Multi-Segmented Drainage Volume Analysis and Forecasting with Parent-Child Interactions

Dynamic drainage volume (DDV) in unconventional reservoirs can be estimated from diffusive time-of-flight analysis using well rates and pressures. However, in multistage fractured horizontal wells, production is often influenced by inter-well communication, particularly frac-hits from child well completions near parent wells. These events can significantly alter well productivity, making accurate detection and quantification essential for performance monitoring, forecasting, and optimization. This paper presents a hybrid, physics-informed, data-driven approach—multi-segmented dynamic drainage volume (ms-DDV)—to continuously estimate DDV in the presence of well interference and forecast its impact on well performance. The ms-DDV approach extends single-well DDV calculations to handle performance discontinuities by segmenting the drainage volume evolution and applying a hybrid SINDy (Sparse Identification of Nonlinear Dynamics) framework. This method automatically detects events such as frac-hits, refracs, or stimulations, quantifies their effects on drainage volume, reservoir pressure, and productivity index (PI), and uses the latest segment for accurate condition-based forecasting. Field case studies demonstrate the method's capability to assess both positive and negative impacts of interference events, enabling reliable PI-based rate forecasts and dynamic inflow performance relationship (IPR) computations. By combining the rigor of physics-based modeling with the adaptability of data-driven techniques, ms-DDV offers a robust, field-proven tool for interpreting frac-hit impacts and integrating these insights into production optimization workflows across U.S. onshore basins.