In the present study, a numerical model based on the lattice Boltzmann method (LBM) is proposed to simulate multiphase mass transfer, referred to as the CST-LB model. This model introduced continuum species transfer (CST) formulation by an additional collision term to model the mass transfer across the multiphase interface. The boundary condition treatment of this model is also discussed. In order to verify the applicability, the CST-LB model is combined with the pseudopotential multiphase model to simulate a series of benchmark cases, including concentration jump near the interface, gas dissolution in a closed system, species transport during drainage in a capillary tube, and multiphase species transport in the porous media. This CST-LB model can also be coupled with other multiphase LBMs since the model depends on the phase fraction field, which is not explicitly limited to specified multiphase models.

In recent years, nuclear magnetic resonance (NMR) logging has become increasingly prevalent in the characterization of rock properties such as porosity, permeability, saturation, and pore size distribution. However, interpreting such properties accurately from NMR logging data is challenging for some reservoirs. In particular, the impact of salinity, viscosity, and saturation on NMR measurements is not always clear, which can lead to inaccuracies in the resulting data interpretation. Properly accounting for these factors is essential in order to obtain accurate and reliable measurements for effective characterization of subsurface formations. This study utilized a random walk technique to simulate the NMR response of homogeneous sandstones using 3D CT images and conducted a sensitivity analysis under various salinity, crude oil viscosity, and water saturation conditions. The results indicate that the T₂ relaxation time slightly shifts toward the short relaxation direction as the salinity of the formation water increases. In addition, longer echo intervals result in a more significant forward shift in the T₂ value than shorter intervals. Whereas, for crude oil, the T₂ relaxation time becomes shorter as its viscosity increases. Furthermore, the effect of echo interval on the forward T₂ shift is less pronounced for crude oil than it is for formation water. Under water wet conditions, the T₂ spectrum of crude oil exhibits a peak at the volume relaxation position. As the water saturation decreases, the left two peaks in the T₂ spectrum shift toward shorter relaxation times. Under oil wet conditions, the T₂ spectrum exhibits a complex three-peak structure. The method provides a physical basis for interpreting NMR macroscopic responses, and the simulated NMR responses can help identify fluids in reservoirs.

The evaluation of rock porosity and the mercury injection capillary pressure (MICP) curve is fundamental for oil and gas exploration and production. Digital rock (DR) technology, incorporating 3D micro-CT imaging and numerical methods, has been widely employed to predict these properties. However, analyzing the pore structure of heterogeneous rocks, such as fractured rocks or glutenite, solely through single-scale DR analysis poses challenges. Existing upscaling methods have limitations in fully representing the complete range of pore structures at different scales, with limited comparison to experimental data. To address this, we propose a novel method that upscales porosity and simulates the MICP curve from nano-scale to core scale by merging results from micro-CT (at resolutions of 35 μm and 2 μm) and SEM (at resolutions of 6.5 nm and 65 nm). We validate the developed DR model by applying it to sandstones, glutenite, and igneous rocks, and achieve excellent agreement between the experimental data and the multi-scale DR model across 67 samples. The results demonstrate that the multi-scale model effectively captures the porosity and pore structures across the entire range. In contrast, the single digital rock (DR) model underestimates the porosity measurements for both homogeneous sandstones and heterogeneous cores. While the MICP model based on a single DR proves suitable for homogeneous rock samples, it introduces noticeable discrepancies when applied to heterogeneous rock samples. The developed multi-scale method significantly enhances the confidence in using DR to assess the pore structure of complex rocks.

