This paper describes the development and application of a methodology to screen and rank Dutch reservoirs suitable for long-term large scale CO₂ storage. The screening focuses on off- and on-shore individual aquifers, gas and oil fields. In total 176 storage reservoirs have been taken into consideration: 138 gas fields, 4 oil fields and 34 aquifers, with a total theoretical storage potential of about 3200 Mt CO₂. The reservoirs are screened according to three criteria: potential storage capacity, storage costs and effort needed to manage risk. Due to the large number of reservoirs, which limits the possibility to use any pair-wise comparison method (e.g. Multi-Criteria programs such as Bosda or Naiade), a spreadsheet tool was designed to provide an assessment of each of the criteria through an evaluation of the fields present in the database and a set of scores provided by a (inter)national panel of experts. The assessment is sufficiently simple and allows others to review it, re-do it or expand it. The results of the methodology show that plausible comparisons of prospective sites with limited characterization data are possible.

Large-scale deployment of carbon capture and storage needs a dedicated infrastructure. Planning and designing of this infrastructure require incorporation of both temporal and spatial aspects. In this study, a toolbox has been developed that integrates ArcGIS, a geographical information system with spatial and routing functions, and MARKAL, an energy bottom-up model based on linear optimization. Application of this toolbox led to blueprints of a CO₂ infrastructure in the Netherlands. The results show that in a scenario with 20% and 50% CO₂ emissions reduction targets compared to their 1990 level in respectively 2020 and 2050, an infrastructure of around 600 km of CO₂ trunklines may need to be built before 2020. Investment costs for the pipeline construction and the storage site development amount to around 720 m€ and 340 m€, respectively. The results also show the implication of policy choices such as allowing or prohibiting CO₂ storage onshore on CO₂ Capture and Storage (CCS) and infrastructure development. This paper illustrates how the ArcGIS/MARKAL-based toolbox can provide insights into a CCS infrastructure development, and support policy makers by giving concrete blueprints over time with respect to scale, pipeline trajectories, and deployment of individual storage sites.

Large-scale implementation of carbon capture and storage needs a whole new infrastructure to transport and store CO₂. Tools that can support planning and designing of such infrastructure require incorporation of both temporal and spatial aspects. Therefore, a toolbox that integrates ArcGIS, a geographical information system with elaborate spatial and routing functions, and MARKAL, an energy bottom-up model based on linear opt imization has been developed. Application of this toolbox for devising blueprint s of a CO₂ infrastructure in the Netherlands, shows that early knowledge on the availability, potential, and suitability of sinks is of major importance for a cost-effective design of the infrastructure.

This paper describes the development and application of an methodology to screen and rank Dutch reservoirs suitable for longterm large scale CO₂ storage. The screening is focused on off- and on-shore individual aquifers, gas and oil fields. In total 177 storage reservoirs have been taken into consideration (139 gas fields, 4 oil fields and 34 aquifers, with a total storage potential of about 3200 Mt CO₂). These reservoirs have been selected from over five hundred potentially suitable CO₂ storage reservoirs. The total number of storage reservoirs has been reduced by applying preconditions with associated threshold values. Nevertheless, the number of reservoirs is still significant and limits the possibility to use any pair-wise comparison method (e.g. Multi-Criteria programs such as Bosda or Naiade). Therefore, a excel tool has been developed based on linear aggregation. The tool screens the reservoirs based on three criteria: storage potentials, costs and effort needed to manage risk.