Carbon capture and storage (CCS) is an important technology that mitigates the effect of climate change. It involves the capture of CO2 from flue gas, transporting it through pipelines, and storing it underground in geological reservoirs. The characterization of the properties of geological reservoirs (i.e., storage capacity and flow rate limit) are subject to uncertainties. These uncertainties affect the planning of CCS systems, especially in determining which CO2 sources are to be matched with geological sinks subject to capacity and injectivity constraints. In this study, a Neutrosophic Linear Programming (NeLP) model is developed for optimal planning of CCS systems considering these uncertainties modeled as neutrosophic sets. The model involves taking into account the degree of satisfaction when minimizing risks, the degree of dissatisfaction when overestimating storage parameters, and the degree of indeterminacy when defining accurate storage site parameters. A case study will be used to illustrate the model. The model was able to generate insights as to how much CO2 must be injected into the geological reservoir to minimize the risks arising from uncertainty. The total CO2 stored in geological reservoirs varies from one risk behavior to another.