Core Porosity Research Articles

Statistical Analysis of Core Porosity of Benin’s Offshore Coastal Sedimentary Basin Reservoir Formations

The reservoir formation porosity is one of the main reservoirs petrophysical properties required for fields characterization. The study aims to verify whether the core porosity of Benin’s offshore petroleum block 1 reservoir formations depends significantly upon the nature of reservoir formations and to determine the porosity ranges, the average porosities and the porosity percentiles (P10, P50 and P90) of these formations. The results have shown that Benin’s Petroleum block 1 reservoir formations core porosities depend significantly on the horizons and the nature of formations. Moreover, the core porosities range from 2.1 to 27.8 percent with averages between 12.31 and 18.95 percent. H9 Albian sand has the highest porosity and H8 Albian sand the lowest one. Abeokuta reservoir formations porosities are respectively 16.95 and 17.77 percent for H6 and H6.5 horizons. They have 50 and 90 percent of chance to be respectively greater than 12 and 5.84 percent no matter the formation. Abeokuta formation core porosity has high chance to be more than 17.3 percent.

A Study on the Breakthrough Pressure of Porous Rock Formations in Gas Storage Reservoirs

Breakthrough pressure of natural gas in rock is an important evaluation parameter in gas reservoir development. In this study, experimental measurements of porosity and permeability of the caprock core were carried out. A digital core model was obtained by body rendering of rock CT (Computed Tomography) slices using Avizo software. Then, the grid model was imported into Fluent software for a numerical simulation of natural gas breakthrough pressure in the core. The innovations of this paper include (1) an accurate calculation method of cap breakthrough pressure based on the VOF method; (2) the method performs a perceptual analysis of average pore radius, wettability, roughness height, and viscosity ratio.

Determination method and application of variable T2 cutoff value in nuclear magnetic logging

Abstract Nuclear magnetic resonance logging (NMR) is a new logging technology. By inversion of relaxation time T2 spectrum, pore characteristics can be directly measured, independent of the influence of rock skeleton minerals, and parameters such as effective porosity, movable fluid porosity, bound water porosity, pore size distribution and permeability can be calculated. The key parameter for calculating fine pore structure is the critical relaxation time of bound water and mobile fluid, namely the T2 cutoff value. The current T2 cutoff value is a fixed value based on the T2 mean value corresponding to the flowable porosity (permeability contribution porosity) in the mercury injection experimental data. However, according to the analysis of mercury injection data, there are differences in the flowable porosity of cores with the same porosity and permeability under the same pressure difference. Based on the synchronous data of nuclear magnetic logging and core mercury injection experiment, this paper establishes a variable T2 cutoff value determination method, which significantly improves the interpretation accuracy of nuclear magnetic logging and lays a foundation for the important application of nuclear magnetic logging in reservoir fine description.

Analysis of classification results of rock cores with different physical properties based on clustering algorithm

Abstract In response to the problem of high difficulty in development caused by different physical properties differences during water flooding in high water bearing oil fields, effective flow unit division and analysis were carried out in Zone 1 of Gangxi through flow unit analysis. The physical property classification of each rock core in the flow unit was determined using the GMM cluster algorithm. The results show that Class I flow units have high permeability and porosity, and good pore permeability performance; The porosity and permeability distribution range of Class II flow units is the widest, with some pore permeability performance comparable to or even higher than Class I, and overall pore permeability performance is good; The porosity and permeability of Class III flow units are lower than the first two types, and their pore permeability performance is relatively poor. The types of core porosity and permeability in the study area can be divided into four categories, with the majority being high permeability, ultra-high permeability, and high permeability. The new research results provide a reference basis for the study of physical property distribution and later well network deployment in the first block of Gangxi District.

