Porosity-permeability Relationships Research Articles

Mineral Precipitation and Geometry Alteration in Porous Structures: How to Upscale Variations in Permeability–Porosity Relationship?

Mineral Precipitation and Geometry Alteration in Porous Structures: How to Upscale Variations in Permeability–Porosity Relationship?

Characterizing permeability-porosity relationships of porous rocks using a stress sensitivity model in consideration of elastic-structural deformation and tortuosity sensitivity

Clarifying the relationship between stress sensitivities of permeability and porosity is of great significance in guiding underground resource mining. More and more studies focus on how to construct stress sensitivity models to describe the relationship and obtain a comprehensive stress sensitivity of porous rock. However, the limitations of elastic deformation calculation and incompleteness of considered tortuosity sensitivity lead to the fact that the existing stress sensitivity models are still unsatisfactory in terms of accuracy and generalization. Therefore, a more accurate and generic stress sensitivity model considering elastic-structural deformation of capillary cross-section and tortuosity sensitivity is proposed in this paper. The elastic deformation is derived from the fractal scaling model and Hooke's law. Considering the effects of elastic-structural deformation on tortuosity sensitivity, an empirical formula is proposed, and the conditions for its applicability are clarified. The predictive performance of the proposed model for the permeability-porosity relationships is validated in several sets of publicly available experimental data. These experimental data are from different rocks under different pressure cycles. The mean and standard deviation of relative errors of predicted stress sensitivity with respect to experimental data are 2.63% and 1.91%. Compared with other models, the proposed model has higher accuracy and better predictive generalization performance. It is also found that the porosity sensitivity exponent α, which can describe permeability-porosity relationships, is 2 when only elastic deformation is considered. α decreases from 2 when structural deformation is also considered. In addition, α may be greater than 3 due to the increase in tortuosity sensitivity when tortuosity sensitivity is considered even if the rock is not fractured.

Expanded pore-emanated cracking model for brittle failure of sedimentary rocks under triaxial compression

Brittle fracture and its relationship to deformation and strength have been a fundamental area of research in rock mechanics. This paper presents an expanded pore-emanated cracking model to better understand the fracture behaviors and predict the compressive strength of sedimentary rocks. This proposed model is developed to account for a triaxial compression condition using the triaxial compression test results on sandstone, limestone and siltstone samples from Wyoming, USA and experimental data on sedimentary rocks collected from published literature. The normalized critical crack length is determined from the proposed model through which the peak compressive strength is estimated when the stress intensity at the crack tip reaches a critical value called the fracture toughness. Results indicate that the rock porosity and pore radius have an inverse relationship with the compressive strength. Adopting the porosity-permeability relationship, the pore radius is calculated in terms of porosity and grain size. Next, the effect of grain size is implicitly included in the model and negatively correlated with the compressive strength. Moreover, a new approach is proposed for the estimation of fracture toughness based on the pore radius and confining pressure. The predicted compressive strengths from the proposed model show a good agreement with the measured strengths with a mean bias (i.e. average ratio of the measured to predicted strengths) of 1.014. The influence of and on was thoroughly studied using parametric study. The study concludes that the effect of is more prominent than on . At a constant porosity of 0.1, the stress ratio decreases from 0.0082 to 0.0078 when increases from 0.1 to 0.2, indicating a 5% decrease in stress ratio. Whereas, at a constant of 0.1, the stress ratio increases from 0.0082 to 0.014 when the porosity increases from 0.1 to 0.2, indicating 71% increases in stress ratio and therefore compressive strength.

Numerical Study on Permeability of Reconstructed Porous Concrete Based on Lattice Boltzmann Method

The reconstruction of the porous media model is crucial for researching the mesoscopic seepage characteristics of porous concrete. Based on a self-compiled MATLAB program, a porous concrete model was modeled by controlling four parameters (distribution probability, growth probability, probability density, and porosity) with clear physical meanings using a quartet structure generation set (QSGS) along with the lattice Boltzmann method (LBM) to investigate permeability. The rationality of the numerical model was verified through Poiseuille flow theory. The results showed that the QSGS model exhibited varied pore shapes and disordered distributions, resembling real porous concrete. Seepage velocity distribution showed higher values in larger pores, with flow rates reaching up to 0.012 lattice point velocity. The permeability–porosity relationship demonstrated high linearity (the Pearson correlation coefficient is 0.92), consistent with real porous concrete behavior. The integration of QSGS-LBM represents a novel approach, and the research results can provide new ideas and new means for subsequent research on the permeability of porous concrete or similar porous medium materials.

