Illustration of workflow of the prediction of reservoir models based on data assimilation of previous reservoir models and Bayesian inversion of rock physics models.

Project Description

This project is developing and validating an integrated package of joint seismic-pressure-petrophysics inversion of a continuous active-source seismic monitoring dataset capable of providing real-time monitoring of a carbon dioxide (CO₂) plume during geologic carbon storage. The resulting real-time map of CO₂ saturation obtained using this process will provide a deeper understanding of the complex, time-varying dynamics of the subsurface fluid flow migration path, as well as the rapid detection of potential CO₂ leakage.

Project Benefits

The proposed methodology will provide an advanced CASSM data processing tool for continuously monitoring and quantifying CO₂ saturation, and predicting the migration pathways of the CO₂ plume before costly leaks occur. The integrated seismic-petrophysical inversion results from the Bayesian approach will not only provide better estimates of CO₂ saturation but also quantify the limits of detection and thresholds of uncertainty. The use of data assimilation for seismic inversion will make the prediction of the CO₂ plume independent of the campaign deployment of seismic sources. “Real-time” ability of delineating CO₂ plume boundaries and quantifying CO₂ saturation using seismic-petrophysics data should allow DOE’s investment in future monitoring systems to be incorporated without the expensive and personnel-intensive effort of independent inversions.

Presentations, Papers, and Publications

• Integration of Seismic-Pressure-Petrophysics Inversion of Continuous Active-Seismic Monitoring Data for Monitoring and Quantifying CO2 Plume (Aug 2018)
  Presented by Tieyuan Zhu, Penn State University, 2018 Carbon Storage and Oil and Natural Gas Technologies Review Meeting, Pittsburgh, PA

Contact Information