Unsupervised Classification of Flow Regime Features in Pressure Transient Responses

Pressure transient analysis (PTA) is a standard tool for interpreting reservoir response in well pressure to production and injection operations and characterizing reservoirs in subsurface engineering. It involves studying flow regimes and the associated pressure changes to extract information about well and reservoir parameters. New opportunities to support reservoir decision-making have opened with more abundant availability of PTA data. A wide deployment of permanent downhole gauges (PDG) in wells provided the wealth of high-frequency data for PTA and has encouraged researchers to explore the integration of PTA into current well monitoring and reservoir evaluation and modelling techniques.

This paper describes an automated method designed and developed to detect and classify reservoir flow regime features using pressure transient data obtained from production and injection wells. The proposed is focused on feature recognition model and solving the optimization problem for pattern classification. The method is applied and validated on real field data. The method presented in this study demonstrated a high level of accuracy, successfully identifying flow regime features with an 89% success rate based on a single pressure transient within the chosen real well dataset.