Integrated petrophysical, sedimentological and well-log study of the Mangahewa Formation, Taranaki Basin, New Zealand

This study aims to address the problem of porosity preservation in the Mangahewa Formation of five main hydrocarbon fields covering onshore and offshore of the Taranaki Basin. An integrated reservoir characterization of the Middle to Late Eocene Mangahewa Formation is achieved through petrophysical evaluation, sedimentological and petrographical descriptions, and well log analysis methods. Petrophysical parameters (porosity and permeability) were acquired from the available core analysis and using mathematical equations to obtain other petrophysical matrices such as normalized porosity index (NPI) and reservoir quality index (RQI). Factors that affected Mangahewa reservoir were studied through thin-section microscopy and well-log analysis helped to measure the reservoir and hydrocarbon potentiality in the Mangahewa Formation. The Mangahewa Formation is dominated by sandstone and a range of marginal to shallow marine facies with varying hydraulic flow units (HFU). The Mangahewa Formation has a high positive correlation in porosity-permeability relationship and has a maximum of 4.67 μm RQI and 20.08 μm FZI (Well Kapuni-14) which reflect potential reservoir. The Mangahewa Formation observed from Wells Kapuni-14, Maui-A1G, McKee-16A, and Mokau-1 are dominated with 59.6%, 56.4%, 79.3%, and 68% of macro- and megapores, respectively. The presence of authigenic clay and calcite cement has greatly reduced the reservoir quality; however, primary and secondary pores are still observed within the Mangahewa sands. Moreover, well log analysis was carried out on four wells in Taranaki Basin, to run a qualitative and quantitative analysis of the Mangahewa reservoir. Eight potential reservoir zones were examined, revealing that the Mangahewa Formation has a very low shale volume of less than 6%, good effective porosity ranging between 11.0% and 13.3%, up to 36.2% of average water saturation and maximum of 69.8% average hydrocarbon saturation. In conclusion, from this comprehensive study, it can be deduced that the Mangahewa Formation possesses fair to good reservoir quality and hydrocarbon potentiality.

Surrogate model for geological CO[formula omitted] storage and its use in hierarchical MCMC history matching

Deep-learning-based surrogate models show great promise for use in geological carbon storage operations. In this work we target an important application — the history matching of storage systems characterized by a high degree of (prior) geological uncertainty. Toward this goal, we extend the recently introduced recurrent R-U-Net surrogate model to treat geomodel realizations drawn from a wide range of geological scenarios. These scenarios are defined by a set of metaparameters, which include the horizontal correlation length, mean and standard deviation of log-permeability, permeability anisotropy ratio, and constants in the porosity-permeability relationship. An infinite number of realizations can be generated for each set of metaparameters, so the range of prior uncertainty is large. The surrogate model is trained with flow simulation results, generated using the open-source simulator GEOS, for 2000 random realizations. The flow problems involve four wells, each injecting 1 Mt CO2/year, for 30 years. The trained surrogate model is shown to provide accurate predictions for new realizations over the full range of geological scenarios, with median relative error of 1.3% in pressure and 4.5% in saturation. The surrogate model is incorporated into a hierarchical Markov chain Monte Carlo history matching workflow, where the goal is to generate history matched geomodel realizations and posterior estimates of the metaparameters. We show that, using observed data from monitoring wells in synthetic ‘true’ models, geological uncertainty is reduced substantially. This leads to posterior 3D pressure and saturation fields that display much closer agreement with the true-model responses than do prior predictions.

Permeability Prediction Using Advanced Magnetic Resonance Tools and Hydraulic Reservoir Units Techniques for the Pliocene Sand Reservoirs, Sapphire Offshore Gas Field, Mediterranean, Egypt

Permeability derived from magnetic resonance advanced logging tools was used to unlock the Pliocene sandstone reservoir heterogeneity. Permeability prediction from well logs is a significant target due to the unavailability of core data. The hydraulic flow unit approach is used to classify the reservoir rocks according to their porosity-permeability relationship. The predicted permeability is calculated using Sapphire-Dh magnetic resonance porosity and permeability relationship for each flow unit. Flow Zone Indicator and the quality flow unit have a direct proportion relationship. For the model's verification, the predicted permeability is plotted against the measured resonance permeability in Sapphire-Dh as a reference studied well, showing highly matching results. Accordingly, the applied approach is implemented in the other three wells, which have neither core samples nor advanced logs measurements.

