CO2 Saturation and Thickness Prediction from 4D Seismic Data at Snřhvit Field

Osdal, B.; Zadeh, Hossein Mehdi; Johansen, Ståle Emil; Gilding, D. T.

doi:10.3997/2214-4609.20130854

Cited by 2 publications

(2 citation statements)

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“…Nakatsuka et al (2009) estimated CO 2 saturation from resistivity, and emphasized that the approach is valuable for CO 2 saturation above a certain threshold, where the seismic methods lack resolution. Osdal et al (2013) predicted CO 2 saturation and thickness in the Stø Fm. at the Snøhvit field by comparing synthetic seismic and time-lapse seismic.…”

Section: Introductionmentioning

confidence: 94%

“…Changes in fluid saturation and pore pressure, and geomechanical changes in the reservoir, are most frequently observed. Time-lapse seismic methods are used to monitor CO 2 injected in saline aquifers, and give a good understanding of the plume migration and CO 2 saturation (Arts et al, 2004;Chadwick et al, 2006;Osdal et al, 2013). Numerous studies have quantified the CO 2 injected at the Sleipner field.…”

Section: Introductionmentioning

confidence: 99%

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CO2 saturation and thickness predictions in the Tubåen Fm., Snøhvit field, from analytical solution and time-lapse seismic data

Grude¹,

Landrø²,

White

et al. 2014

International Journal of Greenhouse Gas Control

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a b s t r a c t CO 2 migration in a saline aquifer is governed by viscous, capillary and gravitational fluid forces at an early stage of injection, where the dominant flow regime is site specific and controls the fluid migration in the pore space. This study combines the CO 2 saturation inverted from time-lapse seismic methods with an analytical expression to define the CO 2 flow regime, saturation distribution and layer thickness in the Tubåen Fm. following CO 2 injection. Quantitative estimates of the CO 2 saturation from time-lapse seismic amplitude versus offset (AVO) and spectral decomposition are compared to a viscous dominated analytical expression of CO 2 injection into a saline aquifer. The spatial extent of the CO 2 plume obtained from time-lapse spectral decomposition and inverted from time-lapse AVO analysis display good agreement with the analytical expression. The CO 2 is limited to an area close to the injection well, with an elongated shape in the channel direction. Comparison between the time-lapse seismic and analytical expression shows that the fluid flow is dominated by viscous forces. CO 2 saturation within the plume is constant and close to the residual brine saturation. The influence of gravity is ignorable on the reservoir CO 2 flow. CO 2 fills the entire sandstone unit up to approximately 50 m away from the injection before the CO 2 layer thickness is reduced to a thin wedge that propagates below the overlying shale unit. Reduction in CO 2 saturation away from the injection well is a reduction in effective CO 2 saturation relative to the thickness of the horizon. The maximum radius of the CO 2 layer from the analytic expression is 750 m, of which 400 m is above the time-lapse noise level. Time-lapse seismic analysis reveals the CO 2 layer radius is 405 m in the direction of the local fluvial channel and 273 m in the perpendicular direction.

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Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

CO2 saturation and thickness predictions in the Tubåen Fm., Snøhvit field, from analytical solution and time-lapse seismic data

Grude¹,

Landrø²,

White

et al. 2014

International Journal of Greenhouse Gas Control

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Estimation of CO ₂ saturation maps from synthetic seismic data using a deep-learning method with a multi-scale approach

Pantaleo,

Molossi,

Pipan

2024

Geoenergy

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In the context of Carbon Capture and Storage (CCS), monitoring the behaviour of CO 2 within subsurface reservoirs is pivotal for efficient and safe storage operations. This study proposes a new approach to enhance the accuracy of predicting CO 2 saturation maps directly from shot gathers, using a combination of deep learning (DL) and feature extraction methods. We employ a U-Net model, specifically tailored to solve regression tasks, and two-dimensional continuous wavelet transform (2D-CWT) to analyse shot gathers at different scales. We introduce a novel approach using multi-channel input data for the DL model, combining shot gathers and CWT images. The DL model was trained and tested using both single channel and multichannel input. The single channel datasets included shot gathers and CWT images at the first scale, while the multi-channel datasets integrated shot gathers with either two or four scales of CWT. We conducted a sensitivity analysis on the number of training epochs to compare the performance of the model with multichannel and single channel input. Additionally, a Transfer Learning approach was implemented to improve performance in noisy conditions by leveraging knowledge from a pre-trained model on noise-free images. Monte Carlo dropout was used to predict pixel-scale variability and provided a prediction variability with a standard deviation ranging from 0.019 to 0.194, enhancing the robustness of CO 2 saturation estimates. Our results suggest that combining feature extraction using 2D-CWT with the U-Net architecture improves the prediction performance of CO 2 saturation in a synthetic CCS model. Additionally, using multi-channel input instead of single channel is more efficient as it requires less training and prediction time to achieve comparable results. This confirms the effectiveness of 2D-CWT as a pre-processing technique, contributing valuable insights and advances in the field of data-driven geophysical inversion problems.

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CO2 Saturation and Thickness Prediction from 4D Seismic Data at Snřhvit Field

Cited by 2 publications

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CO2 saturation and thickness predictions in the Tubåen Fm., Snøhvit field, from analytical solution and time-lapse seismic data

CO2 saturation and thickness predictions in the Tubåen Fm., Snøhvit field, from analytical solution and time-lapse seismic data

Estimation of CO ₂ saturation maps from synthetic seismic data using a deep-learning method with a multi-scale approach

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CO2 Saturation and Thickness Prediction from 4D Seismic Data at Snřhvit Field

Cited by 2 publications

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CO2 saturation and thickness predictions in the Tubåen Fm., Snøhvit field, from analytical solution and time-lapse seismic data

CO2 saturation and thickness predictions in the Tubåen Fm., Snøhvit field, from analytical solution and time-lapse seismic data

Estimation of CO 2 saturation maps from synthetic seismic data using a deep-learning method with a multi-scale approach

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Estimation of CO ₂ saturation maps from synthetic seismic data using a deep-learning method with a multi-scale approach