This paper presents a simple yet rigorous model and provides a methodology to analyze production data from wells exhibiting three-phase flow during the boundary-dominated flow regime. Our model is particularly applicable to analyze production data from volatile oil reservoirs, and should replace the less accurate single-phase models commonly used. The methodology will be useful in rate transient analysis and production forecasting for horizontal wells with multiple fractures in shales. Our analytical model for efficiently handling multi-phase flow is an adaptation of existing single-phase models. We introduce new three-phase parameters, notably fluids properties. We also define three-phase material balance pseudotime and three-phase pseudopressure to linearize governing flow equations. This linearization makes our model applicable to wells with variable rates and flowing pressures. We optimized the saturation-pressure path and further suggested an appropriate method to calculate three-phase pseudopressures. We validated the solutions through comparisons with compositional simulation using commercial software; the excellent agreement demonstrated the accuracy and utility of the analytical solution. We concluded that, during the boundary-dominated flow regime, the saturation-pressure relation given by steady-state path and tank-type model for volatile oil reservoirs leads to satisfactory results. We also confirmed that our definitions of three-phase fluid properties are well suited for ultra-low permeability volatile oil reservoirs. The computation time of our model is greatly reduced compared to a numerical approach, and thus the methodology should be attractive to the industry. Our model is efficient and practical to be applied for production data analysis in ultra-low permeability volatile reservoirs with non-negligible water production during the boundary-dominated flow regime. This study extends existing analytical model methodology for volatile oil reservoirs and is relatively easy for reservoir engineers to understand.

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