Synthesis and characterization of antibacterial and low‐temperature resistant slow rebound polyurethane foams

AbstractSlow rebound polyurethane foam (SPUF) has been widely used due to its advantages such as sound insulation, energy absorption, and good tactile sensation. However, SPUF is prone to harden at low temperature, and its application in medical equipment and households requires significant antibacterial properties. In this paper, self‐made silicone modified polyethylene glycol (Si‐APEG) and graphene oxide supported allicin (Alc@GO) were prepared and used as low‐temperature resistant agent and antibacterial agent, respectively. Low‐temperature resistant polyurethane foam (LSPUF) and antibacterial LSPUF (ALSPUF) were prepared respectively with water as foaming agent. The morphology of ALSPUF was observed by scanning electron microscope. Properties studied include apparent core density and porosity, mechanical properties including tensile strength, 40% compressive hardness, and rebound resilience, as well as low‐temperature resistance. Effects of Si‐APEG content on the structures and properties were analyzed and the LSPUF with an Si‐APEG content of 10 wt.% showed the best comprehensive performance. Therefore, ALSPUFs with Si‐APEG content of 10 wt.% and Alc@GO content of 0–3 wt.% were prepared. The addition of Alc@GO increased the antibacterial ratio significantly without obvious effect on the structure and mechanical properties of LSPUF. The antibacterial ratio of ALSPUF reached 99.07% at a Alc@GO content of 2.5 wt.% and testing time of 60 min. This work provides an effective and feasible method for the preparation of ALSPUF which can be widely used in medical devices and households.Highlights Silicone modified polyether is a suitable low‐temperature resistant agent for PU foam. Allicin supported on GO provides good antibacterial property for PU foam. ALSPUF has better mechanical properties than SPU.

Variation of soil pore structure and predication of the related functions following land‐use conversion identified by multi‐scale X‐ray tomography

AbstractLand‐use conversion profoundly influences the soil pore structure, consequently modifying the soil functions. Investigating the variation of multiscale soil pore structure and their associated functions following land‐use change is critical for evaluating land management strategies. However, this topic has not yet been extensively explored in recent studies. In this study, the pore structure of soil following land‐use conversion was quantitatively investigated by multiscale X‐ray tomography. Intact soil aggregates and undisturbed soil cores were collected from paddy fields (PF) and from vegetable fields were converted from paddy fields for 5 years (VF‐5), 13 years (VF‐13), and 20 years (VF‐20), respectively. Results revealed that the connected porosity of both aggregates and soil cores was significantly increased after land‐use conversion. The isolated porosity of soil aggregates increased, while, conversely, it decreased for soil cores. The variance in pore structure was attributed to the development of new pores, including channels created by vegetable roots, fissures, earthworm holes, and packing pores resulting from the decomposition of soil organic matter and the rearrangement of soil particles. The altered pore structure influenced the soil exchangeability and reservation ability. For aggregates, the isolated porosity of PF and VF‐5 accounted for over 70% of the total imaged porosity. These aggregates displayed a larger water and carbon reservation ability, but limited exchangeability of air, water, and nutrients. The isolated porosity of VF‐13 and VF‐20 aggregates accounted for approximately 50% of the total imaged porosity, suggesting they could effectively balance the exchange and storage of air, water, and nutrients. As for soil cores, isolated pores became negligible (<0.2%) following land‐use conversion, leading to the emergence of a drainable pore system suitable for vegetable plantation. These findings offer insights into the development of pore structures and the prediction of soil function variations at multiple scales, both of which are crucial for optimizing soil management protocols.

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.

Pilot Area Formation Evaluation: Upper Shale Member/ Rumaila Oil Field

This study aims to conduct a comprehensive formation evaluation of a pilot area within the Upper Shale Member of the Rumaila Oil Field. This evaluation is an essential step in the full development of the field. The application of well-log data and core analyses can help in obtaining the desired information about the geological characteristics of the formation. The process begins with measuring the formation temperature and water resistance utilizing Schlumberger’s charts and equations. The volume of shale was determined by two different methods, which were then used together to obtain the final shale volume. The porosity was determined using the conventional porosity equations from the porosity logs and the saturation was estimated based on Archie's equation. In core data analysis, an unconventional technique was utilized to determine rock type and permeability. The core porosity and the permeability were classified into four groups mainly using a self-organizing map and an unsupervised machine-learning method, and selected regression equations of each group were applied to estimate permeability in the core. The method depicted a good agreement between the core and estimated permeabilities, proving it as an effective tool. A complicated training data set was constructed based on the use of a multilayer perceptron neural network on coreless wells to identify rock types and permeability. Analyzing the petrophysical properties of the study area showed evidence that this area is characterized by heterogeneity. The heterogeneity of this formation is due to the presence of a considerable amount of shale, in addition to the significant characteristic differences in the layers and the same layer in different locations. The abundance of shale rock poses challenges during drilling operations, particularly due to shale washout which can lead to mechanical issues with the drilling string. Therefore, caution is advised when drilling new wells in the area to mitigate shale washout risks. Furthermore, the analysis identified layers with high hydrocarbon saturation that are viable for production. Conversely, some layers, characterized by shale presence and poor rock quality, are deemed unsuitable for production, and should not be considered as reservoir rock.

