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Bayesian Inference In CO2 Storage Monitoring: A Way To Assess Uncertainties In Geophysical InversionsGreen Open Access

Authors: B. Dupuy, A. Romdhane and P. Eliasson
Event name: Fifth CO2 Geological Storage Workshop
Session: Poster Session 3
Publication date: 21 November 2018
DOI: 10.3997/2214-4609.201803005
Organisations: EAGE
Language: English
Info: Extended abstract, PDF ( 1.67Mb )

We present an integrated methodology for quantitative CO2 monitoring using Bayesian formulation. A first step consists in full-waveform inversion and CSEM inversion solved with gradient-based inverse methods. Uncertainty assessment is then carried out using a posteriori covariance matrix analysis to derive velocity and resistivity maps with uncertainty. Then, rock physics inversion is done with semi-global optimisation methodology and uncertainty is propagated with Bayesian formulation to quantify the reliability of the final CO2 saturation estimates.

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