permeability

Open Access Article

1 - Consolidation Behavior and Geotechnical Parameters of Oil Contaminated Kaolinite Clay
mohammadreza khosravi امیر حمیدی

20.1001.1.22518738.1393.4.8.2.5

Abstract The pollution of soil and underground water with organic and toxic materials is a common environmental problem and oil is one of the most important of them. In the present study, consolidation behavior of clay contaminated with gas oil and kerosene has been More

Abstract The pollution of soil and underground water with organic and toxic materials is a common environmental problem and oil is one of the most important of them. In the present study, consolidation behavior of clay contaminated with gas oil and kerosene has been investigated. The main objective was to determine the parameters associated with the value and rate of settlement of contaminated soil. Influence of various test parameters such as degree of contamination, contaminant type and density of samples were investigated on the consolidation behavior of kaolinite clay. Results show that by increasing the degree of contamination, Compressibility of soil increases while the consolidation coefficient and the permeability coefficient decrease. Manuscript profile

Open Access Article

2 - Study of Petrography & Petrophysics of Permian- Triassic carbonate sediments in Qatar –South Pars Arch
Ali reza Bashari

Abstract Dalan and Kangan Formations are major gas reservoirs in the Persian Gulf and surrounding area. Several supper giant gas fields has been found in the region. In this study reservoir rock types were identified and were divided into four lithostratigraphic zo More

Abstract Dalan and Kangan Formations are major gas reservoirs in the Persian Gulf and surrounding area. Several supper giant gas fields has been found in the region. In this study reservoir rock types were identified and were divided into four lithostratigraphic zones: K1 to K4. Each of the four succeeding zones have been divided into different subzone. This Studies identified different facies-types on the Dalan and Kangan formation in this region. Petrophysical & Petrographycal studies indicate that the best reservoir unites are found in: Dolo-grainstones, Dolowakestones/Packstones and Grainstones. Isopach maps and Depth maps show variations in thickness and depth of different zones in this region. Depth map on top of Kangan formation shows this formation getting deeper toward north- west and south east in the Persian Gulf. Continuity of marker beds in Permian/Triassic sediment and paleontological evidence support diachroneity of these sediments. Manuscript profile

Open Access Article

3 - Numerical calculation of permeability tensor in fractured reservoirs
سیما جلیلی رئوف حسین معماریان محمد رضا رسائی بهزاد تخم چی

Abstract Proper characterization of fracture reservoir is crucial for their sound development plan. It is however very difficult to correctly obtain various fracture reservoir properties such as permeability due to high order of heterogeneity and anisotropy within th More

Abstract Proper characterization of fracture reservoir is crucial for their sound development plan. It is however very difficult to correctly obtain various fracture reservoir properties such as permeability due to high order of heterogeneity and anisotropy within these reservoirs. Classical dual porosity and/or dual permeability models consider a regular fracture network across the reservoir. To improve the concept, we develop a numerical method for tonsorial permeability calculation of blocks with random/disordered fracture distribution. We considered a 2D Cartesian fine grid in which the fractures were defined explicitly with their endpoints coordinates. Applying proper boundary conditions, single phase flow is then solved. Full tensor permeability is then obtained analytically from the calculated flow and pressure fields. The result of our method is compared well with that of the analytical models for simple fracture systems. In addition we reported the permeability tensor values of random fracture networks where no analytical solution is available. Manuscript profile

Open Access Article

4 - Improved LET function and use to modelinrelative permeability curves for one of the Iranian carbonate reservoir rock
غلامرضا بشیری

20.1001.1.22518738.1392.3.5.6.6

Abstruct There are two key method of simulating multi-phase flow experiments. One is the actual estimation of multi-phase flow properties from measured data, and the other is the representation of the analytical functions for relative permeab More

Abstruct There are two key method of simulating multi-phase flow experiments. One is the actual estimation of multi-phase flow properties from measured data, and the other is the representation of the analytical functions for relative permeability and capillary pressure .It is essential that these functions have sufficient degrees of freedom to model the measured data whilst remaining straightforward and easy to communicate. A new smooth and flexible three-parameter analytical correlation for relative permeability is proposed . Results from e.g. unsteady state relative permeability experiments often exhibit behavior which is difficult to model using e.g. Corey correlation. The new correlation influences different parts of the relative permeability curve and thereby captures variable behavior across the entire saturation range .The validity of new correlation is demonstrated by utilizing unsteady-state experiments performed at ambient conditions on core samples from the Southern Iranian reservoir rocks . results show that there is a logical relation between the basic rock properties and tuning parameters against basic parameters, i.e. permeability and porosity , should be found . Knowing the logical correlation and the basic parameters from routine analysis or logs, the tuning parameters and therefore relative permeability curves will be easily calculated. Manuscript profile

