Time-lapse analysis of seismic surveys to monitor hydrocarbon production has been based so far mainly on amplitude and traveltime changes of seismic signals. However, lab measurements of rock properties show that we can also expect observable changes in the anelastic absorption, when the originally saturating fluids are replaced by others, or even when compaction or fractures are induced. These changes can be detected by Q-factor reflection tomography and used for time-lapse analysis, as a complement to traveltime inversion. Indeed, the seismic signal change due to fluid substitution is observable both in P velocity and Q factor estimates, and from case to case one can be stronger than the other. Their coupled inversion reduces the uncertainties for interpreters involved in reservoir characterization, providing them more information for detecting different lithotypes. The time-lapse tomography we adopted limits the variations of P velocity and Q factor away from the reservoir, and imposes that the interfaces' structure is the same in those external areas. The mismatch between actual and estimated models decreases significantly when these mutual constraints are applied, with respect to an uncoupled inversion where both rock parameters and interfaces' structures are inverted in a totally independent way. The resolution needed for reservoir monitoring is high, so a macro-model analysis, as provided by traveltime inversion or the frequency shift method for the Q factor, is not sufficient. However, those estimates may be complemented with a high-frequency component obtained by the instantaneous frequency. The resulting broadband image in depth for the anelastic absorption may approximate results typical of full-waveform inversion, but at a much cheaper computational cost.
|Original language||English (US)|
|Number of pages||15|
|Journal||JOURNAL OF APPLIED GEOPHYSICS|
|State||Published - Apr 9 2019|
Bibliographical noteKAUST Repository Item: Exported on 2022-06-07
Acknowledged KAUST grant number(s): OSR-2015-CRG4-2619
Acknowledgements: Our work was partially funded by the Petroleum Institute Research Centre (Abu Dhabi, United Arab Emirates) and by the grant OSR-2015-CRG4-2619 from KAUST (Thuwal, Saudi Arabia). We thank Gualtiero Bohm, Davide Gei and Jose' Carcione (OGS, Italy) who kindly provided the computer codes for seismic tomography and modelling, and Tariq Alkhalifah (KAUST) for the support and encouragements.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.