Monte Carlo Simulation: Its Status and Future
Authors: Murtha James A. 
Published: June 2014

Distinguished Author Series articles are general, descriptive representations that summarize the state of the art in an area of technology by describing recent developments for readers who are not specialists in the topics discussed. Written by individuals recognized as experts in the area, these articles provide key references to more definitive work and present specific details only to illustrate the technology. Purpose: to inform the general readership of recent advances in various areas of petroleum engineering.

Introduction

Monte Carlo simulation is a statistics-based analysis tool that yields probability-vs.-value relationships for key parameters, including oil and gas reserves, capital exposure, and various economic yardsticks, such as net present value (NPV) and return on investment (ROI). These probability relationships help the user answer such questions as "What is the probability that the NPV of this prospect will exceed the target of $1,500,000?" or "How likely is it that the reserves added from this year's exploration program will fall short of our planned production? "Monte Carlo simulation is a part of risk analysis and is sometimes performed in conjunction with or as an alternative to decision [tree] analysis.

Putting aside for the moment a description of Monte Carlo simulation, the method has attracted its share of critics over the years. Their comments include "I did this in FORTRAN in 1964, It just never caught on. "; "Why not just add or subtract 10% to the base case?" ; "The answer is whatever you want it to be. "; "The answer depends on who is doing the simulation. "; "Garbage in, garbage out. "; "You never have enough data" ; "A black box, hocus-pocus, that's all it is, "; and "It takes too long to run enough cases. "To some degree, the critics have been silenced by the evolution of virtually universal spreadsheet programs, much faster computers, and relatively simple software to run simulation and process data. Nonetheless, we will address some of the underlying concerns, but it is necessary to lay some foundation first.

Our objectives are (1) to define Monte Carlo simulation in a more general context of risk and decision analysis; (2) to provide some specific applications, which can be interrelated; (3) to respond to some of the criticisms; (4) to offer some cautions about abuses of the method and recommend how to avoid the pitfalls; and (5) to predict what the future has in store.

What Is Risk Analysis?

Although the word "risk" occurs with great regularity these days in the petroleum literature, it has not always been fashionable. In its 60-pageSubject Index, the 1989 printing of the 1,727-page Petroleum Engineering Handbook contains just one reference to "risk [factor]" in an article about property evaluation.

Among the numerous words and phrases associated with risk analysis are decision analysis, risk assessment, risk management, portfolio management and optimization, and strategic planning. In some contexts, these words are used only in a qualitative sense, but our focus is quantitative.

Decision analysis, in its broadest form, includes problem identification, specification of objectives and constraints, modeling, uncertainty analysis, sensitivity analysis, and rules that lead to a decision. Generally speaking, risk analysis and assessment refer to the quantification of uncertainty, almost always in the context of possible investments. In the oil and gas business, although much of the analysis might pertain to reserve size, capital cost, production forecasting, and the like, the bottom line universally is monetary value.

Risk management connotes a second stage, where the investors seek protection from unfavorable situations; i.e., they work to mitigate the risks. Thus, turnkey contracts, guarantees, insurance, locked-in prices, and hedges are instruments of risk management.

A portfolio is an aggregation of investments. Portfolio managers mix their prospects to reduce collective risk and enhance ROI. Optimization is often taken as maximizing some measure of reward, such as NPV or profit-to-investment ratio, subject to constraints on risk. Strategic planning involves portfolio management but may include more intangible aspects of investments, such as the advantage of having a presence in a country.