Handling Risk and Uncertainty in Portfolio Production Forecasting

Stochastic modeling provides a mechanism for incorporating risk and uncertainty considerations into portfolio production forecasts. Through this process, insight is gained into the likelihood of production targets being missed, met, or exceeded. This insight enables organizations to better manage operational, positioning, and strategic planning activities around stakeholders' production expectations. Inherent in all capital programs are numerous uncontrollable, but definable, factors that affect overall corporate production performance. These factors can be categorized into four groups that include

1. timing uncertainties,

2. performance uncertainties,

3. sequencing uncertainties, and

4. risk.

Timing uncertainty considers spud scheduling, spud-to-first-production cycle timing, and production ramp-up cycle timing. Performance uncertainty considers the historical or modeled distribution of period-specific production rates within the constituent plays; for example, what is the unavoidable range of variability within a play as depicted in a peak-normalized composite production plot of wells within the analogue population. Sequencing uncertainty considers performance-percentile clustering or sequencing within the program; for example, the number of top quartile wells that are, by chance, drilled early in the year versus later in the year. Finally, risk addresses commercial failure within a program attributed to either geology or execution, or both. By integrating historical operational data with a standardized set of play assessment deliverables, the building blocks of a stochastic capital program forecast and analysis are readily available. Ultimately, the use of stochastic modeling in portfolio production forecasting provides an organization's decision makers with the information necessary to examine investment and strategic decisions in the context of corporate risk tolerance.

A portfolio¹ production forecast is foundational to the strategic and operational planning activities of a company. It is a primary determinant of a cash flow forecast, which is arguably the most important consideration in strategic planning. An organization's ability to deliver its forecast production and cash flow, and therefore manage its financial obligations and capital program, however, is subject to financial, execution, and production risks and uncertainties.

To meet stakeholder² expectations, resource companies seek to manage risk and uncertainty through either mitigation or contingency measures (Smalley et. al. 2008). Examples include hedging commodity price and currency exchange rates to mitigate financial uncertainty, executing long term contracts between mid-streamers and resource companies to mitigate processing and transportation risk, and through portfolio optimization (Allan 2011) to configure optimal capital investment programs around key performance metrics. Other examples include dedicating large capital programs to select service providers in order to obtain preferred rates, guaranteed access to services, and improved operational performance, thereby mitigating execution risk associated with delivering operational results on-time and on-budget. The impact of production risk and uncertainty on an organization's strategic planning activities, however, is often poorly communicated, generally less understood, and as a result commonly receives insufficient attention at the executive level.