Open Access Article

5 - Klinkenberg Permeability Prediction by Using Absolute Gas Permeability in Carbonate Hydrocarbon Reservoir Rocks of South-West of
حمید شریفی گلویک

20.1001.1.22518738.1391.2.4.6.7

Permeability is one of the main parameters in the study of hydrocarbon reservoirs which are needed to be measured correctly. The conventional methods are well testing and direct permeability measurement on the drilled core samples. Absolute air permeability of core p More

Permeability is one of the main parameters in the study of hydrocarbon reservoirs which are needed to be measured correctly. The conventional methods are well testing and direct permeability measurement on the drilled core samples. Absolute air permeability of core plug samples is often measured in the laboratory which is cheap and fast. The absolute air permeability of a rock sample depends on the flowing mean pressure and type of gas and varies with changing them. Hence, measuring liquid permeability of fully saturated core sample or determination of corrected gas permeability which is equivalent to the liquid permeability is essential. This needs to spend enough time and budget. Klinkenberg investigated the effect of gas slippage in porous media and measured absolute permeability of different gases in various mean pressures. He yielded an equation for correcting absolute gas permeability and defining equivalent liquid permeability. The aim of this study was to present some practical relations for determining Klinkenberg corrected gas permeability of carbonate rocks by using their absolute air permeability, which has not been reported yet. For this purpose, Klinkenberg corrected gas permeability of 541 core plugs, with various petrophysical properties from different carbonate formations in the Southwest of Iran was measured. Exponential relations were obtained with very good correlation coefficients. Considering vast petrophysical properties of the studied samples, the yielded equations can be used to predict and determine equivalent liquid permeability of carbonate core samples of Southwest of Iran from their absolute air permeability Manuscript profile

Open Access Article

6 - Secondary porosity index effect on improving approaches permeability estimation from petrophysical logs utilizing artificial intelligent
سجاد کاظم شیرودی مرتضی خانیان

20.1001.1.22518738.1391.2.3.5.4

Abstract Permeability estimation using core data and petrophysical logs is a conventional approach which bears high uncertainty especially in carbonate reservoir characterization. In essence, the problem consists not only due to coring expenses rate, but also ambig More

Abstract Permeability estimation using core data and petrophysical logs is a conventional approach which bears high uncertainty especially in carbonate reservoir characterization. In essence, the problem consists not only due to coring expenses rate, but also ambiguity in finding proper explicit log correlation to core data. Moreover, utilizing the correlated formula in wells without core data can pose errors. In this research the permeability was estimated from conventional petrophysical logs and it was calibrated with permeability obtained from core lab experiments. Applied intelligent systems are the matter of this research for permeability values estimation. To construct permeability estimation model, three techniques have been applied including conventional ANN, the Gonzalez, and Hambalek fuzzy logic techniques. These methods were applied in two wells drilled in Surmeh reservoir in Balal field to establish ANN and to derive a relation between core and well. The models were applied in control well in order to check the reliability and capability of models to estimate representative permeability value. The result showed however three foresaid techniques for permeability estimation were successful the secondary porosity distributed the correlation due to its reduction effect on permeability so that they were not interconnected. Therefore this effect was omitted using secondary porosity index in which the permeability estimation were improved and were estimated close to core value. Manuscript profile

Open Access Article

7 - Estimation of relative permeability curves from capillary pressure data in one of iranian carbonate reservoir
بابک شعبانی عزت اله کاظم زاده

20.1001.1.22518738.1390.1.2.1.1

Relative permeability can be measured directly from cores, but due to problems such as unavailability of experimental results of direct relative permeability measurement, indirect techniques also have been used to calculate relative permeability. One of these methods is More

Relative permeability can be measured directly from cores, but due to problems such as unavailability of experimental results of direct relative permeability measurement, indirect techniques also have been used to calculate relative permeability. One of these methods is estimating relative permeability curves from capillary pressure data that the reliability of this method for approximation of liquid-gas relative permeability curves had thoroughly investigated. However, there is not enough information to conclude which method is the standard one for calculating oil-water relative permeability curves. Various capillary pressure techniques such as the Corey, Brooks-Corey, Li-Purcell and Li-Burdine methods were utilized to calculate oil-water relative permeabilities using the measured oil-water capillary pressure data in drainage process in an oil-wet Carbonate reservoir. Despite wide popularity of Purcell and Burdine methods for calculating relative permeability, new Li-Purcell and LiBurdine methods were used. The calculated results were compared to the experimental data of oil-water relative permeabilities measured in a Carbonate reservoir. The Corey and Brooks-Corey models are shown an acceptable and nearly exact match with the measured oil relative permeability values. However, the Li-Purcell and Li-Burdine models underestimate the values for wetting phase in most cases. It is also worth mentioning that, except Li-Purcell method, the results of all other methods for calculating non-wetting phase relative permeability are almost the same and overestimate the values. Then, rock typing on the basis of pore throat radius at 35% mercury saturation were done and the accuracy of each model were examined for all rock types. Results of this work revealed that calculation of oil-water relative permeability using the capillary pressure data is also a reliable technique in oil-wet carbonate reservoirs. Manuscript profile

