The objectives of this paper are to summarize effective Reserves estimation methods for use in unconventional reservoirs, and to propose systematic procedures for classification of Resources other than Reserves (ROTR) volumes. We propose optimal timing for application of decline curve analysis (DCA), rate transient analysis (RTA), and reservoir simulation. Using these techniques, we provide results for one well from a 38-well database in the Permian Basin wells (TX USA). We then describe how the volumes are classified and categorized and how those volumes move between Reserves and ROTR as more information becomes available.

We begin with the analysis of well performance, where we specify the information that is necessary for each estimation method. We then suggest procedures to identify the flow regimes using diagnostic plots, provide guidance on the application of multi-segment DCA models, and finally suggest procedures for the application of RTA and reservoir simulation. We continue with progress toward Reserves classification, starting with suggested procedures to reclassify Prospective Resources as Contingent Resources (upon discovery). We provide post-discovery guidance on development and commerciality for the project maturity sub-classes (within the Contingent Resources classification). We explain that “established technologies” must be technically and economically viable before they can be used for development decisions. And finally, we examine requirements to remove contingencies so that the volumes can be reclassified properly as Reserves.

Our major suggestions for well performance analysis are, first, that the multi-segment DCA approach is most effective in unconventional reservoirs when specifically relevant models are used for transient flow and boundary-dominated flow. Furthermore, we suggest that RTA using analytical models expands possibilities of forecasting for changes in well conditions and for well spacing studies. Though time and computationally time consuming, compositional simulation is required for confident analysis of near-critical reservoir fluids.

For movement of resources toward Reserves, we suggest that there is no linear path to define the movement from Prospective to Contingent Resources, though there are certain criteria which must be met for a given project. Certain contingencies, such as price of oil and available technologies, dominate the classification of resource volumes.

This paper provides a visual representation of when to use each Reserves estimation method depending on available data. We present a thorough analysis of best practices for each Reserves estimation method. We provide graphical representation of the movement between Prospective to Contingent Resources categories, the progression in chance of development and commerciality within project maturity sub-classes for Contingent Resources, and the contingencies that must be resolved to move from Contingent Resources to Reserves. Finally, we present an explanation of the criteria that must be met before volumes can be reclassified and/or recategorized from undiscovered to discovered.

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