Research on Evaluation of the Carbon Dioxide Sequestration Potential in Saline Aquifers in the Qiongdongnan–Yinggehai Basin

This paper evaluates the carbon dioxide sequestration potential in the saline aquifers of the South Qiongdongnan–Yinggehai Basin. By using a hierarchical evaluation method, the assessment is divided into five stages: the basin level, the zone level, the target level, the site level, and the injection level. The study primarily focuses on evaluating the sequestration potential of and identifying favorable zones of saline aquifers at the basin and zone levels. The optimized volumetric method is adopted, based on the integration of multi-source data such as regional geological maps, seismic data, core porosity, and permeability. The results show that the estimated potential of the Yinggehai Basin is 60.6 billion tons at the basin level and 54.6 billion tons at the zone level. Additionally, the estimated potential of the South Qiongdongnan Basin is 261.5 billion tons at the basin level and 234.8 billion tons at the zone level. The suitability evaluation indicates that the Yinggehai Basin is moderately suitable overall, the northern depression of the South Qiongdongnan Basin is suitable, the central uplift is moderately suitable, and the central depression is not suitable. This study provides a scientific foundation for carbon dioxide sequestration in marine basins and introduces novel ideas and methods for future similar research. This is highly significant for subsequent engineering applications and decision-making processes.

Fine-Tuning Filter Cake Sealing Performance: The Role of Particle Size in Hematite Weighted Water-Based Drilling Fluid.

Three hematite grades with different particle sizes (i.e., large, medium, and small) were evaluated, and the selection criterion was median particle size. The investigation involves the following stages: rheology, filtration, and filter cake formation. Different rheological models including Bingham, Power law, Herschel-Bulkley, and Robertson-Stiff were implemented to find the optimum model for characterizing fluid behavior. The results showed that medium-sized hematite particles produced the highest filtration volume, filter cake thickness, and filter cake permeability. These results were confirmed when a varied pore distribution filtration medium was used. The NMR results showed the same trend where the highest reduction in core porosity was found when a medium-size particle distribution was used. There is a minimum alteration in the rheological behavior of the drilling fluid as the particle size was varied, and the drilling fluids showed a shear-thinning behavior and were best described by the Herschel-Bulkley model. Particle size ratio emerges as a key factor for controlling and enhancing the filtration properties and filter cake characteristics.

Optimizing hematite filter cake treatment using reducing agents

In drilling operations, the formation of a filter cake is crucial for well stability, but its removal post-drilling is essential to restore rock formation productivity. This study focuses on hematite-based filter cakes and investigates factors influencing their solubility and removal, addressing a significant knowledge gap in the field. The research methodology involves examining the effects of various factors, including types and concentrations of reducing agents, temperature, particle size, and treatment duration, on the dissolution process. Notably, Nuclear Magnetic Resonance (NMR) tests are employed to assess the treatment's impact on core porosity. Among the diverse reducing agents examined, ferrous chloride emerges as the optimal choice for effectively enhancing hematite solubility. Particularly, a composite solution of ferrous chloride (10 wt.%) and hydrochloric acid (6 wt.%), was highly efficient demonstrated by exhibiting rapid solubilization of hematite filter cakes. A removal efficiency of approximately 99%, with a parallel enhancement in core permeability was achieved. NMR tests reveal the treatment's success in reinstating the porosity system, which had undergone reduction due to drilling fluid particles. Crucially, the solution exhibits a considerably lower corrosion rate than concentrated hydrochloric acid, highlighting its potential to mitigate environmental concerns while ensuring efficient filter cake removal. The findings of this research provide valuable insights into optimizing post-drilling operations, balancing environmental sustainability and operational efficiency. The identified composite solution offers a promising approach to efficient filter cake removal while mitigating environmental concerns associated with corrosion. Overall, this study contributes to advancing the understanding and practice of well productivity enhancement in the oil and gas industry.