Control of brine composition over reactive transport processes in calcium carbonate rock dissolution: Time-lapse imaging of evolving dissolution patterns

This study investigates the impact of brine composition—specifically calcium ions and NaCl-based salinity—on the development of dissolution features in Ketton, a porous calcium carbonate rock. Utilizing a laboratory XMT (X-ray microtomography) scanner, we captured time-lapse in situ images of Ketton samples throughout various dissolution experiments, conducting four distinct flow-through experiments with differing brine solutions at a flow rate of 0.26 ml min⁻1. The scans yielded a voxel size of 6 μm, enabling the assessment of the temporal evolution of porosity and pore structure through image analysis and permeability evaluations via single-phase fluid flow simulations employing direct numerical solutions and network modeling, as opposed to direct measurement.Time-lapse imaging technique has delineated the extent to which the concentrations of CaCl₂ and NaCl in the injecting solution control the structural evolution of dissolution patterns, subsequently triggering the development of characteristic dissolution pattern. The inflow solution with no Ca2+ ions and with the minimal salt content manifested maximum dissolution near the sample inlet, coupled with the formation of numerous dissolution channels, i.e., wormholes. Conversely, solutions with a trace amount of Ca2⁺ ions induced focused dissolution, resulting in the formation of sparsely located channels. Inflow solutions with high concentrations of both Ca2⁺ ions and salt facilitated uniformly dispersed dissolution, primarily within microporous domains, initiating particle detachment and displacement and leading to localized pore-clogging. The relative increase in permeability, in each experiment, was correlated with the developed dissolution pattern. It was discerned that varying ratios of salt and calcium concentrations in the injected solution systematically influenced image-based permeability simulations and porosity, allowing for the depiction of an empirical porosity-permeability relationship.

Porosity-permeability tensor relationship of closely and randomly packed fibrous biomaterials and biological tissues: Application to the brain white matter

The constitutive model for the porosity-permeability relationship is a powerful tool to estimate and design the transport properties of porous materials, which has attracted significant attention for the advancement of novel materials. However, in comparison with other materials, biomaterials, especially natural and artificial tissues, have more complex microstructures e.g. high anisotropy, high randomness of cell/fibre dimensions/position and very low porosity. Consequently, a reliable microstructure-permeability relationship of fibrous biomaterials has proven elusive. To fill this gap, we start a mathematical derivation from the fundamental brain white matter (WM) formed by nerve fibres. This is augmented by a numerical characterisation and experimental validations to obtain an anisotropic permeability tensor of the brain WM as a function of the tissue porosity. A versatile microstructure generation software (MicroFiM) for fibrous biomaterial with complex microstructure and low porosity was built accordingly and made freely accessible here. Moreover, we propose an anisotropic poro-hyperelastic model enhanced by the newly defined porosity-permeability tensor relationship which precisely captures the tissues macro-scale permeability changes due to the microstructural deformation in an infusion scenario. The constitutive model, theories and protocols established in this study will both provide improved design strategies to tailor the transport properties of fibrous biomaterials and enable the non-invasive characterisation of the transport properties of biological tissues. This will lead to the provision of better patient-specific medical treatments, such as drug delivery. Statement of significanceDue to the microstructural complexity, a reliable microstructure-permeability relationship of fibrous biomaterials has proven elusive, which hinders our way of tuning the fluid transport property of the biomaterials by directly programming their microstructure. The same problem hinders non-invasive characterisations of fluid transport properties in biological tissues, which can significantly improve the efficiency of treatments e.g. drug delivery, directly from the tissues accessible microstructural information, e.g. porosity. Here, we developed a validated mathematical formulation to link the random microstructure to a fibrous material’s macroscale permeability tensor. This will advance our capability to design complex biomaterials and make it possible to non-invasively characterise the permeability of living tissues for precise treatment planning. The newly established theory and protocol can be easily adapted to various types of fibrous biomaterials.

