CO₂ saturation estimates at Sleipner (North Sea) from seismic tomography and rock physics inversion

Abstract

CO2 saturations are estimated at Sleipner using a two‐step imaging workflow. The workflow combines seismic tomography (full‐waveform inversion) and rock physics inversion and is applied to a two‐dimensional seismic line located near the injection point at Sleipner. We use baseline data (1994 vintage, before CO2 injection) and monitor data that was acquired after 12 years of CO2 injection (2008 vintage). P‐wave velocity models are generated using the Full waveform inversion technology and then, we invert selected rock physics parameters using an rock physics inversion methodology. Full waveform inversion provides high‐resolution P‐wave velocity models both for baseline and monitor data. The physical relations between rock physics properties and acoustic wave velocities in the Utsira unconsolidated sandstone (reservoir formation) are defined using a dynamic rock physics model based on well‐known Biot–Gassmann theories. For data prior to injection, rock frame properties (porosity, bulk and shear dry moduli) are estimated using rock physics inversion that allows deriving physically consistent properties with related uncertainty. We show that the uncertainty related to limited input data (only P‐wave velocity) is not an issue because the mean values of parameters are correct. These rock frame properties are then used as a priori constraint in the monitor case. For monitor data, the Full waveform inversion results show nicely resolved thin layers of CO2–brine saturated sandstones under intra‐reservoir shale layers. The CO2 saturation estimation is carried out by plugging an effective fluid phase in the rock physics model. Calculating the effective fluid bulk modulus of the brine–CO2 mixture (using Brie equation in our study) is shown to be the key factor to link P‐wave velocity to CO2 saturation. The inversion tests are done with several values of Brie/patchiness exponent and show that the CO2 saturation estimates are varying between 0.30 and 0.90 depending on the rock physics model and the location in the reservoir. The uncertainty in CO2 saturation estimation is usually lower than 0.20. When the patchiness exponent is considered as unknown, the inversion is less constrained and we end up with values of exponent varying between 5 and 20 and up to 33 in specific reservoir areas. These estimations tend to show that the CO2–brine mixing is between uniform and patchy mixing and variable throughout the reservoir.

Frequency-dependent attenuation and dispersion caused by squirt flow: Three-dimensional numerical study

“…Seismic methods are widely used for detection and characterization of fluid-saturated porous rocks (Yan et al, 2019). Many studies show that a passing wave loses energy propagating through fluidsaturated rocks (Mavko and Jizba, 1991;Dvorkin et al, 1995;Pride et al, 2004;Müller et al, 2008Müller et al, , 2010Gurevich et al, 2010;Pimienta et al, 2015aPimienta et al, , 2015b.…”

Bayesian rock-physics inversion: Application to CO2 storage monitoring

“…The parametrization and the associated geophysical observables for the monitor case (partial saturation due to the CO 2 injection) are summarized in Table 1. Part of these rock physics properties can be estimated a priori from geological knowledge, log data or baseline inversions (Yan et al, 2019) as shown in the real data application section.…”

Monitoring fluid saturation in reservoirs using time‐lapse full‐waveform inversion

“…To obtain the changes in terms of rock physics properties, full‐waveform inversion (FWI) is employed to estimate $$V_P$$ and in the next step, the estimated $$V_P$$ is inverted using rock physics inversion. For example, this two‐step procedure has been used to estimate the changes in the saturation of CO 2 at the Sleipner field in the North Sea (Queißer & Singh, 2013; Dupuy et al., 2016; Dupuy et al., 2016; Yan et al., 2019; Dupuy et al., 2021; Romdhane et al., 2022).…”