Integration of conventional well logs and core samples to predict porosity of tight reservoir: a case study from Ordos Basin

For reservoirs of oil wells with no cored data, predicting porosity from wireline logs and core samples is an effective approach. Integration of conventional well logs and core samples to predict porosity with high accuracy is particularly challenging owing to complex logging responses of tight sandstone. Therefore, a novel prediction workflow based on a linear interpolation algorithm (LIA) is described to estimate porosity from well logs in the present study. Based on core reposition, porosity correction under overburden pressure, core–log data matching and calculation of shale content, two multi-regression formulae to estimate porosity values are obtained using the nearest neighbour algorithm and LIA respectively. The formulae are applied to the tight sandstone in the Chang 9 member of the Yanchang Formation in the NE Wuqi Oilfield, Ordos Basin. The comparison results indicate that the porosity predicted from the formula obtained by the LIA is in better agreement with the measured porosity, showing a better prediction effect. The application example demonstrates that the LIA formula is applicable for core porosity prediction in the study region. This approach can also be applied for porosity prediction in other oil regions that have similar geological background.

Real-Size Reconstruction of Porous Media Using the Example of Fused Filament Fabrication 3D-Printed Rock Analogues

The multi-scale study of rock properties is a necessary step in the planning of oil and gas reservoir developments. The amount of core samples available for research is usually limited, and some of the samples can be distracted. The investigation of core reconstruction possibilities is an important task. An approach to the real-size reconstruction of porous media with a given (target) porosity and permeability by controlling the parameters of FFF 3D printing using CT images of the original core is proposed. Real-size synthetic core specimens based on CT images were manufactured using FFF 3D printing. The possibility of reconstructing the reservoir properties of a sandstone core sample was proven. The results of gas porometry measurements showed that the porosity of specimens No.32 and No.46 was 13.5% and 12.8%, and the permeability was 442.3 mD and 337.8 mD, respectively. The porosity of the original core was 14% and permeability was 271 mD. It was found that changing the layer height and nozzle diameter, as well as the retract and restart distances, has a direct effect on the porosity and permeability of synthetic specimens. This study shows that porosity and permeability of synthetic specimens depend on the flow of the material and the percentage of overlap between the infill and the outer wall.

Advanced machine learning for missing petrophysical property imputation applied to improve the characterization of carbonate reservoirs

Missing data is a common cause of uncertainty in reservoir characterization, especially in core analysis of porosity and permeability. This is due to the high cost and time required to gather core samples while drilling through the entire reservoir thickness. Therefore, the ability to collect core samples and directly assess petrophysical parameters is restricted by the small proportion of the reservoir thickness that can be measured by the retrieved cores. As a result, the absence of data has the potential to lead to inconsistent and imprecise classification of reservoirs and geomodeling, thereby increasing reservoir uncertainty. Therefore, imputation algorithms are needed to estimate petrophysical properties for incomplete intervals. This study comprehensively compares seven imputation techniques for predicting missing horizontal and vertical core permeability and core porosity data in a well drilled through a carbonate reservoir in a southern Iraqi gas field. The performance of each method was assessed using relative bias (RB) and reasonable descriptive statistical distributions (histogram, log view, and box plots of data ratios to compare the imputed and original data), and robustness to outliers (RtO). The results revealed that the random imputation of missing data (RIMD) technique is the most effective algorithm in addressing the 30.5% missing data (vertical permeability), resulting in the attainment of the RB value closest to zero (0.04076191) compared to other algorithms. Principal component analysis (PCA) and random forest (RF) yielded the most favorable results in terms of handling missing values and outliers for the 15% missing ratio dataset (core porosity and horizontal permeability). The advantages of these approaches are related to their capacity to independently and accurately impute the missing data without requiring extra information, such as well logging records. Additionally, the multiple imputation and machine learning algorithms fill missing values with adequate numbers based on dataset variable distributions and correlations. Multiple plausible values quantify the uncertainty in estimating missing data, avoiding false precision (as with single imputation). Also, the novel workflow involving multiple imputation methods accurately take into account the correlations and variances between the variables. The novel workflow developed for missing data imputation has the potential to be applied to other clastic and carbonate reservoirs in oil and gas fields. The entire data imputation workflow was conducted, validated, visualized by codes in R, a robust open-source statistical computing software.

