Scales of fluid saturation below seismic resolution introduce uncertainties in the interpretation of seismic velocity. A “coarse‐scale” or “patchy” distribution always has a higher effective seismic velocity than a “fine‐scale” or “uniform” distribution. We present a multidisciplinary study which links rock physics and seismic modeling with reservoir engineering, and provides strategies to reduce uncertainties in saturation scales. In our study, we performed fine‐scale flow simulations that helped us to understand which reservoir parameters control the subseismic‐resolution fluid distribution. Our studies show that when gas is injected into oil reservoirs, gravitational forces induce the formation of subresolution gas caps, which lead to patchy saturation at seismic scales. We also learned that the uniform saturation model is appropriate for most waterflooding into oil and for primary production scenarios where gas comes out of solution. Fluid density contrasts, mobility ratios, and residual oil saturations are some parameters that are crucial in constraining saturation scales.
A B S T R A C TWide-azimuth seismic data can be used to derive anisotropic parameters on the subsurface by observing variation in subsurface seismic response along different azimuths. Layer-based high-resolution estimates of components of the subsurface anisotropic elastic tensor can be reconstructed by using wide-azimuth P-wave data by combining the kinematic information derived from anisotropic velocity analysis with dynamic information obtained from amplitude versus angle and azimuth analysis of wide-azimuth seismic data. Interval P-impedance, S-impedance and anisotropic parameters associated with anisotropic fracture media are being reconstructed using linearized analysis assuming horizontal transverse anisotropy symmetry. In this paper it is shown how additional assumptions, such as the rock model, can be used to reduce the degrees of freedom in the estimation problem and recover all five anisotropic parameters. Because the use of a rock model is needed, the derived elastic parameters are consistent with the rock model and are used to infer fractured rock properties using stochastic rock physics inversion. The inversion is based on stochastic rock physics modelling and maximum a posteriori estimate of both porosity and crack density parameters associated with the observed elastic parameters derived from both velocity and amplitude versus angle and azimuth analysis. While the focus of this study is on the use of P-wave reflection data, we also show how additional information such as shear wave splitting and/or anisotropic well log data can reduce the assumptions needed to derive elastic parameter and rock properties.
The goal of this paper is to interpret and analyze time‐lapse seismic data quantitatively to better understand subsurface fluid saturations and saturation scales. We present a case study of a time‐lapse seismic survey. Water and gas were injected into an oil‐producing reservoir, and repeat seismic surveys were collected to monitor the subsurface fluids over a period of 14 years. In this study, we show that the subresolution spatial distribution of fluids, not captured by traditional flow simulators can impact the seismic response. Although there is a good qualitative match between the fluid changes predicted by the flow simulator and the fluid changes interpreted from the seismic data, the simulator predicts smooth saturation profiles that do not quantitatively match the time‐lapse seismic changes. We find that downscaling smooth saturation outputs from the flow simulator to a more realistic patchy distribution is required to provide a good quantitative match with the near‐ and far‐offset time‐lapse data, even though the fine details in the saturation distribution are below seismic resolution. We downscaled the smooth saturations from the simulator by incorporating high spatial frequencies from well logs and constraining the saturations to the total mass balance predicted by the flow simulator. The computed seismic response of the downscaled saturation distributions matched the real time‐lapse seismic data much better than the saturation distributions taken directly from the simulator. This study demonstrates the feasibility of using seismic and well‐log data to constrain subblock saturation scales, unobtainable from flow simulation alone. This important result has the potential to significantly impact and enhance the applicability of seismic data in reservoir monitoring.
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