![]()
Abstract Over $300 billion of value has been destroyed in US shale gas development since 2006 due to companies underperforming expectations. For resource sector investments to perform at expectation, even when budgeted capital and commodity pricing expectations are met, there is a fundamental need for forecasted production targets to be met. Meeting production targets is primarily reliant on basing capital programs on drilling inventories that are unbiased and meaningfully characterized.
Significant work has been conducted over the years on how best to represent well performance expectations associated with undeveloped inventories. Where corporate production forecasts often fail, however, is in adopting inventory characterizations (i.e., type wells, success rate expectations) that are too broad or overly biased. As such, a methodology is herein presented referred to as Risked Inventory Characterizations (RICs) that incorporates isoprobability mapping of Key Success/Failure (KSF) play attributes and risked economics into the characterization of an inventory. In the workflow, producing wells are normalized for exploitation intensity (i.e., stage spacing, proppant loading, lateral length) and subdivided into populations based on similar well performance attributes (i.e., IP, GOR, EUR). These well populations are next spatially examined (i.e., areally and stratigraphically) for controlling geological attributes (i.e., KSFs). Once identified, the limits of these Geologically Relevant Areas (GRAs) are mapped using isoprobability contours of the KSFs. An example includes the possible geographic placements of where the 7 meter net pay and 10 ohm resistivity contours could occur in a play where these attribute cutoffs are determined to be the thresholds below which the associated type curve no longer applies.
The presented workflow not only considers uncertainty ascribed to well performance (i.e., P10/50/90 type wells), but also "mapping" uncertainty ascribed to subsurface data density (e.g., well and seismic control, open hole log suite completeness) and data quality (e.g., borehole condition effects on log suite, acquisition parameter effects on seismic). Beyond ESG (Environmental Social Governance) considerations, broad investment in the oil and gas sector is not likely to return until companies consistently demonstrate an ability to deliver meaningful returns to investors. Meanwhile, a KSF isoprobability-based approach to inventory characterization offers oil and gas sector stakeholders a mechanism to optimize capital programs around annual production addition expectations, heighten assurances around delivering economic returns, and evaluate and compare undeveloped assets in a way that fully incorporates risk and uncertainty considerations into inventory valuations.
Site News