault extraction are becoming increasingly common, however their limitations and corresponding uncertainty is still largely unknown. We show how fault extraction using DNN compares with faults that have been picked manually, and with different line spacing. Uncertainty related to both manual and automated fault extraction methods are heavily reliant on seismic quality. As such, faults that are well-imaged show a closer similarity to those that have been manually picked. Conversely, DNN picking of poorly imaged faults creates a fault surface that is more irregular and with a lower predicted stability than the smoother and simpler fault model created by manual picking. We conclude that fault picking by DNN without in-depth expertise works for well-imaged faults; poorly imaged faults require additional considerations and quality control for both manually and DNN picked faults.
| Item Type: | Conference or Workshop Item (Unspecified) |
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| Divisions: | Faculty of Science and Engineering > School of Environmental Sciences |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 17 Apr 2023 08:01 |
| Last Modified: | 17 Mar 2024 16:10 |
| DOI: | 10.3997/2214-4609.202243009 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3169576 |
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