BCH modelling studies on biocementation process in mitigating leaks from a CO2 sequestrated aquifer

BCH modelling studies on biocementation process in mitigating leaks from a CO2 sequestrated aquifer

Rock Typing Approaches for Effective Complex Carbonate Reservoir Characterization

For highly heterogeneous complex carbonate reef reservoirs, rock typing with respect to depositional conditions, secondary processes, and permeability and porosity relationships is a useful tool to improve reservoir characterization, modeling, prediction of reservoir volume properties, and estimation of reserves. A review of various rock typing methods has been carried out. The basic methods of rock typing were applied to a carbonate reservoir as an example. The advantages and disadvantages of the presented methods are described. A rock typing method based on a combination of hydraulic flow units and the R35 method is proposed. Clustering methods for rock typing are used. The optimum clustering method is identified, and for each rock type, the permeability–porosity relationships are built and proposed for use in the geomodelling stage.

Integrated geological data, 3D post‐stack seismic inversion, depositional modelling and geostatistical modelling towards a better prediction of reservoir property distribution for near‐field exploration: A case study from the eastern Sirt Basin, Libya

De‐risking the hydrocarbon potential in near‐field exploration is one of the most important procedures in the exploration of hydrocarbons, and it requires the integration of various data to predict the reservoir characteristics of the prospect area more accurately. In this work, wells and 3D seismic data from the Libyan producing oil fields were utilized to demonstrate how well this technique worked to improve and describe the hydrocarbon potential of the carbonate geobody that corresponds to the Palaeocene Upper Sabil Formation, which was revealed by new seismic data. This study integrates different types of data, including 3D seismic, seismic acoustic impedance, depositional history and geostatistical analysis, to predict the facies, reservoir porosity and permeability distributions and then visualize them in a 3D reservoir model. The 3D seismic data analysis revealed the presence of a clear seismic anomaly geobody (GB) that has never been penetrated by any well. The sedimentological analysis for the well adjacent to the GB indicated a deep‐water depositional environment as turbidites surrounded by deep‐water mud dominated facies. The Upper Palaeocene interval in the study area was subdivided based on the depositional facies and seismic stratigraphy into eight zones that were used to build the reservoir model framework. According to the porosity permeability relationships, the carbonate facies has been classified into five E‐Facies, that is, soft highly argillaceous limestone, hard argillaceous limestone, porous limestone (<20% porosity, and >30% shale volume), medium quality limestone (10–20% porosity, and >30% shale volume) and tight limestone (<10% porosity, and >30% shale volume). The rock physics and inversion feasibility analysis indicated that the acoustic impedance (AI) can be used to predict the porosity but not the lithology or the fluid content. The Bayesian classification has shown excellent results in predicting and modelling the reservoir facies distribution within the study area, utilizing the integration of gross depositional maps (GDEs), wells and seismic data. The reservoir quality of the GB was predicted by using the post‐stack seismic inversion, which indicated a high porosity interval (25%–30%). Moreover, the statistical analysis integrated with the well and seismic data was used to predict the GB permeability. The predicted permeability was reasonably high (40–60 mD). The final E‐facies show an excellent match with the input well data and an excellent match with the blind wells that were used for result quality control (QC) with higher vertical resolution. The developed model can be used as a guide for de‐risking the studied GB hydrocarbon potential in the studied basin, and it can be applied in other similar geological conditions worldwide for exploring underexplored reservoirs and de‐risking their hydrocarbon potential.

Channeling is a distinct class of dissolution in complex porous media

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.

Determination of Reservoir Hydraulic Flow Units and Permeability Estimation Using Flow Zone Indicator Method

Reservoir characterization plays a crucial role in comprehending the distribution of formation properties and fluids within heterogeneous reservoirs. This knowledge is instrumental in constructing an accurate three-dimensional model of the reservoir, facilitating predictions regarding porosity, permeability, and fluid flow distribution. Among the various methods employed for reservoir characterization, the hydraulic flow unit stands out as a widely adopted approach. By effectively subdividing the reservoir into distinct zones, each characterized by unique petrophysical and geological properties, hydraulic flow units enable comprehensive reservoir analysis. The concept of the flow unit is closely tied to the flow zone indicator, a critical parameter that defines the porosity-permeability relationships of each hydraulic flow unit. Additionally, the flow zone indicator method proves valuable in estimating permeability accurately. In this study, we demonstrate the application of the flow zone indicator method to determine hydraulic flow units within the Khasib formation. By analyzing core data and calculating the Rock Quality Index (RQI) and Flow Zone Indicator (∅Z), we differentiate the formation into four hydraulic flow units based on FZI values. Specifically, HFU 1 represents a rock of poor quality, corresponding to compact and chalky limestone. HFU 2 represents intermediate quality, corresponding to argillaceous limestone, while HFU 3 represents good quality, corresponding to porous limestone. Lastly, HFU 4 signifies an excellent reservoir rock quality characterized by vuggy limestone. By establishing a permeability equation that correlates with effective porosity for each rock type, we successfully estimate permeability. Comparing these estimated permeability values with core permeability reveals a strong agreement with a high correlation coefficient of 0.96%. Consequently, the flow zone indicator method effectively classifies the Khasib formation into four distinct hydraulic flow units and provides an accurate and reliable means of determining permeability in the reservoir. The resulting permeability equations can be applied to wells and depth intervals lacking core measurements, further emphasizing the practical utility of the FZI method.

