Full Waveform Inversion (FWI) delivers high-resolution quantitative images and is a promising technique to obtain macro-scale physical properties model of the subsurface. In most geophysical applications, prior information, as those collected in wells, is available and should be used to increase the image reliability. For this, we propose to introduce three
Full‐waveform inversion is an appealing technique for time‐lapse imaging, especially when prior model information is included into the inversion workflow. Once the baseline reconstruction is achieved, several strategies can be used to assess the physical parameter changes, such as parallel difference (two separate inversions of baseline and monitor data sets), sequential difference (inversion of the monitor data set starting from the recovered baseline model) and double‐difference (inversion of the difference data starting from the recovered baseline model) strategies. Using synthetic Marmousi data sets, we investigate which strategy should be adopted to obtain more robust and more accurate time‐lapse velocity changes in noise‐free and noisy environments. This synthetic application demonstrates that the double‐difference strategy provides the more robust time‐lapse result. In addition, we propose a target‐oriented time‐lapse imaging using regularized full‐waveform inversion including a prior model and model weighting, if the prior information exists on the location of expected variations. This scheme applies strong prior model constraints outside of the expected areas of time‐lapse changes and relatively less prior constraints in the time‐lapse target zones. In application of this process to the Marmousi model data set, the local resolution analysis performed with spike tests shows that the target‐oriented inversion prevents the occurrence of artefacts outside the target areas, which could contaminate and compromise the reconstruction of the effective time‐lapse changes, especially when using the sequential difference strategy. In a strongly noisy case, the target‐oriented prior model weighting ensures the same behaviour for both time‐lapse strategies, the double‐difference and the sequential difference strategies and leads to a more robust reconstruction of the weak time‐lapse changes. The double‐difference strategy can deliver more accurate time‐lapse variation since it can focus to invert the difference data. However, the double‐difference strategy requires a preprocessing step on data sets such as time‐lapse binning to have a similar source/receiver location between two surveys, while the sequential difference needs less this requirement. If we have prior information about the area of changes, the target‐oriented sequential difference strategy can be an alternative and can provide the same robust result as the double‐difference strategy.
Extracting detailed earth information from an ensemble of seismic traces is a challenge facing full-waveform inversion. So far, success on synthetic and real data has been accomplished primarily for the twin purposes of complex structural imaging and geologic interpretation. An ongoing issue for the seismicimaging community, in addition to building high-resolution images, is the reliable extraction of acoustic and shear velocities, anisotropic parameters, quality factors, and density. Such extractions, performed at the seismic resolution scale, should help greatly with quantitative interpretation and estimation of rock properties. A step toward this goal is described here. A generic rock-physics model is assumed, which upscales microscale rock-physics properties to mesoscale (effective-medium) poroelastic quantities to be recovered from macroscale estimates of seismic attributes. It is shown on simple synthetic examples that quantitative multiparameter reconstruction, when it is possible, can reduce ambiguities in mesoscale parameter estimation dramatically, using a semiglobal search. Successful estimation of these effective-medium quantities will narrow the range of possible rock-physics estimations to be considered for seismic imaging target zones. For example, estimating the P-wave quality factor along with P-wave velocity from full-waveform inversion is shown to change the estimation of mesoscale parameters significantly, assuming that the upscaling of the rock-physics model and the recovered macroscale parameters are well constrained. In addition, shear-wave information is shown to be crucial for pressure-saturation discrimination. The inferred information at the reservoir level, resulting from full-waveform inversion and subsequent mesoscale estimation, can be useful for reservoir characterization.
The estimation of quantitative rock physics properties is of great importance for reservoir characterization and monitoring in CO 2 storage or enhanced oil recovery as an example. We have combined the high-resolution results of full-waveform inversion (FWI) methods with rock physics inversion. Because we consider a generic and dynamic rock physics model, our method is applicable to most kinds of rocks for a wide range of frequencies. The first step allows determination of viscoelastic effective properties, i.e., quantitative seismic attributes, whereas the rock physics inversion estimates rock physics properties (porosity, solid frame moduli, fluid phase properties, or saturation). This two-step workflow is applied to time-lapse synthetic and field cases. The sensitivity tests that we had previously carried out showed that it can be crucial to use multiparameter inputs to accurately recover fluid saturations and fluid properties. However, due to the limited data availability and difficulties in getting reliable multiparameter FWI results, we are limited to acoustic FWI results. The synthetic tests are conclusive even if they are favorable cases. For the first time-lapse fluid substitution synthetic case, we first characterize the rock frame parameters on the baseline model using P-wave velocity estimations obtained by acoustic FWI. Then, we obtain an accurate estimation of fluid bulk modulus from the time-lapse P-wave velocity. In the Marmousi synthetic case, the rock frame properties are accurately recovered for the baseline model, whereas the gas saturation change in the monitor model is not estimated correctly. On the field data example (time-lapse monitoring of an underground blowout in the North Sea), the estimation of rock frame properties gives results on a relatively narrow range, and we use this estimation as a starting model for the gas saturation inversion. We have found that the estimation of the gas saturation is not accurate enough, and the use of attenuation data is then required. However, the uncertainty on the estimation of baseline rock frame properties is not critical to monitor gas saturation changes.
For monitoring purposes, one of the promising techniques dedicated to assess physical properties changes in target regions is the differential waveform inversion, both in the acoustic and elastic cases. A central question of this technique regards the choice of the reference model. One solution could be the use of the reconstructed baseline image provided through the standard Full Waveform Inversion (FWI) procedure of initial data. However, how the accuracy of the baseline reconstructed image will affect the precision of further time-lapse images is of crucial importance. Here, we present a sensitivity analysis of timelapse images obtained from differential inversion, with respect to various reference models. Density, P-and S-wave velocity changes could be converted into fluid property changes thanks to an empirical downscaling relationship. For accurate estimation of fluid parameter changes, the construction of highly resolved time-lapse images presenting acceptable errors is a key issue for the downscaling procedure. We illustrate on a specific synthetic example that the sensitivity analysis over the reference model variation provides linear convergence towards the time-lapse image obtained when using the exact baseline. An accurate baseline reconstruction is essential and could benefit from other data collected for monitoring purposes.
We present an application of 2D acoustic frequency-domain Full Waveform Inversion (FWI) to the hydrophone component of 4-C ocean bottom cable (OBC) data recorded from the Valhall field in North sea. The starting model for FWI was built by reflection traveltime tomography (RTT). Although this starting model leads to flat common-image gathers (CIGs), it does not allow us to match first-arrival traveltimes of diving waves from above the gas layers. This mismatch between vertical and horizontal velocities is likely the footprint of anisotropy. We updated the RTT model by first-arrival traveltime tomography (FATT) to build a new starting model for FWI. The velocities above the gas layers of the updated model are significantly higher than velocities from in-well seismic (VSP) data. FWI models were computed from the two starting models just mentioned. More stable results were obtained with the starting model updated by FATT. The resulting FWI model shows a reasonable agreement with a former model developed by 3D FWI. A reasonable match of both short-aperture and wideaperture components of the data was obtained by isotropic FWI. This might indicate that layer-induced anisotropy was created by FWI in the gas layers to balance the increase of the shallow velocities created by the inversion of the wide-aperture data components.
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