Combined geophysical and rock physics workflow for quantitative CO2 monitoring

Safe CO2 storage requires conformance verification, i.e. confirmation that the pressure and CO2 accumulation are consistent with modelling forecasts within a given uncertainty range. Quantitative estimates of relevant reservoir parameters (e.g. pore pressure and fluid saturations) are usually derived from geophysical monitoring data (e.g. seismic, electromagnetic and/or gravity data) and potential prior knowledge of the storage reservoir. We describe a two-step strategy combining geophysical and rock physics inversions for quantitative CO2 monitoring. A Bayesian formulation is used to propagate and account for uncertainties in both steps. We demonstrate our workflow using datasets from the Sleipner CO2 storage project (Norwegian North Sea) and combining seismic Full Waveform Inversion and rock physics inversion. We derive rock frame properties from baseline data and use them as input to obtain 2D spatial distribution of CO2 saturation with uncertainty assessment from monitor data. We also discuss the need for advanced rock physics models, considering the way fluid phases are mixed (uniform to patchy mixing) and the trade-off effects of pore pressure and fluid saturation on geophysical measurements. We consequently recommend a joint rock physics inversion approach, where multi-physics, and multi-parameter inversion can be used for better discrimination of pressure, saturation, and fluid mixing effects towards more quantitative conformance verification.

Automated summary

This study presents a two-step strategy combining geophysical and rock physics inversions for quantitative CO2 monitoring, using a Bayesian formulation to account for uncertainties. Demonstrated using data from the Sleipner CO2 storage project, the workflow involves deriving rock frame properties from baseline data and obtaining a 2D spatial distribution of CO2 saturation with uncertainty assessment. The study also highlights the need for advanced rock physics models and the recommendation of a joint rock physics inversion approach for better conformance verification.