Compaction and sintering effects on scaling law of permeability-porosity relation of powder materials

Analysis and understanding of the permeability-porosity relationship of powder materials by cold compaction and solid-state hot sintering is very important for material design and optimization. This work presents a pore-scale numerical framework, including a discrete element method for powder cold compaction, a cellular automata algorithm with curvature-driving redistribution for solid-state hot sintering and a lattice Boltzmann method for fluid flow simulation, to study the permeability-porosity relationship of materials by cold compaction and solid-state hot sintering processes. The results show that the cubic scaling law always holds for the porous materials by cold compaction, while the hot sintering process decreases the permeability dramatically at low porosity. An exponential decay function has been proposed as a correction factor to the permeability-porosity relationship of materials by compaction & sintering processes, which predicts the permeability asymptotically approaching to the cubic scaling law at high porosity while agreeing well with both numerical and experimental data at low porosity. The microstructure evolution analysis shows that the small pores that connect large pores may vanish by sintering, which causes the remarkable permeability decrease at low porosity. The excellent agreements between the numerical predictions and the experimental measurements suggest that the proposed numerical framework provides a powerful tool for analysis and optimization of material designs.

Lower limits of petrophysical parameters for effective reservoirs in ultradeep carbonate gas reservoirs: A case study from the Deng IV Member, Gaoshiti-Moxi Area, Sichuan Basin, SW China

Lower limits of petrophysical parameters (LLPP) of effective reservoirs are significant parameters for reserve evaluation and exploitation scheme formulation of hydrocarbon reservoirs. However, the existing LLPP determination method is not applicable to ultradeep carbonate reservoirs with diverse reservoir space and strong heterogeneity. Therefore, a systematic method for determining the LLPP of ultradeep carbonate gas reservoirs was developed in this study. First, the geological setting and reservoir characteristics were briefly introduced, and numerous cores were classified according to whether cavities and fractures were developed. Subsequently, the test data of petrophysical property, NMR, high-pressure mercury intrusion (HPMI), and fluid physical property were collected, and a series of LLPP values were obtained through static methods of cumulative frequency statistics, porosity–permeability relationship, irreducible water saturation, and minimum flowable pore throat radius (Rmin). The LLPP determined by static methods were then verified by dynamic methods of gas well testing, productivity model prediction, and productivity simulation experiment, and the LLPP of reservoirs that can form industrial gas flow were determined. Finally, the effect of reservoir heterogeneity on LLPP was revealed, the applicability of various LLPP determination methods were summarized, and the accuracy of the obtained LLPP was confirmed by well testing interpretations. The research results show that the reasonable classification of reservoir types is the prerequisite to accurately determine the LLPP of carbonate reservoirs. The lower limit of porosity is little affected by cavities, while the lower limit of permeability is greatly affected by fractures. Rmin of ultradeep carbonate reservoirs obtained by HPMI test and water film thickness calculation is approximately 60 nm. The significant heterogeneity of carbonate reservoirs requires that effective reservoirs should reach the lower limit of porosity and permeability simultaneously. LLPP determined through static methods and dynamic methods can be applied to evaluate geological and dynamic reserves, respectively. The LLPP of effective reservoirs that allow gas to accumulate, migrate, and form industrial gas production are 2.68% and 0.042 mD.

