Accurate dynamic reserve estimation is essential for effective reservoir development, particularly in fractured vuggy carbonate reservoirs characterized by complex pore structures, multiple spatial scales, and pronounced heterogeneity. Traditional reserve evaluation methods often struggle to account for the coupled behavior of pores, fractures, and vugs, leading to limited reliability. In this study, a modified material balance equation is proposed that explicitly considers the contributions of matrix pores, fractures, and vugs, as well as the influence of varying aquifer multiples. To validate the model, physical experiments were conducted using cores with different fracture–vug configurations under five distinct aquifer multiples. A field case analysis was also performed using production data from representative wells in the Fuman Oilfield. The results demonstrate that the proposed model achieves a fitting accuracy exceeding 94%, effectively capturing the dynamics of fractured vuggy systems with active water drive. The model enables quantitative evaluation of single-well reserves and aquifer multiples, providing a reliable basis for estimating effective recoverable reserves. Furthermore, by comparing simulated formation pressures (excluding aquifer effects) with actual static pressures, the contribution of external aquifer support to reservoir energy can be quantitatively assessed. This approach offers a practical and robust framework for reserve estimation, pressure diagnosis, and development strategy optimization in strongly water-driven fractured vuggy reservoirs.

Pressure-dependent pore-volume deformation is a critical but poorly constrained variable in dynamic reserve assessment for ultra-deep fractured-vuggy carbonate reservoirs, where fractures, dissolution pores, and vugs respond differently to effective-stress loading. In this work, a pore-structure-aware evaluation strategy was developed by integrating high-temperature and high-pressure volumetric measurements with data-driven regression. Twelve carbonate core plugs from the Ordovician Yijianfang and Yingshan formations of the Fuman Oilfield were selected to represent matrix-pore, dissolution-pore, fracture-vug, and fracture-dominated pore systems. Stepwise net-pressure experiments were performed under simulated reservoir conditions, and pore-volume compressibility (Cp) was calculated from corrected pore-volume changes. Measured C_p values reveal a distinct stress-sensitive response: C_p declines sharply during the low-net-pressure stage and then tends toward a quasi-stable level as net pressure increases, indicating progressive closure of mechanically compliant fractures, narrow throats, and weakly supported dissolution pores. Although porosity is positively associated with Cp, samples with comparable porosity display markedly different compressibility values, confirming that pore-space geometry and fracture-related compliance must be considered. Eight representative regression algorithms were then compared, using net pressure, porosity, permeability, initial pore volume, surface porosity, temperature, and a pore-structure index as model inputs. To further assess model generalization to completely unseen core plugs, additional core-ID-based leave-one-core-out (LOCO) validation was performed for k-nearest neighbors and AdaBoost. Under this grouped validation, k-nearest neighbors yielded an RMSE of 13.5978 × 10⁻⁴ MPa⁻¹ and an R² of 0.8408, whereas AdaBoost achieved an RMSE of 10.0160 × 10⁻⁴ MPa⁻¹ and an R² of 0.9136, indicating greater cross-core robustness of AdaBoost. Permutation-importance analysis of the split-specific KNN model indicated that net pressure, porosity, surface porosity, and pore-structure index made the largest predictive contributions within that model. Moreover, the predicted normalized Cp values reproduced the experimentally observed decreasing trend with increasing net pressure, supporting the physical consistency of the k-nearest neighbors predictions. The proposed experimental–machine learning framework offers a pressure-dependent method for estimating pore-volume compressibility within the geological and petrophysical domain represented by the investigated Fuman Oilfield cores, and provides more representative inputs for material-balance analysis, dynamic reserve evaluation, and production adjustment.

In the development of carbonate reservoirs via water flooding huff-n-puff, the osmotic pressure effect is frequently overlooked, and existing models inadequately quantify the matrix imbibition and oil expulsion driven by salinity gradients. To address this issue, this study establishes a coupled oil–water two-phase huff-n-puff flow model for carbonate reservoirs that incorporates the interplay between salt concentration and osmotic pressure, which, for the first time, fully couples the van ’t Hoff osmotic pressure equation with solute transport equations for fractured-vuggy carbonate huff-n-puff, filling the gap that prior tight/shale reservoir low-salinity flow models fail to adapt to cyclic injection-soaking production regimes of carbonates. Based on the IMPES (implicit pressure–explicit saturation) numerical simulation method, an equivalent single-nucleus model is adopted to characterize the fractured-vuggy reservoir architecture. The model integrates the osmotic pressure formula, solute transport equation, and two-phase seepage governing equations, enabling a systematic analysis of the mechanisms by which osmotic pressure affects the multi-stage seepage process and the influence of key parameters on development performance. Quantitative simulation reveals three core laws controlled by salinity-induced osmosis: first, osmotic pressure drives water molecules to spontaneously migrate from the high-permeability fracture inner core toward the tight matrix pores, thereby modifying the water saturation distribution, expanding the water sweep region, and smoothing the saturation gradient between the inner and outer cores, which effectively mitigates water channeling in fractured reservoirs. Under the base case (injected water salinity = 1000 mg/L, inner-core permeability = 1000 mD, shut-in time = 80 d), the oil recovery factor with osmotic pressure considered reaches 13.46%, representing a 3.50% increment over the case without osmotic pressure. The recovery factor decreases monotonically with increasing injected water salinity, while it increases with longer shut-in time and higher inner-core permeability, both exhibiting pronounced diminishing marginal returns; the optimal shut-in time is approximately 80 d under the simulated conditions. This work delivers a fully coupled numerical tool and quantitative evaluation standard for osmotic imbibition mechanisms in fractured-vuggy carbonates. The quantified recovery increment and optimal soaking window established herein can directly guide field parameter optimization of injection water salinity, shut-in cycle and fracture reconstruction scale, balancing oil increment revenue and water treatment/well shutdown operation costs for on-site low-salinity huff-n-puff design.