Early transient flow corresponds to the period before the effect fluid depletion has reached the nearest reservoir no-flow boundary. Production from unconventional reservoirs tends to exhibit extended periods of early transient flow because of their low permeabilities. Massive flow areas are generated, typically through the creation of multiple fractures in horizontal wells, to feasibly produce hydrocarbons from these formations at economic rates. The presence of these fractures leads to a series of non-radial flow regimes, which may continuously change before reservoir no-flow boundaries are reached, with linear flow being one of the dominant regimes. One of the significant challenges in this area has been devising a proper production analysis technique applicable to the analysis of early transient flow data. Progress has been made in the area through the use of the concept of the region of influence, which accounts for the portion of reservoir volume responsible for early transient production. In this study, we propose to implement a density-based approach to analyze early transient production data. In the density-based approach, rate-time responses of gas reservoir system are predicted by rescaling the responses of liquid system with depletion driven variables. The density-based technique has previously proven applicable to boundary-dominated radial-flow, and has been extended to analyze boundary-dominated linear-flow behavior. In this work, we show that early transient flow behaviors can be analyzed using the density-based method that incorporates region of influence concept into rescaling variables, λ¯-β¯ calculations. A density-based procedure is proposed to analyze early transient production data and its applicability is verified using simulated rate-time data. Results show that the proposed method can effectively predict Contacted Gas In-Place and the fracture half-length and square root of permeability product. The density-based methodology provides an alternative and reliable means to model and analyze data from gas reservoirs exhibiting extended early transient production.
All Science Journal Classification (ASJC) codes
- Renewable Energy, Sustainability and the Environment
- Energy Engineering and Power Technology