Wettability evaluation of hydrocarbon-bearing shales: A review of methods, controlling factors, and application

Evaluating wettability in hydrocarbon-bearing shales poses significant challenges due to their fine-grained structure, heterogeneous mineralogy, and intricate pore-fracture networks. This paper reviews the wettability testing methods, influencing factors, and wettability characteristics of hydrocarbon-bearing shales from different sedimentary facies. The main results include: (1) Although analytical methods such as contact angle, spontaneous imbibition, nuclear magnetic resonance, calorimetry, electron microscope, etc. have been employed, a universally accepted standard remains elusive. The oft-cited neutral wettability, indicating both hydrophilic and hydrophobic characteristics, is highly variable and influenced by the intrinsic shale properties and experimental uncertainties. (2) Shale wettability is governed by the matrix composition, surface functional groups, and microstructural features, as well as by the physical and thermodynamic properties of interacting fluids, including formation water and hydrocarbons. Geological factors, such as tectonic burial, diagenetic evolution, thermal maturation, and hydrocarbon generation, further complicate wettability characteristics. Shales from different sedimentary facies display marked differences: marine shales are predominantly affected by organic pore development and mineral composition; transitional shales by inorganic pore-fractures and organic matter type; and lacustrine shales by inorganic pore-fracture systems and mineralogy characteristics. (3) The complex fluid–solid interactions within multi-scale pore networks dictate heterogeneous wettability, which in turn influences hydrocarbon distribution, retention, and migration. Future studies should focus on in-situ wettability characterization under reservoir conditions (T&P conditions, fluid property, etc.), dynamic wettability near wellbores, and the effects of external fluid intrusion to enhance predictive models and optimize hydrocarbon extraction strategies.