Full waveform inversion combining rock physics for seismic reservoir characterization and monitoring

Qi Hu

Quantitative estimation of rock physics properties, such as porosity, lithology, and fluid saturation, is an important part of reservoir characterization. Most current seismic workflows in this field are based on amplitude variation with offset (AVO). Full waveform inversion (FWI) methods, although computationally more complex than AVO approaches, can produce more accurate elastic models by extracting the full information content in the seismogram. Progress has been reported in using elastic FWI results as intermediate quantities to derive rock properties from seismic data. However, the question of whether FWI can be geared towards the direct determination of rock physics properties remains open. In this thesis, I formulate FWI with rock physics model parameterizations to directly estimate parameters of immediate interest in reservoir characterization. This approach allows examination of any rock physics property that has a well-defined relationship with elastic parameters. It also shares the same numerical structure as the conventional elastic FWI, allowing various existing inversion strategies to be used. The reliability of the approach is systematically examined using different synthetic examples and is quantified by comparing it to conventional two-step inversions. Building on this approach, I formulate a time-lapse FWI framework for quantitative seismic monitoring of CO2 storage. The method is tested on synthetic data generated for the Johansen formation model. The results demonstrate this approach's robustness for retrieving static properties, such as porosity and mineral volumes, and dynamic reservoir properties, such as CO2 saturation. Moreover, with a joint rock physics model combining Gassmann’s equation with empirical pressure relations, I illustrate the potential of this approach for the simultaneous prediction of CO2 saturation and pore pressure. Finally, I apply a sequential inversion scheme combining elastic FWI and Bayesian rock physics inversion to a vertical seismic profile (VSP) dataset acquired with accelerometers and a collocated distributed acoustic sensing (DAS) fiber at the Carbon Management Canada’s Newell County Facility. The inverted porosity and lithology models are reasonably accurate at the well location and are geologically meaningful in spatial distribution. This baseline (before injection) study can be used to support later monitoring of CO2 storage.