The oil and gas industry has always been a competitive arena, in which handling risks effectively has now become critical for business efficiency. The effect of risks on project costs should be carefully quantified in order to implement efficient measures to mitigate these risks.
A general introduction to risk analysis for cost estimation, based on a structured approach used by many companies in the industry, is presented here. In this approach, risks are identified, quantified, and then mitigated.
The starting requirement is a project-cost estimate to be used as a baseline. This estimate will change as the project changes during its development phases. However, it will represent the most likely cost, based on the best information available.
The baseline estimate is conceived and reviewed at the project level, with issues analyzed and ranked according to their likely impact on the cost estimate. The issues identified usually represent major cost factors, such as uncertainties regarding production, schedules, and manpower, as well as market conditions regarding equipment and bulk material.
All of these issues are ranked in terms of influence on the final cost estimate, and a range is determined for each of them. The range around the base estimate represents the variation in the base cost. For each uncertain cost, a possible variation range in the base cost is established. A typical cost range (from –5% to +10%) can be modelled, as in Fig. 1.
In this case, the most likely change in cost variation is 0%. The main problem is to define the possible range of estimates provided by the risk-assessment or project team assessing project risk. There is a central-tendency effect in establishing ranges, because of conservatism at the project level. The ranges proposed tend to put the most-likely costs at the median, which can discourage the assessment of extreme scenarios. As a rule of thumb, events with 1-in-100 probability of occurrence should be taken into consideration.
To determine the effect of the risks on the total cost estimate and the range of possible uncertainties, the main tool commonly applied is the Monte Carlo simulation.
This simulation technique considers randomly and combines the effects of the different risk factors, yielding a risk-weighted cost expressed as a range.
The main results obtained have two main components: a cumulative frequency (probability) distribution (Fig. 2) that shows the range of possible costs attributable to the influence of all the possible uncertain factors considered; and the tornado chart (Fig. 3) that shows which of the different costs have more influence on the total cost estimate. These two components of the risk analysis are an invaluable tool that can be used for allocation of contingency and budget purposes.
From the cumulative frequency plot of probable cost, based upon the ranges estimated, it can be inferred that there is
The effect of the various influence factors on the total cost estimate is shown in the tornado chart. The listed factors of greatest uncertainty are power generation and chemicals cost, respectively. From the results shown in the tornado diagram, a risk-mitigation and -management plan can be developed.
The use of risk-weighted cost estimates has provided doubtless benefits to companies in the oil and gas industry. One of the main benefits is a different methodology for allocating contingencies to the project costs. Traditionally, contingencies are captured as a fixed percentage (5–10% of base project cost) added to the deterministic base estimate. The risk/cost estimate can generate contingencies that are smaller, enabling a reduction in funds allocated to a project.
In addition, the contingency obtained from a risk analysis can be used effectively as a negotiation tool for contracts. The tornado chart will help in developing risk-mitigation plans and focusing on project control.
Risk-analysis techniques also have been developed for planning purposes in terms of scheduling. The durations of activities on the critical path are analyzed, with appropriate contingencies allocated.
Structured risk analysis for cost estimation is a tool that will continue to play a key role in the management of projects and operations, especially with the increasing complexity foreseen in projects of the future.
David Alvarado is the Chief Executive Officer of Dalcor, a consultancy specializing in technical support for energy developments (including E&P and renewable-energy projects). He has worked as Technical Coordinator for Techint and as Operations Manager for Eni in Iran and Kazakhstan.
In this issue, we focus on risk management and operations readiness. The increasing complexity of field development requires a careful analysis of risks and uncertainties. David Alvarado, Chief Executive Officer, Dalcor, provides a description of a structured approach on how to handle risks and uncertainties, resulting in reduced delays and greater cost-effectiveness. In addition, my own article discusses operations readiness and assurance, a management system used in complex project environments to improve the project planning and cost control.
Francesco Verre, Editor, Economist's Corner