Finding the best drilling locations in an extensive shale play holding is key to achieving production profile expectations and good economic metrics. Shale plays have been described as statistical plays. However, it becomes increasingly unacceptable to drill disappointing, underperforming wells as the operator and partners move from the exploration lifecycle stage into the appraisal and field development stages.The physical and chemical properties of shales dictate the economic success of development drilling programs. It is recognized that at least seven parameters must fall within empirically-determined ranges for a play to have economic production rates and estimated ultimate recovery (EUR) exceeding threshold internal rate of return (IRR) requirements.A geostatistical shale property workflow that high-grades 160-acre sections in a regional shale play, using a limited number of wellbores with standard logging suites is demonstrated. This paper extends the workflow from high-grading drilling targets to quantitative risk assessment. An application of the workflow to a multi-square mile U.S. shale play illustrates the analysis and its interpretation. The example shows that down-spacing well density in high-graded sections (high potential reward) is a quantitatively lower risk investment program than would normally be expected. Typically high reward opportunities, in the investment world, are expected to represent higher risk as well. Geostatistical analysis in the example play shows just the opposite behavior because the statistical nature of the local shale quality can be mapped and profitably drilled.Exploiting this geostatistical, high-grading workflow can accelerate an operator's development program with higher rewards, lower risk, and better rates of return than pursuing a uniform development program over a large regional play.

Portfolio theory requires the decision maker to associate a project's reward potential with its risk profile to characterize its contribution to an investment program. Reward and risk must be quantified in a manner that enables comparison across the set of investment alternatives to ensure that the capital allocation process is optimized. This quantification becomes difficult when the opportunity set contains very different investments, such as an offshore oil field, an oil sands project expansion, and a refinery upgrade. The risk components are different for each, and the rewards have different time horizons. Nevertheless, the risks and rewards for these types of investment opportunities are clear and can be modeled using historical information and experience.Many companies have added shale plays to their investment portfolio, mixing one or more shale plays into an opportunity set. The risk and rewards of shale plays are gradually being understood. However, the ability to predict the economic performance in terms of production rate and reserve addition is not a science. Controllable and uncontrollable risks impact the expected reward. Controllable risks are quantifiable; however, uncontrollable risks, critical shale properties' distribution within the play and their effect on production, remain unpredictable before appraisal drilling.Evaluating shale play investments as part of a portfolio requires quantifying both types of risk. Uncontrollable risks require new methods and insights to understand and quantify. Key shale property distribution prediction, coupling well logs with geostatistics, enables the quantification of uncontrollable risks in a shale play investment. The method quantifies relations between key shale properties and well performance to improve predrilling production forecasts. This paper addresses the method's application within and between shale plays to optimize capital allocations. This enables senior management to deliver production growth, cash flow, net present value (NPV), and reserve replacement, within capital constraints, from a portfolio comprising shale assets.