Microporosity is commonly assumed to be non-connected porosity and not commonly studied in geoengineering industry. However, the presence of micropores plays a key role in connecting macropores and it can contribute significantly to the overall flow performance. In this study, targeted CO2 storage carbonate fields in Southeast Asia have significant amounts of microporosity ranging from 10 to 60% of the total measured porosity. Microporosity can only be seen in high resolution images. To study the unresolved and the resolved microporosity, Middle Miocene carbonate samples from CO2 storage candidate fields were scanned using lower resolution micro-computed micro-tomography (micro-CT) and higher resolution synchrotron light source to understand the pore scale structure of the carbonate sample at different length scales. This paper proposes a proof-of-concept upscaling method that integrates multiscale 3D imaging techniques and trendline analysis to establish porosity-permeability relationships with microporosity insight. After image acquisition and processing, the images were divided into smaller sub-volumes. Pore-scale modelling was conducted to predict the permeability using Darcy-Brinkman-Stokes (DBS) model. Then, a nano-scale porosity-permeability transform is generated using natural log trendline fitting based on simulation results. The porosity-permeability transform is further extended to three cases to cover the low case, mid case, and high case of datapoint fittings and is further validated with laboratory measured data. The established porosity-permeability transforms in this study have been applied to compare with petrophysical derived porosity-permeability transforms with better performance (higher R2 value) for low permeability datapoint. The multiscale imaging upscaling workflow has integrated machine learning during image segmentation with pore-scale modelling and trendline fitting during the upscaling study. It emphasises the importance of seeing the unseen (unresolved microporous phase) to understand the internal texture and microstructure of a rock sample in order to understand the connectivity of the overall flow performance in a carbonate rock.@en

Subsurface porous rocks hold significant hydrogen (H2) storage potential to support an H2-based energy future. Understanding H2 flow and trapping in subsurface rocks is crucial to reliably evaluate their storage efficiency. In this work, we perform cyclic H2 flow visualization experiments on a layered rock sample with varying pore and throat sizes. During drainage, H2 follows a path consisting of large pores and throats, through a low permeability rock layer, substantially reducing H2 storage capacity. Moreover, due to the rock heterogeneity and depending on the experimental flow strategy, imbibition unexpectedly results in higher H2 saturation compared to drainage. These results emphasize that small-scale rock heterogeneity, which is often unaccounted for in reservoir-scale models, plays a vital role in H2 displacement and trapping in subsurface porous media, with implications for efficient storage strategies.@en

The traditional model of solid dissolution in porous media consists of three dissolution regimes (uniform, compact, wormhole)-or patterns-that are established depending on the relative dominance of reaction rate, flow, and diffusion. In this work, we investigate the evolution of pore structure using numerical simulations during acid injection on two models of increasing complexity. We investigate the boundaries between dissolution regimes and characterize the existence of a fourth dissolution regime called channeling, where initially fast flow pathways are preferentially widened by dissolution. Channeling occurs in cases where the distribution in pore throat size results in orders of magnitude differences in flow rate for different flow pathways. This focusing of dissolution along only dominant flow paths induces an immediate, large change in permeability with a comparatively small change in porosity, resulting in a porosity-permeability relationship unlike any that has been previously seen. This work suggests that the traditional conceptual model of dissolution regimes must be updated to incorporate the channeling regime for reliable forecasting of dissolution in applications like geothermal energy production and geologic carbon storage.@en