Rate-transient analyses (RTA) is a useful reservoir/hydraulic fracture characterization method that can be applied to multi-fractured horizontal wells (MFHWs) producing from low permeability (tight) and shale reservoirs. In this paper, a recently-developed three-phase RTA technique is applied to the analysis of production data from a MFHW completed in a low-permeability volatile oil reservoir in the Western Canadian Sedimentary Basin.
This new RTA technique is used to analyze the transient linear flow regime for wells operated under constant flowing bottomhole pressure conditions. With the new method, the slope of the square-root-of-time plot applied to any of the producing phases can be used to directly calculate the linear flow parameter, xf√k, without defining pseudo-variables. The method requires a set of input PVT data and an estimate of two-phase relative permeability curves. For the field case studied herein, the PVT model is constructed by tuning an equation of state (EOS) from a set of PVT experiments, while the relative permeability curves are estimated from numerical model history-matching results.
The subject well, a MFHW completed in 15 stages, produces oil, water and gas at a nearly constant (measured downhole) flowing bottomhole pressure. This well is completed in a low-permeability, near-critical volatile oil system. For this field case, application of the new RTA method leads to an estimate of xf√k that is in a close agreement (within 7%) with the results of a numerical model history-match performed in parallel. The RTA method also provides pressure-saturation relationships for all three phases that are within 2% of those derived from the numerical model. The derived pressure-saturation relationships are central to the use of other RTA methods that require calculation of multi-phase pseudo-variables.
The new three-phase RTA technique developed herein is a simple-yet-rigorous and accurate alternative to numerical model history-matching for estimating xf√k when fluid properties and relative permeability data are available.