Enabling full-waveform inversion to recover salt bodies in challenging conditions: A field data application ��
Abdullah Alali and Tariq Alkhalifah
Motivation
Enabling FWI to recover salt bodies in challenging condition
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(Duffy et.al, 2022)
Duffy, Oliver B., et al. "The role of salt tectonics in the energy transition: An overview and future challenges." (2022).
geothermal
Full-waveform inversion (FWI) with salt bodies
Enabling FWI to recover salt bodies in challenging condition
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(Kalita et.al, 2019)
FWI
BP salt model
Initial model
Inversion result
Kalita, Mahesh, et al. "Regularized full-waveform inversion with automated salt flooding." Geophysics 84.4 (2019): R569-R582.
Full-waveform inversion (FWI) with salt bodies
Enabling FWI to recover salt bodies in challenging condition
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Top to bottom approach
1.6 Hz
Long offset ~ 20 km
FWI
(Shen et al., 2017)
Shen, Xukai, et al. "Salt model building at Atlantis with full-waveform inversion." SEG Technical Program Expanded Abstracts 2017. Society of Exploration Geophysicists, 2017. 1507-1511.
Objectives
Enabling FWI to recover salt bodies in challenging condition
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Initial model
Imaging -Picking ToS
Flooding
Imaging – Picking BoS
Unflooding
Top-to-bottom:
Objectives:
Utilize deep learning(U-net) for flooding and unflooding
2. Reduce the imaging cost
Reconstruct the salt in multi-scale frequency FWI
Depends on the velocity estimation by U-net
1D Training workflow
Enabling FWI to recover salt bodies in challenging condition
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Network Input
(FWI)
Network Output
(Flooding/unflooding)
Generating training data
Enabling FWI to recover salt bodies in challenging condition
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Random 1D models
Adding salts
FWI
Validation Samples
Enabling FWI to recover salt bodies in challenging condition
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Flooding 1
Initial for FWI
FWI
Target
Prediction
Validation Samples
Enabling FWI to recover salt bodies in challenging condition
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Flooding 2
Initial for FWI
FWI
Target
Prediction
Validation Samples
Enabling FWI to recover salt bodies in challenging condition
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Unflooding
Initial for FWI
FWI
Target
Prediction
BP 2004 salt model (central part)
Enabling FWI to recover salt bodies in challenging condition
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Max. Offset 6 km
Min. Frequency 3 Hz
BP inversion – FWI
Enabling FWI to recover salt bodies in challenging condition
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Flooding 1
Flooding 2
Unflooding
FWI
FWI
Initial
model
Freq < 7 Hz
Freq < 10 Hz
Freq < 15 Hz
BP inversion - flooding 1
Enabling FWI to recover salt bodies in challenging condition
Flooding 1
Flooding 2
Unflooding
FWI
FWI
Initial
model
Freq < 7 Hz
Freq < 10 Hz
Freq < 15 Hz
BP inversion – FWI
Enabling FWI to recover salt bodies in challenging condition
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Flooding 1
Flooding 2
Unflooding
FWI
FWI
Initial
model
Freq < 7 Hz
Freq < 10 Hz
Freq < 15 Hz
BP inversion - flooding 2
Enabling FWI to recover salt bodies in challenging condition
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Flooding 1
Flooding 2
Unflooding
FWI
FWI
Initial
model
Freq < 7 Hz
Freq < 10 Hz
Freq < 15 Hz
BP inversion – FWI
Enabling FWI to recover salt bodies in challenging condition
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Flooding 1
Flooding 2
Unflooding
FWI
FWI
Initial
model
Freq < 7 Hz
Freq < 10 Hz
Freq < 15 Hz
BP inversion - Unflooding
Enabling FWI to recover salt bodies in challenging condition
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Flooding 1
Flooding 2
Unflooding
FWI
FWI
Initial
model
Freq < 7 Hz
Freq < 10 Hz
Freq < 15 Hz
BP inversion – Final FWI
Enabling FWI to recover salt bodies in challenging condition
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Flooding 1
Flooding 2
Unflooding
FWI
FWI
Final
FWI
Initial
model
Freq < 7 Hz
Freq < 10 Hz
Freq < 15 Hz
Gulf of Mexico (Mississippi Canyon) data
Enabling FWI to recover salt bodies in challenging condition
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Shot gather
Frequency spectrum
Max. offset: 4.8 Km
Min. frequency: ~5 Hz
GOM inversion
Enabling FWI to recover salt bodies in challenging condition
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Flooding 1
Flooding 2
Unflooding
FWI
FWI
Initial model
Freq < 7.5 Hz
Freq < 10 Hz
Freq < 15 Hz
GOM Final inversion and RTM image
Enabling FWI to recover salt bodies in challenging condition
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Final Inversion
RTM image
FWI and RTM overlay
GOM Final inversion and RTM image
Enabling FWI to recover salt bodies in challenging condition
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FWI and RTM overlay
Common Angle Gathers
Conclusions
Enabling FWI to recover salt bodies in challenging condition
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- Efficient 1D training
- Prevent adding cost courtesy of the multiscale FWI
- Challenging synthetic and field dataset
Acknowledgments
Abdullah Alali
Tariq Alkhalifah
08-06-2023
Thank you for listening!