Carbon capture and storage (CCS) demonstration projects are exposed to a unique and complex set of risks due to high capital investment costs, unpredictable political incentives and novel technology. Deadlines for start-up may be attached to public funding and can create incentives for projects to deviate from a commercial investment model and accept higher risks early in the project.

A study has investigated the risk management implications for a hypothetical CCS demonstration project that is designed to represent key features of real world projects. The demonstration project is obliged to begin operation by the end of 2015 in order to secure some degree of public funding. The main challenge facing the project at the beginning of 2010 is that the qualification of a suitable geological storage site is not complete and three candidate sites remain to be characterised in detail. The risk of missing the project deadline is analysed.

The opportunity to reduce the deadline risk by increasing the schedule overlap between capture and transport engineering and storage site qualification is explored through the modelling of an alternative front-loaded case. The increased exposure this approach may create to not finding adequate CO₂ storage reserves is studied in the context of the storage site qualification process described in the CO2QUALSTORE joint industry guideline, and now also in the EU’s CCS Directive guidance documents.

Approach
Schedule risk is defined as the effect of uncertainty on schedule objectives (ISO 31000, 2009). In the example project presented, the schedule risk is measured against the planned target date for the start of CO₂ storage operations. The risk modelling for the schedule risk analysis undertaken for the example project was done using the Monte Carlo schedule simulation tool Primavera Risk Analysis (PRA).
The schedule risk analysis included uncertainty related to:

• Storage site qualification risks - uncertainty regarding the CO₂ storage potential of a candidate site cannot be reduced to zero prior to the start of operations and this risk is normally dealt with by assessing a portfolio of screened and short-listed candidates (leads or prospects) until one or a combination prove adequate.

• Other major schedule risks - where identified based on experience from related projects and indications of problems that could be encountered in ongoing CCS projects.

• Unspecified risks (estimate uncertainty) - each activity has specified a general uncertainty in the duration estimate. This is to account for the aggregated upside and downside effects of unspecified risks.

The schedule risk analysis undertaken for the example project followed the steps below:

1. Establish a high level activity network for the generic project with base case assumptions for activity durations, dependencies and target dates;
2. Identify major risks relative to base case and quantify the effect on the plan in terms of probability of occurrence and the extent of delays if occurring;
3. Quantify any additional uncertainty (often referred to as estimate uncertainty) in activity durations due to the aggregated effect of unspecified risks (both upside and downside);

4. Simulate the schedule in order to estimate a probability distribution for when the “Start operation” milestone is accomplished. The schedule risk is given by the planned target date relative to this distribution.
   From this distribution, several risk metrics can be derived, including the probability of meeting a planned target date and the worst case scenario for when a milestone may be accomplished.

CCS project case study assumptions
The example chosen for this high-level study is a commercial-scale, integrated capture-transport-storage demonstration project to be added on to an existing coal-fired power station. Feasibility studies and storage-site screening are assumed to have been completed prior to 2010 and the deadline for the start of operations is set as the end of 2015 (defined funding requirement). The following assumptions are made:

• Three candidate storage sites have been short-listed by a site-screening process (A, B, C) prior to 2010. All three sites require further site investigation in order to qualify sufficient storage reserves (enough capacity at the required rate and with secure containment);
• The project will make use of only one storage site (not a combination) and each site is judged to have a 50% chance of successful qualification. Thus, the probability of one of the three sites succeeding is 87%;
• The storage-site qualification process will focus on investigating sites A, B and C in turn and in this order until one of the sites is able to fulfil the qualification criteria;
• The sequence of activities within the storage sub-project is derived from the project-development model presented in the CO2QUALSTORE guideline;
• The sequence of activities within the capture and pipeline sub-projects is based on normal engineering practice;

• The basic duration of each activity has been chosen to broadly represent industry norms within civil engineering and upstream oil and gas exploration operations.

Results
The results for the base case and frontloaded case models are presented in Figure 1. These results show the estimated probability distribution of the example project beginning CO₂ storage operations by specific dates. The optimistic, expected and pessimistic dates for beginning CCS operations in the front-loaded and base case models were found to be:

• Optimistic: March 2014 vs. April 2015;
• Expected (statistical mean): April 2016 vs. May 2017;
• Pessimistic: February 2020 vs. May 2021.

Figure 1: Results of a simulation of the base case (left) and front-loaded case (right) models showing the probability of the example project beginning CO₂ storage operations by specific dates.

The modelling shows that the front-loaded case model has approximately a 50% probability of beginning operations by the end of 2015, whereas the base-case model has approximately a 5% probability of meeting the same deadline.

The overall schedule uncertainty is dominated by the impact of qualification and other major risks. This is illustrated in Figure 2 for the base-case model.

Figure 2: Results of a simulation of the base case model showing the contributions from risk events and the general estimate uncertainty to the overall schedule uncertainty.

A ranking of the individual risks is indicated in Figure 3, based on changes in the completion date when risks are successively removed from the model. The most significant risks in this example are:

• Storage site qualification (exploration) risk;
• Public and NGO opposition to the storage site;
• Underestimation of the storage site exploration and appraisal (qualification) schedule.

Figure 3: Results of a simulation of the base case model showing the ranking of the underlying drivers based on the expected bringing forward of the completion date when risks are successively removed from the model.

Conclusion
The case study described in this article shows that a CCS project developer can reduce the deadline risk substantially by concentrating more of the capture plant and pipeline engineering activities and costs in the early period of the project. The probability of the base case and frontloaded models meeting the 2015 deadline was found to be approximately 5% and 50% respectively.

However, the front-loaded approach does not allow for full qualification of a storage site before starting these activities and increases the project funds put at risk prior to the full qualification of a storage site. In this case study, there is a 13% probability of losing early investment costs because none of the candidate storage sites proves adequate for qualification (irrespective of front-loading).

In deciding on the project development approach, the project developer has to answer the following question: is the funding tied to the 2015 deadline greater than the cost of qualifying a storage site? If the
amount of public funding tied to the 2015 deadline is greater than the site qualification costs, the front-loaded case would offer the lowest overall risk profile in this example.

It is noted that finding the balance between deadline risk and site qualification risk for a real project would require the careful modelling of project activities and costs to a greater level of detail than discussed in this hypothetical example. In addition, the base case and front-loaded models in this study have been parameterised to represent end members of a site qualification risk spectrum. In reality, the extent to which capture and pipeline costs should be moved prior to final site qualification will depend on:

• The technical dependencies within and between the capture, transport and storage sub-projects (greatly simplified in this example);
• A detailed risk analysis to quantify project risks in a meaningful way and find the optimum trade-off between deadline risk and site qualification risk;

• An iterative qualification process that can provide an increasing level of confidence in CO2 storage reserves and therefore timely decision support for project investments.