TY - GEN
T1 - Full-waveform inversion for automated salt flooding
AU - Kalita, Mahesh
AU - Kazei, Vladimir
AU - Choi, Yun Seok
AU - Alkhalifah, Tariq Ali
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We would like to thank King Abdullah University of Science & Technology (KAUST) for its support and all members of Seismic Wave Analysis Group (SWAG) for the fruitful discussions. For computer time, this research used the resources of the Super computing Laboratory and IT Research Computing at KAUST. We also thank Dr. Antoine Guitton for his valuable suggestions.
PY - 2018/10/16
Y1 - 2018/10/16
N2 - Full-waveform inversion (FWI) often attempts to resolve an ill-posed non-linear optimization problem in order to retrieve the unknown subsurface model from the seismic data. With model regularization, we alleviate the ill-posedness of FWI associated with salt bodies affected datasets by decoupling the minimization problem into two parts. We minimize the data misfit along with the total variation in the model, seeking an inverted model with sharp interfaces. In the second optimization, we penalize sharp velocity drops in the model, which is equivalent to computationally flooding of velocity field. Besides the minimal human intervention, our technique requires no information whatsoever of the top of the salt, which is required for conventional industrial salt flooding. Those features are demonstrated on a dataset corresponding to the BP 2004 model with frequencies less than 3 Hz muted to make the data more practical. The model is well retrieved if the same constant density acoustic code is used for preparing the observed data, which is still one of the most common FWI tests. However, our approach still allows us to reconstruct a reasonable depiction of the salt structure from data synthesized independently with a variable density model.
AB - Full-waveform inversion (FWI) often attempts to resolve an ill-posed non-linear optimization problem in order to retrieve the unknown subsurface model from the seismic data. With model regularization, we alleviate the ill-posedness of FWI associated with salt bodies affected datasets by decoupling the minimization problem into two parts. We minimize the data misfit along with the total variation in the model, seeking an inverted model with sharp interfaces. In the second optimization, we penalize sharp velocity drops in the model, which is equivalent to computationally flooding of velocity field. Besides the minimal human intervention, our technique requires no information whatsoever of the top of the salt, which is required for conventional industrial salt flooding. Those features are demonstrated on a dataset corresponding to the BP 2004 model with frequencies less than 3 Hz muted to make the data more practical. The model is well retrieved if the same constant density acoustic code is used for preparing the observed data, which is still one of the most common FWI tests. However, our approach still allows us to reconstruct a reasonable depiction of the salt structure from data synthesized independently with a variable density model.
UR - http://hdl.handle.net/10754/663437
UR - http://www.earthdoc.org/publication/publicationdetails/?publication=92424
UR - http://www.scopus.com/inward/record.url?scp=85083938775&partnerID=8YFLogxK
U2 - 10.3997/2214-4609.201801035
DO - 10.3997/2214-4609.201801035
M3 - Conference contribution
SN - 9789462822542
BT - 80th EAGE Conference and Exhibition 2018
PB - EAGE Publications BV
ER -