Diagnostic fracture injection tests (DFIT's), or "mini-fracs" are often used to gauge many reservoir and fracture design parameters. However, DFITs are not always conducted in conjunction with the main completions work. This paper proposes a novel workflow to determine the instantaneous shut-in pressure (ISIP) from readily available completions data. This is a valuable parameter in itself as related to the least principal in-situ stress states as demonstrated by the stress change relationships near faults in Lavoie et al. (2018).
Directly using completions data from fracture stimulation operations, the authors have leveraged on the water-hammer signature in bottom-hole pressure data during completions to process the ISIP for each completions stage. Within this study, completions data from ~2100 stages from ~300 horizontal Montney formation wells were analyzed. A MATLAB script was used to automate the derived ISIP stress trends over the Montney formation and to deduce the ISIP in a consistent format.
This novel workflow also validates the expected in-situ stress trends at depth, with a relationship of high ISIP gradients closer to fault zones similar to stress change behaviour as shown in Lavoie et al. (2018). Specifically, a positive spatial relationship was observed pertaining to local ISIP gradients, the lithostatic gradient, the minimum in-situ stress, and the propagation of hydraulic fractures that are prone to reactivation of critically stressed faults. Based on our real-time observations, field operators may allow to flowback a well for a short amount of time to deplete the anthropogenic reservoir pressure and stress shadowing prior to resuming fracture stimulation.
Considering the continued push for higher fluid and sand loading in industry in the development of unconventional assets as an economic driver, there also exists a large and tangible corporate citizenship opportunity of mining real time completions dark data with the possibility of relating that live feed as a prescriptive tool to mitigate reactivation of critically stressed faults. This case study focuses on the Montney formation as a basis for processing easily available data from standard operations in an effort of systematically designating areas prone to seismicity risk in future hydraulic fracturing operations based on automated real-time analytics of dark data.