The transition to a low-carbon economy necessitates effective carbon capture and storage (CCS) solutions, particularly for hard-to-abate sectors. Herein, pipeline networks are indispensable for cost-efficient transportation over long distances. However, there is deep uncertainty regarding which industrial sectors will participate in such systems. This poses a significant challenge due to substantial investments as well as the lengthy planning and development timelines required for pipeline projects, which are further constrained by limited upgrade options for already built infrastructure. The economies of scale inherent in pipeline construction exacerbate these challenges, leading to potential regret over earlier decisions. While numerous models were developed to optimize the initial layout of pipeline infrastructure based on known demand, a gap exists in addressing the incremental development of infrastructure in conjunction with deep uncertainty. Hence, this paper introduces a novel optimization model for pipeline infrastructure development, minimizing regret as its objective function and incorporating various upgrade options, such as looping and pressure increases. The model's effectiveness is also demonstrated by presenting a comprehensive case study of Germany's cement and lime industries. The developed approach quantitatively illustrates the trade-off between different options, which can help in deriving effective strategies for infrastructure development.