Porosity-permeability Relationships Research Articles

The Effects of Facies Variability and Bioturbation Intensity on Permeability in a Mixed Siliciclastic–Carbonate Core from the Upper Strawn Group, Katz Field, Eastern Shelf of the Permian Basin, Texas, USA

For oil and gas reservoir characterization, permeability prediction is indispensable because it helps identify potential flow pathways and lowers risk. Estimating permeability in heterogeneous media is challenging due to the limited number of measurement tools, low-resolution sampling methods, and sampling bias. To combat these issues, we employed a probe permeameter to produce a high-resolution (4 in [10 cm] spacing) permeability dataset for cores from the Strawn Formation, Katz Field, Permian Basin, Texas, USA. We structured our sampling to record permeability changes related to facies variability and fluctuating bioturbation intensity. We compared probe permeameter data to wireline logs and core-plug porosity and permeability data recorded at larger spacings. The results show that permeability is affected by facies type, bioturbation intensity, and cementation. The effects of bioturbation are non-linear; in our study, moderate bioturbation enhances permeability by improving connections between sands while intense bioturbation decreases permeability by redistributing fines. Core-plug and probe measurements gave similar permeability values, but the number of core plugs taken in the finer-grained intervals was insufficient. The probe, however, provided better resolution and gave larger net-to-gross sand ratios than core-plug-based evaluations. Using only the core-plug porosity–permeability relationship with wireline density log porosities led to permeability predictions too large by a factor of three or more compared to averaged probe permeameter values.

Investigation of geochemically induced permeability alteration in geothermal reservoirs and its implications for sustainable geothermal energy production

Geothermal resources constitute a significant portion of the world's low-carbon, renewable energy potential, with about 75% classified as low-temperature. One such potential resource exists in Precambrian basement rocks underlying the Williston Basin in southern Saskatchewan, Canada, with a reservoir temperature of 120 °C. However, geochemically induced permeability alteration in these highly reactive low-temperature granitoid resources poses a significant risk to long-term heat production. To assess and potentially mitigate this risk, we conducted a geochemical and mineralogical study of both altered and unaltered samples. Our findings facilitated the parameterization of geochemical simulations of water-rock interactions to predict mineral volume changes and, by extension, draw inferences on porosity and permeability changes resulting from these interactions. The simulations indicate an increased mineral volume in both samples, yet geothermal alteration of the unaltered, and thus more reactive, rocks induced relative mineral volume changes about 30% greater than those in the altered rocks. The resulting absolute change in porosity is 0.5 vol% for the unaltered rocks and 0.35 vol% for the altered rocks. Utilizing an empirical porosity-permeability relationship, the computed change in permeability indicates that the unaltered basement rock experienced a greater change in total permeability than the altered basement rocks. Additional calculations demonstrate the sensitivity of the porosity-permeability equation to critical porosity and power exponent, forecasting various scenarios with permeability changes ranging from 1.0 × 10−13 to 1 × 10−20 m2. Consequently, we infer that altered, permeable zones of the examined Precambrian basement rocks are likely to offer favourable conditions for sustained, multi-decade heat production, and thus should be targeted over less altered zones to justify initial capital expenditures. Globally, geothermal heat extraction from these rocks remains an underexplored yet promising resource for generating reliable, low-carbon renewable energy, crucial in our efforts to decarbonize the global economy.

Permeability Upscaling Conversion Based on Reservoir Classification

Deep and ultra-deep reservoirs are characterized by low porosity and permeability, pronounced heterogeneity, and complex pore structures, complicating permeability evaluations. Permeability, directly influencing the fluid production capacity of reservoirs, is a key parameter in comprehensive reservoir assessments. In the X Depression, low-porosity and low-permeability formations present highly discrete and variable core data points for porosity and permeability, rendering single-variable regression models ineffective. Consequently, accurately representing permeability in heterogeneous reservoirs proves challenging. In the following study, lithological and physical property data are integrated with mercury injection data to analyze pore structure types. The formation flow zone index (FZI) is utilized to differentiate reservoir types, and permeability is calculated based on core porosity–permeability relationships from logging data for each flow unit. Subsequently, the average permeability for each flow unit is computed according to reservoir classification, followed by a weighted average according to effective thickness. This approach transforms logging permeability into drill stem test permeability. Unlike traditional point-by-point averaging methods, this approach incorporates reservoir thickness and heterogeneity, making it more suitable for complex reservoir environments and resulting in more reasonable conversion outcomes.

Naturally fractured reservoir characterisation in heterogeneous sandstones: insight for uranium in situ recovery (Imouraren, Niger)

Abstract. This study delves into the characterisation of a heterogenous reservoir, the Tchirezrine II sandstone unit in northern Niger. The characterisation is crucial for potential uranium in situ recovery (ISR) in a naturally fractured and faulted context. Employing a multifaceted approach, including well log data, optical borehole imagery, and hydrogeological tests, alongside satellite-based lineament analysis, this study provides a comprehensive understanding of the structures and their impact on fluid flow. Lineament analysis reveals scale-dependent patterns, consistent with spatially homogeneous joint networks restricted to mechanical units, as well as nearly scale-invariant patterns, better corresponding to spatially heterogeneous fault networks. Various deformation structures are detected from borehole imagery, including extensional fractures, cataclastic deformation bands, and brecciated–cataclastic fault cores. Based on well log data, the Tchirezrine II reservoir displays heterogeneous porosity and permeability related to its fluvial context. These data differ from the traditional porosity–permeability relationship obtained in a sandstone reservoir matrix but are instead consistent with Nelson's classification, emphasising the impact of deformation structures on such petrophysical properties. Hydrological tests have been implemented into a zone of E–W-trending deformation structures, revealing a strong permeability anisotropy. This strong E–W anisotropy is consistent with the presence of the observed E–W structures, i.e. with a draining behaviour of extensional open fractures and a sealing behaviour of both cataclastic bands and fault rocks. Considering implications for ISR mining, this study allows the discussion of the interplay between fractures, faults, and fluid flow properties. It suggests that a well pattern perpendicular to the main permeability orientation can attenuate channelled flow, thus improving the contact of the leach solution with the mineralised matrix. These results provide an integrated approach and a multi-scale characterisation of naturally fractured reservoir (NFR) properties in sandstone, offering a basis for the optimisation of NFR production such as ISR development.