Optimization and Application of XGBoost Logging Prediction Model for Porosity and Permeability Based on K-means Method

The prediction and distribution of reservoir porosity and permeability are of paramount importance for the exploration and development of regional oil and gas resources. In order to optimize the prediction methods of porosity and permeability and better guide gas field development, it is necessary to identify the most effective approaches. Therefore, based on the extreme gradient boosting (XGBoost) algorithm, laboratory test data of the porosity and permeability of cores from the southern margin of the Ordos Basin were selected as the target labels, conventional logging curves were used as the input feature variables, and the mean absolute error (MAE) and the coefficient of determination (R2) were used as the evaluation indicators. Following the selection of the optimal feature variables and optimization of the hyper-parameters, an XGBoost porosity and permeability prediction model was established. Subsequently, the innovative application of homogeneous clustering (K-means) data preprocessing was applied to enhance the XGBoost model’s performance. The results show that logarithmically preprocessed (LOG(PERM)) target labels enhanced the performance of the XGBoost permeability prediction model, with an increase of 0.26 in its test set R2. Furthermore, the application of K-means improved the performance of the XGBoost prediction model, with an increase of 0.15 in the R2 of the model and a decrease of 0.017 in the MAE. Finally, the POR_0/POR_1 grouped porosity model was selected as the final predictive model for porosity in the study area, and the Arctan(PERM)_0/Arctan(PER0M)_1 grouped model was selected as the final predictive model for permeability, which has better prediction accuracy than logging curves. The combination of K-means and the XGBoost modeling method provides a new approach and reference for the efficient and relatively accurate evaluation of porosity and permeability in the study area.

Characterization of pore structures after ASP flooding for post-EOR

With the global assistance of oil fields entering the stage of improving oil recovery, diversified composite flooding technology has become one of the key research targets. This article takes composite flooding to improve oil recovery as the research object, explores the differential mechanism of crude oil displacement efficiency under water flooding and composite flooding conditions, and elucidates the dynamic evolution characteristics of pore structure before and after composite flooding. Results show that: (a) The permeability and porosity of Daqing oilfield cores have a good correlation. The porosity of cores after water driving and ternary composite driving mainly ranged from 23.6 % to 27.4 % and 22.8 %–26.8 %. The water-driving permeability mainly ranged from 168 × 10−3 μm2 to 2162 × 10−3 μm2. Ternary composite driving permeability mainly ranges from 302 × 10−3 μm2 to 2307 × 10−3 μm2. (b) Compared with water driving, quartz and clay minerals are corroded by alkali during ternary composite driving. (c) Under the condition of similar permeability, the average pore size of the core after ternary composite driving is smaller than the average pore size after water driving.

Static and modal analysis of sandwich panels with rib-reinforced re-entrant honeycomb

The low stiffness resulting from substantial core porosity within the re-entrant honeycomb sandwich panel can be addressed by introducing rib-reinforcements. To investigate its static and vibration characteristics, an energy-based 2D equivalent-homogenization model (2D-EHM) was derived through asymptotic analysis of the leading terms in the governing equations considering the energy-related characteristics. The accuracy of the constructed model for predicting the elastic bending performance of the sandwich panel was verified by comparing the results of a three-point bending experiment with 3D-printed specimens. Comparative analysis with a 3D FE model demonstrates that the 2D-EHM exhibits maximum errors of only 4.65% and 6.46%, respectively, in analyzing static deformation and natural frequency while improving computational efficiencies by up to 59- and 173-folds. Parameter analysis reveals that the performance of SP-RRH is minimally affected by the reinforcement-to-honeycomb wall thickness ratio. However, its performance is compromised when the honeycomb walls align in an equilateral triangle with the reinforcing walls. Comparing specific stiffness as well as static and vibration characteristics of sandwich panels with different core configurations (including traditional and diamond reinforced re-entrant honeycombs) shows that inclusion of rib reinforcements enhances deformation resistance and natural frequencies through increased specific stiffness. These findings provide valuable insights for optimizing design of re-entrant honeycomb sandwich panels.

