Abstract

Risk management, risk analysis, and uncertainty analysis are still-growing trends in cost and schedule estimating. Engineers and managers alike have been lead to believe that correct application of best practices will ensure that operations achieve their objectives on time and within budget.

Unfortunately, a number of misapplications, misunderstandings, and mistakes have threatened to endanger the continued useful growth of this trend. Insufficient tools and / or incorrect use of the available tools have allowed creation of a false sense of security which is shattered by loss of objectives and time / cost overruns. It is very important that the industry understands and chooses the correct applications, and has realistic expectations.

This paper will present best practices for applying risk management, risk analysis and uncertainty analysis to capital expenditure cost and schedule estimates. In addition to outlining our recommended process, we will highlight current misapplications that, in our opinion, are potential barriers to the continued growth of this valuable management tool.

Introduction

The oilfield industry is, by its very nature, an industry that contains many uncertainties (unknown variables) and risks (things that can go wrong). Many companies, albeit to varying degrees and with varying degrees of success, are currently applying risk management, risk analysis, and uncertainty analysis for their cost and schedule estimating, particularly for drilling and completion operations and facilities in upstream oil and gas operations.

The paper will begin with a brief review of the background to risk management, risk analysis, and uncertainty analysis. It will then detail best practices covering risk and uncertainty for cost and schedule:

• Identification – the who and the how

• Rating and ranking – what is important, how to carry it into quantitative analysis

• Probabilistic estimating for times and cost – the ranges that can be expected

• Mitigation methodologies – how to reduce the impact of unwanted events.

Background of Risk Management, Risk Analysis and Uncertainty Analysis

Risk and uncertainty identification, risk and uncertainty analysis, and decision analysis are all integral to any responsible and respectable risk management process. A thorough risk management process combines two defined forms - qualitative analysis and quantitative analysis.

Qualitative risk analysis defines and frames the scope of further analysis by providing context of a scenario or story. Furthermore, qualitative risk analysis includes methods for prioritizing the risks for action. It is a necessary pre-requisite for quantitative risk analysis.

Quantitative risk and uncertainty analysis can further be subdivided into deterministic methods, such as decision trees or risk matrices, and stochastic methods, such as Monte Carlo simulation. Quantitative risk analysis analyzes the effects of the prioritized risks and values assigned to them. As reported and illustrated in the literature[1,2], the preferred method of Monte Carlo simulation helps to:

• assess the probability to achieve project objectives,

• identify realistic and achievable cost, schedule and scope targets,

• determine the apparent best project decision when some conditions or outcomes are uncertain.

Best practices require the earliest possible identification of risk / uncertainty and their cataloging in a risk register. This register is then continuously added to as the project commences through the concept to definition and finally planning phase. Simple registers, built in spreadsheet format, can be readily assessed and ranked. In this manner the design and planning decisions as well as quantitative analysis can focus on the ones that have the most impact.