Quantifying subresolution saturation scales from time‐lapse seismic data: A reservoir monitoring case study

Abstract

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.