Accurate cost estimates are critical for making informed investment decisions. The more defined a project’s design scope is, the more refined the financial assessment can be. However, a project begins its lifecycle as an initial idea with an undefined scope and the opportunity for broad deviation from basic concept; how do we ensure financial viability of a project during these early phases?
This article will outline some rules-of-thumb for project economics in the oil and gas or specialty chemicals industries. We will consider AACE International’s standardised CECS framework, with a particular focus on lower-definition classifications, Classes 4 and 5.
Order of Magnitude (AACE Class 5)
Class 5 is the lowest level of project definition, often referred to as order of magnitude and useful for high-level strategic planning. At this level, the project is not yet defined in any detail, the level of accuracy is usually within ± 30% to ± 50% of the actual cost. The following rules of thumb can be applied:
Total project cost is 3 – 5 times the cost of major equipment required
Piping is 10% - 30% of the cost of major equipment required
Instrumentation and control systems are 5% - 15% of the total project cost
The cost of site preparation and civil work is 10% - 20% of the total project cost
The accuracy of these rules of thumb is dependent on several factors such as a project’s location, its complexity, and market conditions.
Preliminary Estimate (AACE Class 4)
Class 4 is the second-highest level of project definition, used for feasibility studies when a concept is being considered with a little more detail. The level of accuracy for the estimate is usually within ± 15% to ± 30% of the actual cost. Rules of thumb appropriate for this class may include:
Analogy – predicting the cost based on similar projects which have been completed prior. An example could be the power law:
Where k is a quantity based on expert judgement. A typical value of k = 0.6, often referred to as the six-tenths rule, is often a good starting point.
Parametric models – predicting the cost based on the contributions of multiple cost drivers. For example:
Where a and b are quantities typically derived from historical data and expert judgement. The values vary widely based on the type of equipment or process being evaluated and the parameters being considered.
Equipment-factored – multiplying the cost of major equipment items by a factor that accounts for the auxiliary equipment, installation, and indirect costs associated with that equipment. Typically expressed as:
Common equipment factors are often based on capacity, material of construction, pressure rating, corrosion allowance, number of trays or packing, rotating machinery type, heat exchanger surface, and shape inclusive.
Lower classes in the framework require increasing detail, where rules of thumb are no longer appropriate. Class 3 is often based on front end engineering design (FEED) involving semi-detailed unit costs with assembly-level line items; the natural conclusion to FEED is the final investment decision – the point at which the design, cost and complexity are well-enough understood to recommend committing to, or abandoning, the capital project. Class 2 and Class 1 require detailed material take-off lists and apply to bids, tenders, and check estimates.
In conclusion, while accurate cost estimation is crucial to any project's success, determining the most appropriate method for getting an idea off the mark can be challenging. It is possible to achieve a reasonable cost estimate using the methods outlined for Class 4 and 5 projects. Early engagement with a specialist can also help develop the scope and refine the budget through front end engineering design, and throughout the project delivery.
Further reading and references:
AACE International. (2018). AACE International Recommended Practice No. 18R-97: Cost Estimate Classification System - As Applied in Engineering, Procurement, and Construction for the Process Industries.
Towler, G., & Sinnott, R. (2013). Chemical Engineering Design: Principles, Practice, and Economics of Plant and Process Design. Elsevier.
Peters, M. S., Timmerhaus, K. D., & West, R. E. (2003). Plant Design and Economics for Chemical Engineers. McGraw-Hill.
Lang, H. J. (2012). Chemical process equipment: selection and design. Butterworth-Heinemann.
Ulrich, G. D., & Vasudevan, P. (2004). Chemical engineering process design and economics: A practical guide. Process Publishing.