Imaging flow focusing and isolation of aqueous fluids in synthetic quartzite: implications for permeability and retained fluid fraction in deep-seated rocks

The microstructure of realistic fluid–rock systems evolves to minimize the overall interfacial energy, enabling local variations in fluid geometry beyond ideal models. Consequently, the permeability–porosity relationship and fluid distribution in these systems may deviate from theoretical expectations. Here, we aimed to better understand the permeability development and fluid retention in deep-seated rocks at low fluid fractions by using a combined approach of high-resolution synchrotron radiation X-ray computed microtomography imaging of synthesized rocks and numerical permeability computation. We first synthesized quartzite using a piston-cylinder apparatus at different fluid fractions and wetting properties (wetting and non-wetting systems with dihedral angles of 52° and 61°–71°, respectively) under conditions of efficient grain growth. Although all fluids should be connected along grain edges and tubules in the homogeneous isotropic wetting fluid–rock system enabling segregation by gravitational compaction in natural settings, the fluid connectivity rapidly decreased to ~ 0 when the total fluid fraction decreased to 0.030–0.037, as the non-ideality of quartzite, including the interfacial energy anisotropy (i.e., grain faceting), became critical. In non-wetting systems, where the minimum energy fluid fraction based solely on the dihedral angle is ~ 0.015–0.035, the isolated (disconnected) fractions was 0.048–0.062. A streamline computation in the non-wetting system revealed that with decreasing total porosity, flow focusing into fewer channels maintained permeability, allowing the effective segregation of the connected fluids. These results provide insight into how non-wetting fluids segregate from rocks and exemplify the fraction of retained fluids in non-wetting systems. Thus, the findings suggest a potential way for wetting system fluids to be transported into the deep Earth's interior, and the amount of fluids dragged down to the Earth’s interior could be higher than what was previously estimated.

Rock Typing and Flow Unit Identification in the Upper Cretaceous Carbonate Reservoirs in Jambur Oil Field

The effectiveness of dynamic models in field development and predicting future reservoir performance depends on the accuracy and reliability of geological models. These models are constructed based on an accurate categorization of reservoir rock types and the identification of flow units. understanding the geological structure, lithological characteristics, and depositional processes is crucial in differentiating rock types and determining flow units within strata. This study focuses on identifying rock types and flow units within the upper Cretaceous reservoir/Qamchuqa formation of the Jambur oilfield. By employing four petrophysical techniques across six wells, it was determined that the Rock Fabric Number technique and the Winland porosity-permeability relation were insufficient for accurately estimating permeability, primarily due to constraints in regression analysis. The classification of flow zone indicators resulted in the identification of five distinct rock classes that offer a more reliable means of assessing permeability in intervals lacking core data. Subsequently, the cluster analysis process sorted the reservoir rock into cohesive groups based on the raw log data and calibrated it with the Flow Zone Indicator (FZI) method. In conclusion, permeability can be determined through equations derived from the FZI method, and the establishment of petrophysical characteristics within a geological model can be achieved by utilizing rock facies derived from cluster analysis.

A MATLAB approach for developing digital rock models of heterogeneous limestones for reactive transport modeling

Porosity is a key parameter controlling the physico-chemical behavior of porous rocks. Digital rock physics offers a unique technique for imaging the inherently heterogeneous rock microstructure at fine spatial resolutions and its computational reconstruction, through which a better understanding and prediction of the rock behavior can be achieved. In this study, we propose a simple but accurate method to build a 3D porosity map of centimeter-scale carbonate rock cores from X-ray Micro Computed Tomography (XMCT) imaging data. The method consists of 3 main steps: i) decomposition of 3D volumetric XMCT data into sub-volumes, ii) processing of equidistributed 2D cross-section images in each sub-volume and iii) 2D slice-by-slice calculation of porosity and its assembly to reconstruct a 3D continuum porosity map over the whole core domain using a MATLAB code. The proposed approach significantly conserves the required memory to manipulate large image datasets. The digitized porosity representations are used to build 3D permeability maps of the cores by applying an explicit permeability-porosity relationship. The permeability maps are used as input for numerical simulation of the rock response to the percolation of reactive fluids through which the general validity of the approach is verified. The developed digital rock model paves the way for an improved understanding of reactive transport in carbonate rocks.

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 ϕ and KIC on σ1 was thoroughly studied using parametric study. The study concludes that the effect of ϕ is more prominent than KIC on σ1. At a constant porosity of 0.1, the stress ratio decreases from 0.0082 to 0.0078 when KIC increases from 0.1 to 0.2, indicating a 5% decrease in stress ratio. Whereas, at a constant KIC 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.

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.

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.

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.

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.

Reevaluating Traditional Porosity-Permeability Relationships: Investigating the Influence of Crystallite Distribution on Pore Geometry and Permeability Evolution in Porous Media

Reevaluating Traditional Porosity-Permeability Relationships: Investigating the Influence of Crystallite Distribution on Pore Geometry and Permeability Evolution in Porous Media

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.