Pore-scale study of calcite dissolution during CO2-saturated brine injection for sequestration in carbonate aquifers

The calcite reaction with carbonate acid is a prerequisite to release cations providing the reactant for mineral trapping, however, the complicated multiple physicochemical processes during calcite dissolution are hardly precisely captured in carbonate aquifers, impeding the CO2 sequestration technology. In this work, a pore-scale numerical study based on the lattice Boltzmann method coupled fluid flow, mass transport, heterogeneous reactions, and calcite structure evolution is implemented to investigate the calcite dissolution process. Firstly, the impact of pressure difference on this reaction is analyzed to identify two characteristic dissolution patterns. Selecting two typical pressure differences, namely 0.036 and 0.36 Pa, the dissolution dynamics under different temperatures from 25 to 85 °C is then investigated by species concentration and solid distributions elucidating that the effect of pressure difference on calcite dissolution will drop with the increment of temperature. Moreover, the regime diagram of calcite dissolution is plotted based on the relation between temperature and pressure. Finally, to upscale the simulation results to the representative element volume scale, the temporal evolution of normalized permeability, the normalized permeability-porosity relationship and the optimal operations are explored to find that the maximum discrepancy of the normalized permeability with the time among all cases is approximately seven times and the best operating conditions promoting the mineral trapping are a high-temperature formation with a high injection rate.

3D Pore-Throat Microstructure Complexity of Igneous Reservoir Rock and its Effects on the Porosity–Permeability Relation

3D Pore-Throat Microstructure Complexity of Igneous Reservoir Rock and its Effects on the Porosity–Permeability Relation

Applying Facies Characterization to Build 3D Rock-Type Model for Khasib Formation, Amara Oil Field

Building a rock-type (facies) model is critical in the process of constructing the geological model.The facies model utilizes the facies obtained from the different characterization methods to represent the structure and the geology of the studied reservoir. Therefore, the importance of building a 3D rock-type model is to distribute the petrophysical properties depending on the rock facies to reflect the actual distribution and achieve a realistic model.Khasib formation in Amara oil field is mainly composed of limestone and exhibits a high degree of heterogeneities in its petrophysical and geological features, showing a complicated porosity-permeability relationship. Hence, the formation should be characterized by facies with specific property relationships and use these facies to build an accurate rock-type model to represent the geological rock modeling for this carbonate formation.The Rock-Type model for Khasib formation has been constructed using the facies obtained from flow zone indicator and cluster analysis characterization methods, these facies were distributed with the PETREL software by applying the sequential indicator simulation (SIS) algorithm.The 3D Rock- type model establishes that a different rock type characterized each unit within Khasib formation; the reservoir units (KH11, KH12, and KH2) were characterized by the presence of RT-1, RT-2,andRT-3, which represent the best, good, and intermediate reservoir quality rocks, respectively. The best rock type RT-1 with the best reservoir petrophysical properties was only noticed in unit KH2. The non-reservoir units (Khasib, Base KH11, Base KH12, and Base KH2) were characterized by RT-4 and RT-5, which reflect the bad rock quality with non-reservoir properties.

Multi-scale geophysical characterization of microporous carbonate reservoirs utilizing machine learning techniques: An analog case study from an upper Jubaila formation outcrop, Saudi Arabia

Microporosity hosts a significant portion of the total hydrocarbon volume in the Middle Eastern carbonate reservoirs. An improved understanding of microcrystals' morphology that hosts micropores, their impact on reservoir properties, and their spatial distributions will contribute to a more accurate reservoir quality prediction. This study proposes a methodology that utilizes machine learning approaches for microporosity characterization and integrates a multi-scale dataset ranging from micrometer-scale SEM images to meter-scale seismic attributes to build reservoir porosity models. We tested the methodology on an outcrop in Riyadh, Saudi Arabia, which exposes the upper part of the Jubaila Formation equivalent to the lower part of the Arab-D reservoir. We acquired a 35 m-long core and a 600 m-long 2D seismic line behind the outcrop. Laboratory-scale petrophysical measurements, including porosity, permeability, acoustic velocity, bulk and grain density, and x-ray diffraction, were performed over 106 horizontal core plugs drilled from the core. We quantitatively characterized the morphology and microtextures of micrite crystals using SEM images by performing Random Forest classifications trained on SEM image features. We performed unsupervised classification using Self-Organizing Map (SOM) to all lab-measured properties for data clustering. We investigated potential correlations between SOM clusters with micrite morphology, which resulted in a predictable relationship following the granularity and sphericity of microcrystals with porosity, permeability, and acoustic velocity. It was possible to represent multiple lithofacies with a single log-linear porosity-permeability relationship and a single value of equivalent differential effective medium (DEM) aspect ratio in velocity-porosity space. The inter-relationship between micrite morphology and microporosity in the well was then propagated to reservoir-grid scale using inverse differential effective medium (DEM) of acoustic impedance from inverted seismic data. The methodology developed in this study thus provides a practical way to integrate key sub-grid scale micro-and macro-heterogeneities into reservoir scale property models.