The formulation of an effective development plan, optimizing exploitation efficiency, relies heavily on accurate reservoir characterization. However, existing reservoir classification methodologies, which rely on macroscopic geological observations and well-logging data, have limitations in data availability and fail to capture micro-scale pore structure characteristics accurately. The emerging technology of digital rock, widely employed in the petroleum industry, also faces challenges in accurately capturing reservoir heterogeneity due to its single-scale nature and limited application for reservoir classification. To overcome these challenges, this study presents an innovative reservoir classification approach based on the multi-scale digital rock method. This approach integrates qualitative assessment of micro-CT images for particle contact relationships and pore types with quantitative evaluation of multi-scale characteristic parameters, obtained from micro-CT and scanning electron microscopy (SEM) images. The proposed classification method demonstrates excellent agreement with the prioritization of development and production data for offshore sandstone reservoirs. By establishing a robust evaluation methodology, this classification method facilitates exploration potential assessment and development strategy optimization within the field.

Formation damage is a common phenomenon and is impaired to the reservoir by reducing the productivity. Formation damage is usually caused by solids plugging, clay swelling, saturation changes, etc., and fracturing fluids with a series of chemical additives are pumped into the well for production enhancement. It is difficult to optimize the fracture fluids and well shut-in time due to lack of fundamental understandings. Currently, little research has been done to investigate the mechanisms of formation damage at the pore scale. In this study, a combination of digital rock technology and core sample laboratory soaking experiments is used to evaluate the formation damages for different fracture fluids in tight sandstone reservoir. Three core samples from a full-diameter core are soaked in three different fracture fluids (surfactant, polymer, and gel) for eight different durations (from 2 h to 15d) to simulate well shut-in process. The samples in various soak times are scanned by X-ray micro-computer tomography (Micro-CT) to obtain the 3D images of the true geometry. The images are then compared to optimize the fracture fluids and quantify the damage degree after various well shut-in times. Then, displacement processes are simulated using lattice Boltzmann method (LBM) to evaluate the residual oil saturations and optimize the well shut-in time. The study suggests that the well shut-in process can cause irreversible damage to tight sandstone reservoir even for optimized fracture fluid. In the initial shut-in stages, clays swelling dominates pore structure alteration and reduces the porosity. Calcite will dissolute after which lead to slight porosity increase. In the flowback process after well shut-in, the simulated residual oil saturation will decrease initially and then increase after, which is complied with the porosity variation. The digital rock technology combined with the soaking experiments will provide alternative method for the evaluation of formation damage and the optimization of well shut-in time in tight sandstone reservoir, which can guide the selection of the fracture fluids and onsite fracturing operation.

Reservoir stimulation plays a vital role in enhancing the productivity of tight sandstone formations; however, the injection of stimulation fluids often leads to varying degrees of reservoir damage. Traditional sensitivity evaluations, which rely primarily on laboratory core displacement experiments, can assess overall permeability loss but are limited in revealing the pore-scale mechanisms underlying fluid–rock interactions and their multi-scale effects on reservoir microstructure. To address these limitations, this study introduces a multi-scale digital rock-based methodology that integrates high-resolution imaging and numerical upscaling techniques. Three imaging modalities—plug-scale micro-CT, sub-sample micro-CT, and scanning electron microscopy (SEM) at 500× and 5000× magnifications—were employed to quantitatively analyze changes in pore structure and permeability before and after five types of sensitivity tests: rate, water, salt, acid, and alkali sensitivity. Results show that all five sensitivity mechanisms significantly impair permeability, with water and salt sensitivities causing the most severe reductions (up to 68.4% and 69.9%, respectively), mainly due to clay swelling and particle detachment. In acid sensitivity tests, although pore volume increased via mineral dissolution, permeability still declined by 57.1% due to pore-throat blockage from secondary precipitates. Importantly, multi-scale digital rock analysis revealed that microscopic alterations in pore-throat geometry exert a dominant influence on macroscopic permeability trends—an insight not accessible through conventional experimental methods. The proposed approach enables a more quantitative, visual, and mechanism-informed evaluation of sensitivity-induced damage. These findings offer critical guidance for optimizing stimulation fluid design and mitigating formation damage, demonstrating the superior capability of digital rock technology to resolve complex fluid–mineral interactions and inform reservoir management strategies across scales.