Permeability modeling for Enhancing Resource Utilization

Building high-quality reservoir models that integrate geological and petrophysical properties is a complex task. The primary modeling process involves creating two-dimensional maps of porosity and either absolute or effective reservoir permeability using results from well-log interpretations and laboratory measurements of core samples. Often, the petrophysical relationship between rock porosity and permeability is adjusted, and variograms used for spatial correlation are fine-tuned to reconcile with the measurements. However, such adjustments make it challenging to address significant errors in permeability, which can vary dramatically, spanning several orders of magnitude within a geological formation. In energy security and environmental conservation scenarios—such as enhanced oil recovery (EOR), shale gas production, enhanced geothermal systems, and geological CO₂ storage (GCS)—fluid injection typically results in a permeability drop of 35-86% around the injection well. This reduction can impede the injection process and lead to unnecessary remediation costs. Storage capacity, indicated by porosity, and injection efficiency, governed by permeability, are critical criteria for characterizing GCS sites. Therefore, accurate quantification of permeability is essential. Quantitative permeability modeling holds the key to unlocking the questions about fluid flow direction in hydrocarbon reservoirs, especially in the face of limited measurements from core samples or Well tests. Permeability is strongly influenced by pore-scale heterogeneities, which range from nanometers to micrometers (µm), and the evaluation of these heterogeneities varies depending on the scale considered in Euclidean geometry. This study will present a method based on scale-invariant or fractal geometry to predict reliable permeability and will validate these predictions with core-scale measurements. Additionally, the significance of permeability maps in EOR and GCS studies for forecasting fluid flow directions within a reservoir will be examined through two case studies. Finally, the discussion will include future directions for incorporating ultra-small heterogeneous effects (less than 0.1 µm), which are often overlooked due to observational and mathematical-model limitations.