Speaker
Description
The resistivity index (RI) is a key parameter that describes how a rock’s electrical resistivity varies with changes in fluid saturation. Electrical conduction within porous media is primarily controlled by the presence and distribution of conductive fluids such as water. When non-conductive fluids like oil or gas occupy the pore spaces, these conduction pathways are disrupted and, as water saturation decreases,
resistivity typically increases. Thus, the RI serves as a crucial link between electrical resistivity measurements and fluid saturation, enabling more accurate evaluation of fluid distribution within a reservoir. An equally important factor influencing resistivity behavior is rock wettability, which determines the rock’s preference for contact with either water or hydrocarbons. It governs how fluids occupy the pore spaces and therefore directly affects the connectivity of the conductive water phase. Any change in wettability can significantly alter the shape and slope of the RI–Saturation curve and consequently, accounting for different wettability conditions is essential when interpreting resistivity data or estimating the RI–Saturation relationship numerically.
In this work we incorporate wettability effects for more reliable reservoir characterization from well logs and improvement of fluid saturation and distribution evaluations. We implemented a robust numerical simulation framework to calculate RI-Saturation curves for digital rock samples. This framework incorporates a methodology that
accounts for the presence of water films at the rock – oil interface, providing a more realistic representation under partially saturated conditions. The water films are numerically introduced into the pore structure of the digital rock models, and their electrical behavior is modeled using a conductivity relation, which links film conductivity to film thickness and water conductivity. Fluid distributions corresponding to each saturation state are generated using morphological methods that simulate imbibition and drainage processes. Different wettability states are modeled by varying the contact angle within the morphological algorithms and by adjusting the water film thickness according to the specified wetting condition. Contact angles between 0° and 60° represent water-wet to mixed-wet systems, while water films are omitted entirely in oil-wet simulations.
Simulated resistivity index curves for digital sandstone samples under water-wet conditions showed close agreement with experimental measurements, yielding a saturation exponent of approximately n = 2. For other wettability states obtained by varying the contact angle, the calculated saturation exponents exhibited systematic variations consistent with empirical trends reported in the literature. As wettability shifted from water-wet to mixed- and oil-wet conditions, RI curves became steeper and displayed higher resistivity at equivalent water saturations, indicating reduced connectivity of the conductive water phase.
Our findings demonstrate that incorporating different wettability states of the rock matrix into the numerical framework provides a more comprehensive understanding of RI behavior. By explicitly modeling how wettability influences fluid distribution and electrical conduction, this approach enables a more reliable evaluation of the uncertainty associated with RI measurements. This methodology extends beyond conventional resistivity modeling by linking pore-scale wettability effects to
macroscopic electrical responses, offering a novel pathway for improved reservoir characterization and saturation estimation.
| Country | Brazil |
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