Resolving Reservoir Uncertainty To Create Value
Authors: Chorn L.G. , Croft Michael 
Published: June 2014

Technology application focuses on acquiring knowledge to reduce the uncertainty surrounding large capital investments in E&P. In practice, the industry makes incremental investments that exploit the increasing knowledge base for the asset, such as an exploration lease or a newly discovered field. Reservoir characterization reduces the uncertainty that surrounds development of a field by gathering and interpreting data from many investigative tools. Acquisition of that knowledge cannot be valued readily by traditional discounted-cash-flow (DCF) analysis. A new financial tool, real-options analysis, estimates the value of acquiring a knowledge base or developing a new technology.

A real-options analysis indicates that a maximum-value benefit in reducing reserves' uncertainty is a function of a project's estimated net present value (NPV), with uncertainty; characterization-analysis time; and the cost of delay.

Introduction

The need to integrate reservoir management and the data involved has changed the method of providing technical support to production operations. Technical teams of geo-scientists and engineers operate and optimize performance from oil and gas reservoirs on the basis of their understanding of reservoir architecture. Business-performance indicators drive the demand for better utilization of assets and technical staff. The proper level of reservoir knowledge is one key to optimizing these indicators.

Traditional financial tools, such as DCF, routinely under-value the impact of incremental reservoir knowledge on uncertain investments relative to what management intuitively senses they are worth.1 DCF cannot reproduce management's insight into the value of additional knowledge or improved technologies in making less risky decisions. Consequently, management usually is unable to determine quantitatively how much more knowledge or technology refinement is necessary before committing to a major investment.

Why does DCF fail to illuminate this strategic value? We believe that traditional tools do not adequately value the flexibility in investment behavior created by management's acquisition and use of new knowledge. New project knowledge allows management to be flexible with project scope, investment rate, production rates, and other such factors to accommodate the uncertainties related to price, market, and cost, in addition to those related to reserve size and distribution. As a consequence, incremental knowledge can be valued through its impact on reducing the potential for poor investment outcomes.

Mimicking Existing Investment Behavior.

Flexibility in investment behavior is the existence of options to adjust the timing and size of the investment profile as new knowledge becomes available. Economists agree that flexibility has value but that it is difficult to quantify in a manner that can guide management action. A remedy is to identify and value the outcome of an intelligent decision pathway for the project. The pathway maps an optimal sequence of choices through multiple decision points. The choices maximize the return on the investment and are based on the values of key variables at each decision point. Therefore, maximizing the return from an uncertain investment requires building flexibility into the investment program. Guidance in selecting the optimal sequence arises from knowledge available at the time of the decision. The cost of acquiring that knowledge can be viewed as the cost of an option on the investment. The value of the option is the difference between the maximized return from a flexible investment program and the return from an inflexible program constructed with only the knowledge available at the project's initiation.

The purchase of properly valued options (i.e., incremental knowledge) always contributes a positive or zero value to a project. They never subtract value. The ability to assess the value of the option and set the appropriate price is critical in determining whether to buy the option (i.e., acquire the knowledge) or forego the option and make the investment outright. This has an analog for the reservoir manager in determining the value of acquiring additional reservoir-characterization knowledge or proceeding with development on the basis of existing knowledge.

From an applications perspective, economic theories for optimizing investment behavior are problematic if they involve estimating many unknown parameters with little or no guidance. However, real-options analysis is the branch of finance theory that has made the most progress toward describing optimal behavior in investments incorporating uncertainty.2 The value and optimal exercise of a real option can be modeled in the same way as a financial option. Solutions of these problems depend on the rate at which key uncertainties are resolved and the time remaining in the option's life. Real-options analysis is valuable in improving the overall valuation exercise for projects with opportunities for management intervention that use incremental knowledge.