When it comes to forecasting production from shale plays that are subject to multistage hydraulic fracturing, most modeling approaches do not apply throughout the life of a well. The Duong decline method, introduced in 2010, is no exception. When a well reaches the stage of boundary-dominated flow (BDF), the method's limitations become clear.

Part 2 of the Duong method proposes to extend the approach in order to apply it to the long-term performance of wells that are influenced by various fracture fabrics, well spacing, and fluid types such as gas and saturated and unsaturated oil production. In addition to overcoming its own limitations, the extended method is also intended to rectify limitations associated with other commonly used production forecasting methods. The outcome of this work should generate a model that accounts for the physical processes of flow regimes in horizontal wells with multistage hydraulic fracturing.

This extension employs empirical, analytical, and numerical solutions to represent a depletion model that consists of multiple realistic flow regimes. The method uses the Duong diagnostic plot, log(q/Gp) versus log(t), to normalize the constant rate and constant pressure analytical solutions during both linear flow and BDF. This forms an equivalent Fetkovich-type curve for unconventionals and serves as the base curve for identifying the start time of fracture interference among the fractures and in connection with the Arps' b values. Results from numerical simulation modeling are used to fill in long-term production estimates affected by various fracture geometries, well drilling spacing units, and fluid types. Type-curve parameters include start fracture interference time and fluid influx ratio for each depletion system. The fluid influx ratio based on permeabilities, fracture distance and half-length, and well spacing ranges from zero to one, where zero represents an isolated system and one represents transient conditions.

The outcome of this work should help the industry not only to forecast rate production more accurately, but to better understand decline prediction in tight oil and shale gas reservoirs. The paper also discusses methods to estimate input parameters for forecasting, using factors such as permeabilities, fracture interference time, stimulated-rock volume (SRV), and fracture half-length from production history and completion data. The paper applies field and simulation data to demonstrate the use of the new extension.

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