Vat photopolymerization 3D printing of Al2O3 ceramic cores with strip‐shaped pores by using polyamide 6 fiber template

AbstractThe complex ceramic core used for hollow turbine blades requires high porosity and flexural strength. This work combined vat photopolymerization 3D printing with sacrificial template method to prepare Al2O3 ceramic cores with strip‐shaped pores using polyamide 6 (PA6) fibers as templates. When the porosity was greater than 30%, the maximum flexural strength reached up to 110.48 MPa. The sacrificial templating method improved the porosity of Al2O3 ceramic cores, forming an internal porous structure that combined strip‐shaped large pores with irregularly shaped small pores. The influences of PA6 fiber content and diameter on the shrinkage, porosity, microstructure, and comprehensive properties of alumina ceramic cores were studied, revealing the mechanism of the coexistence of high porosity and high strength.

Time-dependent model for two-phase flow in ultra-high water-cut reservoirs: Time-varying permeability and relative permeability

For the ultra-high water-cut reservoirs, after long-term water injection exploitation, the physical properties of the reservoir change and the heterogeneity of the reservoir becomes increasingly severe, which further aggravates the spatial difference of the flow field. In this study, the displacement experiments were employed to investigate the variations in core permeability, porosity, and relative permeability after a large amount of water injection. A relative permeability endpoint model was proposed by utilizing the alternating conditional expectation (ACE) transformation to describe the variation in relative permeability based on the experimental data. Based on the time dependent models for permeability and relative permeability, the traditional oil-water two-phase model was improved and discretized using the mimetic finite difference method (MFD). The two cases were launched to confirm the validation of the proposed model. The impact of time-varying physical features on reservoir production performance was studied in a real water flooding reservoir. The experimental results indicate that the overall relative permeability curve shifts to the right as water injection increases. This shift corresponds to a transition towards a more hydrophilic wettability and a decrease in residual oil saturation. The endpoint model demonstrates excellent accuracy and can be applied to time-varying simulations of reservoir physics. The impact of variations in permeability and relative permeability on the reservoir production performance yields two distinct outcomes. The time-varying permeability of the reservoir results in intensified water channeling and poor development effects. On the other hand, the time-varying relative permeability enhances the oil phase seepage capacity, facilitating oil displacement. The comprehensive time-varying behavior is the result of the combined influence of these two parameters, which closely resemble the actual conditions observed in oil field exploitation. The time-varying simulation technique of reservoir physical properties proposed in this paper can continuously and stably characterize the dynamic changes of reservoir physical properties during water drive development. This approach ensures the reliability of the simulation results regarding residual oil distribution.

The Effect of Diagenetic Minerals on the Petrophysical Properties of Sandstone Reservoir: A Case Study of the Upper Shallow Marine Sandstones in the Central Bredasdorp Basin, Offshore South Africa

The upper shallow marine sandstone reservoirs of the Barremian-to-Valanginian formation are the most porous and permeable sandstone reservoirs in the Bredasdorp Basin and an important target for oil and gas exploration. There is a paucity of information on the reservoir characterization and effect of diagenetic mineral studies focusing on the upper shallow marine sandstone reservoirs in the central Bredasdorp Basin; thus, there is a need to investigate the effect of diagenetic minerals and to characterize these reservoirs due to their high porosity and permeability. Datasets, including a suite of geophysical wireline logs, routine core analysis, geological well completion reports, description reports, and core samples, were utilized. A total of 642 core porosity measures, core water saturation, and core permeability data were used for calibration with the log-derived parameters, ranging in depth from 3615 m to 4259 m. Rock samples were prepared for diagenetic mineral analyses, such as thin sections and Scanning electron microscopy, for each well to investigate the presence of diagenetic minerals in the selected reservoir units. The petrophysical analyses showed the results of porosity, volume of clay, water saturation, and permeability, ranging from 9% to 27%, 8.6% to 19.8%, 18.9% to 30.4%, and 0.096 mD to 151.8 mD, respectively, indicating a poor-to-good reservoir quality. Mineralogical analyses revealed that micrite calcite, quartz cement, quartz overgrowth, and authigenic pore-filling and grain-coating clay minerals (illite–smectite and illite) negatively affected intergranular porosity. Porosity-versus-permeability cross plot showed good correlation of 0.86 for ZN1 and 0.83 for ZN3 reservoirs, suggesting that although porosity is the main drive of permeability, there were other geological factors at play, such as diagenetic minerals and compaction.