This study integrates field data, numerical simulations, and analytical derivations to study production interference testing in shale. First, we investigate the Chow Pressure Group (CPG) technique, and: (a) explain why the CPG has a qualitative association with the strength of production interference, (b) assess the conditions under which the CPG reaches a stable long-term plateau during the typical duration of a test, and (c) if it does, explain whether this plateau has a physical interpretation. Next, we study the Devon Quantification of Interference (DQI) technique, and: (a) use the ‘two-well’ Degree of Production Interference (DPI) metric to derive a relationship for a ‘uniform-spacing’ DPI that is applicable for a well bounded on both sides, and (b) develop a procedure to calculate a generalized DPI that accounts for arbitrary gun-barrel configurations, spatially variable fracture conductivity, and anisotropy. The new generalized DPI technique is validated by applying to a field dataset where extended shut-ins (2+ days) were performed months after the interference tests, allowing independent assessment of the interference test interpretations. The generalized DPI procedure: (a) provides fracture conductivity measurements that can be used in general-purpose reservoir engineering calculations, and (b) enables rapid ‘what-if’ analysis to test the economic impact of modifying well configuration.
Interference tests are used to inform well spacing decisions in shale. When a well is put on production, pressure is measured in one or more offset wells and analyzed to assess the strength of the hydraulic connection. If tests are performed at different distances, it is possible to estimate the relationship between spacing and connectivity.
The Chow Pressure Group (CPG) technique is commonly used to interpret interference tests. The CPG is a metric related to the power-law scaling of ΔP (the pressure change caused by the offset production) with respect to time. The CPG concept first was applied to rate-transient analysis (RTA) by Chu et al. (2017) as an empirical way of describing trends that exhibit deviation from linear flow. Subsequently, Chu et al. (2020) showed that the CPG metric can be applied to analyze interference tests. Lower values of CPG (0-0.4) indicate weak interference and higher values (greater than 0.7) indicate strong interference.
Almasoodi et al. (2023) introduced the ‘Devon Quantification of Interference’ (DQI) method. In this procedure, the initial pressure response at the monitoring well is matched with the solution to the 1D diffusivity equation, as observed from an offset location. The match is used to estimate hydraulic diffusivity, which is then used to calculate fracture conductivity. Finally, the conductivity is used to estimate the ‘degree of production interference’ (DPI), a metric that quantifies the amount of production loss at the monitoring well caused by the offset well.
