Stochastic Inversion‐Driven Petrophysical Modelling in Sub‐Tuning Reefal Carbonates: Soğucak Formation, Thrace Basin, Türkiye

ABSTRACT Seismic inversion plays a critical role in populating subsurface properties into geomodel; however, its effectiveness is often constrained by the resolution limits of seismic data. This study evaluates the effectiveness of stochastic versus deterministic acoustic‐impedance inversion for estimating total porosity ( Φ total ), effective porosity ( Φ e ) and permeability ( K ) in the complex reefal carbonates of the Soğucak formation, Deveçatağı oil field—northwestern Thrace Basin, Türkiye—whose thickness ranges from 2 to 57 m. The wedge model indicates a tuning thickness of 60 m in Soğucak formation which limits the vertical resolution of the deterministic inversion that directly affects the geomodel resolution. To address this challenge, a stochastic inversion was performed to resolve beds below the tuning thickness, using a high‐resolution 1 millisecond (ms) vertical sampling grid and producing non‐unique, fine‐layered impedance realizations. Petrophysical relationships were established using 75 core plugs showing strong porosity–permeability trends that were cross‐validated with wireline logs. These relationships were applied to acoustic‐impedance volumes derived from both deterministic and stochastic inversion. Correlations at well locations used in the model are naturally higher due to constraints from acoustic‐impedance logs; therefore, we emphasized blind‐well correlations to assess predictive performance at locations without well control. Blind‐well tests at W‐2, W‐4, W‐6 and W‐11 demonstrate valid predictive capability, with stochastic inversion achieving correlations of 0.65–0.73 compared to 0.45–0.52 for deterministic inversion, effectively resolving sub‐tuning thickness beds and reliably predicting porosity and permeability. By overcoming the resolution limitations of deterministic inversion, stochastic inversion supported by robust petrophysical relationships—when applicable—provides a reliable and field‐proven tool that can be adapted to carbonate reservoirs in diverse geological settings worldwide.