Dimensionless Scaling of First-Cycle Huff-n-Puff Hydrocarbon Recovery and CO2 Storage in Shale Reservoirs

Abstract Cyclic CO2 injection is the key component of carbon capture, utilization, and storage (CCUS) that enhances hydrocarbon recovery while sequestering CO2, contributing to global greenhouse gas mitigation. However, its optimization remains challenging because the process is governed by numerous interacting variables with nonlinear and competing effects, limiting the transferability of optimized parameters across reservoir systems. To address this, for the first time, this study applies dimensional analysis to identify the key dimensionless groups and establish physically interpretable scaling relations governing CO2 injection performance, enabling optimization with substantially reduced computational cost. A species-based mass transport model incorporating inhomogeneous fluid distribution induced by fluid–solid interactions is used to simulate cyclic CO2 injection and generate a comprehensive data set for dimensional analysis. Based on the Vaschy–Buckingham Pi theorem, dimensional analysis reveals key dimensionless groups governing hydrocarbon recovery (RF) and CO2 storage (EF), including response-specific Fourier numbers (FoR, FoS), diffusivity ratios (RDR, RDS), fluid–solid friction modulus (φR, φS), together with time ratio (RT), normalized drawdown pressure (PD), and relative fluid–solid interaction coefficient (χ). The RF scaling relation identifies a critical point, i.e., ψRC = 0.0015, separating mixing-dominated and mixing-limited regimes, providing a calibrated transition criterion for identifying diminishing recovery gains. The critical point ψSC = 0.0025 in the EF scaling relation marks the transition between retention-growth and retention-limited regimes, beyond which additional gains in postcycle CO2 retention diminish. This study provides practical guidance for cyclic CO2 injection in ultratight reservoirs, supporting more effective CO2 utilization for hydrocarbon recovery and improved CO2 storage performance.