In this study, we integrated numerical modeling and field data to investigate several topics related to Rate-Transient Analysis (RTA) in unconventional wells. First, we tested the accuracy of conventional RTA techniques against synthetic data generated by an integrated hydraulic fracturing and reservoir simulator. As expected, pseudopressure adjustments were able to account for sources of nonlinearity such as multiphase flow and pressure-dependent permeability, and they yielded accurate estimates for the linear flow parameter (LFP), fluid in place, and permeability. Two different methods of estimating permeability were assessed, and one proved much more robust than the other. Second, we evaluated whether to perform the analysis with respect to total fluids or with respect to the primary hydrocarbon phase. Results suggest that in some datasets, performing the analysis with respect to total fluids will better capture the character of the RTA transient. The ‘total fluids’ approach is valuable if linear flow at early time is distorted by changing water cut during early production. Third, we investigated the effect of finite fracture conductivity on RTA behavior. In theory, RTA can be used to identify finite fracture conductivity from the y-intercept on a reciprocal productivity index plot. However, in practice, a clearly discernible y-intercept will only be evident if the conductivity is exceptionally low. Otherwise, the y-intercept can be obscured by the ambiguity created by pressure charging from the hydraulic fracturing treatment. With realistic fracture conductivity values, the fracture is finite conductivity, and yet, in many cases, a y-intercept is not clearly discernable. Fourth, we investigated how to diagnose reservoir behaviors from RTA and GOR plots. Drawing on results from simulations, we made schematic diagrams showing RTA and GOR trends under different conditions. These guidelines can be used for engineering diagnosis of subsurface processes and to guide history matching procedures.
Rate-transient analysis (RTA) integrates production and pressure data to quantify well productivity and infer reservoir properties. In this study, we used numerical simulation and field datasets to investigate several topics related to RTA interpretation. Analysis was performed on both: (a) simplified ‘synthetic’ scenarios and (b) simulations based on detailed history matches to historical data (previously presented by Singh et al., 2025, and Morsy et al., 2025). The RTA results were compared with the ‘known’ values from the simulations to evaluate accuracy and to address practical questions regarding the interpretation procedure.
This paper focuses on RTA techniques utilizing pseudopressure/time corrections. In recent years, ‘numerical RTA’ methods have become popular (Bowie and Ewert, 2020). These techniques are more general than classical pseudopressure techniques but are largely based on similar assumptions. Therefore, the results in this paper can be viewed as applicable to either classical or numerical RTA techniques.