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\section{Introduction}   Measurements, monitoring and verification (MMV) of geological CO$_2$ storage are essential components for ensuring storage integrity and social acceptance of Carbon Capture and Storage (CCS), which are needed for the deployment of the technology at a scale that will have an impact on climate change. Also, in a carbon market context, appraisal and verification of stored CO$_2$ should be integrated components of CCS projects. As such, monitoring programs of CO$_2$ injection should ultimately allow for the quantitative estimation of CO$_2$ saturation in the reservoir. Geophysical methods are challenged in this respect, and multi-method approaches should be favored. To date, seismic methods remain the principal geophysical method of all monitoring programs. Indeed, seismic methods were shown to be efficient for MMV due to their high resolution and their sensitivity to porosity and fluid saturation \citep{White2013a,Lumley2010a,Lumley2010,Carcione2006}. Nevertheless, ambiguity in seismic data interpretation occurs due competing pressure and saturation effects, consecutive to relatively small changes in seismic properties at mid to large CO$_2$ saturations. Gravity monitoring could be helpful for mass balance estimation, especially if downhole gravimeters can be positioned close to the reservoir \citep{dodds13}. Electrical methods can also play an important role due to insensitivity the very low sensitivity  of electrical properties to pressure effects. Nevertheless, seismic methods will always play a central part in CO$_2$  monitoring programs due to their high resolution compared to other geophysical methods. Since 2008, the INRS  CO$_2$ research chair granted by the Minist\`ere du D\'e\-ve\-loppe\-ment durable, de l'Environnement et des Parcs du Qu\'ebec, studies the feasibility of geological storage of CO$_2$ in the province of Quebec, Canada. As part of the research program of the Chair, an assessement of the performance of seismic monitoring is carried out for in the particular context of the St. St.\  Lawrence Lowlands. The Cambrian-Ordovician sedimentary basin of the St. St.\  Lawrence Platform in southern Quebec has been identified as the most prospective basin in the province of Quebec for CO$_2$ storage \citep{Malo2012}. The Becancour region is located on the south shore of the St. St.\  Lawrence River, midway between Montr\'eal and Quebec City (Fig.~\ref{fig:fig1}). The B\'e\-can\-cour region region's  deep saline aquifers were selected as a potential target for injection of CO$_2$ in a future pilot project, based on seismic reflection and well log data available from gas exploration, and based on  the proximity of an industrial zone emitting up to 1 Mt of CO$_2$ per year. The success of the storage depends on the capability to monitor movements of the injected gas into the subsurface. As in all current CCS projects, seismic methods are an important component of the monitoring program at B\'ecancour. In such projects, prior estimation of elastic property changes in response to the injection of CO$_2$ is crucial to perform a proper monitoring and subsequent interpretation of the time-lapse seismic data. There is thus a growing mandatory  need to understand how injected CO$_2$ influence seismic response and how seismic methods could get a reliable quantitative estimates of injected CO$_2$ \citep{White2013}. The aim of this study is to better understand the dependance of the seismic properties on the porosity, mineralogy and pore fluid of the B\'e\-can\-cour reservoir through both laboratory measurements and numericalseimic  modeling. In this contribution, we presents first a set of laboratory measurements of the $P$- and $S$-wave velocity and amplitude made  on the sandstones two sandstone samples  of the target reservoir reservoir,  fully saturated with CO$_2$ at different temperatures and pressures. The results of this experiments are then used to build a geological model and generate synthetic seismograms reproducing th forcasting the response to  CO$_2$ injection in the reservoir fromations.