A Modern Approach to E&P Asset Valuation, Development, and Decision Making

Abstract

The development of an oil and gas asset can be one of the most capital-intensive endeavors in the modern business world. The largest energy industry projects may require more than U.S. $15 billion in capital spending. While oil and gas assets normally have long economic lives, they have been characterized historically by low rates of return in comparison with endeavors in other industries. According to a recent report by Goldman Sachs, major oil company properties have an average life span of 21 years, but pay only 10% cash return on capital invested. This level of performance can be attributed to two major challenges faced by nearly all recent E&P projects. First, most include substantial elements of risk and uncertainty, in terms both of commodity prices and estimates of subsurface hydrocarbon reserves and performance. Highly publicized write-downs of booked reserves illustrate the difficulties E&P companies face in this area. The second major challenge is that conventional tools and techniques are unable to model all components of the production system simultaneously—from the subsurface upward through the wells, pipelines, and other surface facilities—across the entire productive life of an asset. Hence, engineers can create and evaluate no more than a handful of potential development scenarios, thus often resulting in suboptimal decisions. Traditionally, E&P companies resort to modeling each component of an asset—the subsurface, surface facilities, and economic outcomes—individually. At the end of this long, tedious process, they combine all the results, hoping they will represent the behavior of a fully integrated asset, which is rather questionable. Alternatively, they may simplify an integrated asset model to a point at which it can be evaluated as a single entity, which makes an accurate representation of predicted vs. actual returns somewhat risky. Both of these approaches evolved 30 to 40 years ago within major oil companies. They were strongly influenced by the hierarchical corporate structures of those days, as well as the limited computational and storage capabilities available at the time. Because most oil and gas companies have been evolving rapidly toward asset-centered organizations, and because dramatic advancements have been made in cost-effective computational power and storage, the methodologies and tools for E&P asset valuation and decision making must be revolutionized to keep pace. Otherwise, the energy industry could squander its most precious resources at a time when global demand is going nowhere but up.