Using fiber-optic cables as distributed sensors to monitor the subsurface is one of the fastest growing acquisition technologies in the hydrocarbon energy sector. Since the first exploration and production downhole field trial of a Distributed Acoustic Sensing (DAS) system for seismic monitoring in 2009, the technology has boomed. It has already proven to be an effective tool for acquiring vertical seismic profiles (VSP), performing passive interferometric measurements, and monitoring of microseismic earthquakes. DAS cables record seismo-acoustic wavefields and ground motions because ground-motion-induced changes in strain on the fiber affect the phase of back-scattered light in the fiber. Commercially available systems already provide sub-meter spatial resolution in sensing fibers up to 50 km in length with a frequency response up to several kHz. This exceeds the frequency range and spatial coverage of conventional seismic sensors. As a result, surface and borehole monitoring with DAS in addition to traditional sensors will most likely form a central component of future Measurement, Monitoring and Verification (MMV) systems for CO2 storage. DAS, however, does possess some key disadvantages in that it only provides a single component measurement which is most sensitive to motions in line with the fiber. DAS also measures linear strain rather than particle motion, meaning the recorded signals are not directly comparable to conventional sensors. In order to better understand the response of DAS it is therefore necessary to understand the seismic source, path, site and instrument effects. The ACT DIGIMON project aims to develop and demonstrate an affordable, flexible and societally embedded Digital Monitoring early-warning system, for monitoring CO2 storage sites. Within the DIGIMON concept fiber-optic monitoring will form a key component, therefore a thorough understanding of the response of DAS systems, including the transfer function, is a fundamental issue to be addressed. In this paper we present our modeling approach for the DAS response for a fictive CO2 storage site. The workflow exploits geometrical models of different complexity which in the end are representative of North Sea geology. Using ray tracing techniques and the seismic waveform modelling packages: SW4 and SPECFEM3D, we were able to analyze and compare these modeling approaches in relation to the response of a DAS system. With varying model complexity, we accurately capture and analyze the DAS response for realistic cable geometries. These geometries represent both vertical and horizontal deployments, which replicate fiber placed in wells and deployed on the seabed and or in shallow trenches.