We have developed a generalisable machine learning framework for reservoir quality prediction in deeply buried clastic systems. Applied to the Lower Jurassic deltaic sandstones of the Tilje Formation (Halten Terrace, North Sea), the approach integrates sedimentological facies modelling with mineralogical and petrophysical prediction in a single workflow. Using supervised Extreme Gradient Boosting (XGBoost) models, we classify reservoir facies, predict permeability directly from standard wireline log parameters and estimate the abundance of porosity-preserving grain coating chlorite (gamma ray, neutron porosity, caliper, photoelectric effect, bulk density, compressional and shear sonic, and deep resistivity). Model development and evaluation employed stratified K-fold cross-validation to preserve facies proportions and mineralogical variability across folds, supporting robust performance assessment and testing generalisability across a geologically heterogeneous dataset. Core description, point count petrography, and core plug analyses were used for ground truthing. The models distinguish chlorite-associated facies with up to 80% accuracy and estimate permeability with a mean absolute error of 0.782 log(mD), improving substantially on conventional regression-based approaches. The models also enable prediction, for the first time using wireline logs, grain-coating chlorite abundance with a mean absolute error of 1.79% (range 0–16%). The framework takes advantage of diagnostic petrophysical responses associated with chlorite and high porosity, yielding geologically consistent and interpretable results. It addresses persistent challenges in characterising thinly bedded, heterogeneous intervals beyond the resolution of traditional methods and is transferable to other clastic reservoirs, including those considered for carbon storage and geothermal applications. The workflow supports cost-effective, high-confidence subsurface characterisation and contributes a flexible methodology for future work at the interface of geoscience and machine learning.

Grain-coating chlorite preserves porosity and permeability through the inhibition of quartz cement whereas pore-filling chlorite blocks pore-throats and diminishes reservoir quality. The aim of this study is to determine the origin and principal mechanisms which govern the distribution of grain-coating and pore-filling chlorite in Jurassic deltaic sandstones (Tilje Formation, Smørbukk field, Mid Norwegian Shelf). The study focussed on very high-density sampling for petrographic analysis, from three sections of sandstone core from the same well with contrasting reservoir quality, rather than the low-density sampling approach typically employed. The aim was to gain new understanding of specific controls on porosity and permeability based on core description, core analysis measurements and a suite of petrographic techniques. Results of this study show grain-coating chlorite originated from the thermally-driven recrystallisation of detrital clay coats and/or clay mineral precursors. Pore-filling chlorite has principally derived from the ductile deformation of chlorite-rich Fe-ooids, that were possibly reworked from a proximal evaporitic setting. The distribution of chlorite precursor material, detrital clay coats, and subsequently the distribution of grain-coating and pore-filling chlorite, were controlled by the relative dominance of tidal and fluvial processes active during sediment deposition. Optimum grain-coating chlorite is found in tidal-fluvial sandstones with moderate fluvial influence. Pore-filling chlorite is pervasive in tidal-fluvial channel sandstones deposited during periods of high fluvial discharge, or proximal to the central turbidity maximum zone; marked by an abundance of fluid mud. Tidal channel sandstones with no fluvial influence are pervasively quartz cemented due to an absence of grain-coating chlorite. Grain-coating chlorite and good reservoir quality occurs in heterolithic distributary mouth bar sandstones, however mixing of mud- and sand-prone facies due to intense bioturbation has reduced permeability. Results from this study can be used to predict reservoir quality in the Smørbukk field and in analogous shallow-marine sandstones worldwide.