Moving Toward an Optimal and Automated Geospatial Network for CCUS Infrastructure

Abstract

Modifications in the global climate are being driven by the anthropogenic release of greenhouse gases (GHG) including carbon dioxide (CO2) (Middleton et al. 2014). CO2 emissions have, for example, been directly linked to an increase in total global temperature (Seneviratne et al. 2016). Strategies that limit CO2 emissions—like CO2 capture, utilization, and storage (CCUS) technology—can greatly reduce emissions by capturing CO2 before it is released to the atmosphere. However, to date CCUS technology has not been developed at a large commercial scale despite several promising high profile demonstration projects (Middleton et al. 2015). Current CCUS research has often focused on capturing CO2 emissions from coal-fired power plants, but recent research at Los Alamos National Laboratory (LANL) suggests focusing CCUS CO2 capture research upon industrial sources might better encourage CCUS deployment. To further promote industrial CCUS deployment, this project builds off current LANL research by continuing the development of a software tool called SimCCS, which estimates a regional system of transport to inject CO2 into sedimentary basins. The goal of SimCCS, which was first developed by Middleton and Bielicki (2009), is to output an automated and optimal geospatial industrial CCUS pipeline that accounts for industrial source and sink locations by estimatingmore » a Delaunay triangle network which also minimizes topographic and social costs (Middleton and Bielicki 2009). Current development of SimCCS is focused on creating a new version that accounts for spatial arrangements that were not available in the previous version. This project specifically addresses the issue of non-unique Delaunay triangles by adding additional triangles to the network, which can affect how the CCUS network is calculated.« less