Open Access Article

8 - Comparisons of intelligent systems and empirical equation results in permeability prediction: a case study in one of the southern Iranian carbonate reservoirs
الهام عزیز ابادی فراهانی مجتبی رجبی

Prediction of permeability that is one of the most important parameters in oil and gas reservoirs is probably the most challenging issue geologists, petrophysicists, and reservoir engineers have to deal with. This parameter control fluid flow in production stage. The mo More

Prediction of permeability that is one of the most important parameters in oil and gas reservoirs is probably the most challenging issue geologists, petrophysicists, and reservoir engineers have to deal with. This parameter control fluid flow in production stage. The most reliable data of permeability are taken from laboratory analysis of cores. Since coring is a costly and time consuming operation, researchers have tried to predict this parameter from other methods. Empirical equation is one of these methods, but results of these equations are not satisfied for all lithology and reservoirs. So far, several studies have been carried out for the estimation of reservoir parameters using intelligent systems. These studies indicate the successful role of these methods such as fuzzy logic, neuro-fuzzy and genetic algorithms for reservoir characterization. In this study, we try to compare results of these two methods (empirical equations and intelligent systems) for permeability prediction in a carbonate reservoir. For this purpose, petrophysical and core data of four well in a carbonate reservoir in the Southern Iran were used. At first, using empirical equations permeability was calculated for the test well; then using data of three wells, intelligent models were constructed. A forth well (test well) from the field was used to evaluate the models. The results show that fuzzy logic result (with R2= 0.88) is the best method for prediction of permeability in the studied reservoir. Also between empirical equations, result of Wyllie-Rose equation is better than others. Finally we offer the constructed fuzzy model (as a best predictor) for permeability prediction in the studied reservoir. Manuscript profile

Open Access Article

9 - Comparisons of intelligent systems and empirical equation results in permeability prediction: a case study in one of the southern Iranian carbonate reservoirs
Amir Mola jan Hoseyn Memarian

20.1001.1.22518738.1390.1.1.1.9

Prediction of permeability that is one of the most important parameters in oil and gas reservoirs is probably the most challenging issue geologists, petrophysicists, and reservoir engineers have to deal with. This parameter control fluid flow in production stage. The mo More

Prediction of permeability that is one of the most important parameters in oil and gas reservoirs is probably the most challenging issue geologists, petrophysicists, and reservoir engineers have to deal with. This parameter control fluid flow in production stage. The most reliable data of permeability are taken from laboratory analysis of cores. Since coring is a costly and time consuming operation, researchers have tried to predict this parameter from other methods. Empirical equation is one of these methods, but results of these equations are not satisfied for all lithology and reservoirs. So far, several studies have been carried out for the estimation of reservoir parameters using intelligent systems. These studies indicate the successful role of these methods such as fuzzy logic, neuro-fuzzy and genetic algorithms for reservoir characterization. In this study, we try to compare results of these two methods (empirical equations and intelligent systems) for permeability prediction in a carbonate reservoir. For this purpose, petrophysical and core data of four well in a carbonate reservoir in the Southern Iran were used. At first, using empirical equations permeability was calculated for the test well; then using data of three wells, intelligent models were constructed. A forth well (test well) from the field was used to evaluate the models. The results show that fuzzy logic result (with R2= 0.88) is the best method for prediction of permeability in the studied reservoir. Also between empirical equations, result of Wyllie-Rose equation is better than others. Finally we offer the constructed fuzzy model (as a best predictor) for permeability prediction in the studied reservoir. Manuscript profile

Open Access Article

10 - Comparisons of intelligent systems and empirical equation results in permeability prediction: a case study in one of the southern Iranian carbonate reservoirs
الهام عزیز ابادی فراهانی Kazemzadeh Ezatolah ELham Aziz Abadi Farahani

Prediction of permeability that is one of the most important parameters in oil and gas reservoirs is probably the most challenging issue geologists, petrophysicists, and reservoir engineers have to deal with. This parameter control fluid flow in production stage. The mo More

Prediction of permeability that is one of the most important parameters in oil and gas reservoirs is probably the most challenging issue geologists, petrophysicists, and reservoir engineers have to deal with. This parameter control fluid flow in production stage. The most reliable data of permeability are taken from laboratory analysis of cores. Since coring is a costly and time consuming operation, researchers have tried to predict this parameter from other methods. Empirical equation is one of these methods, but results of these equations are not satisfied for all lithology and reservoirs. So far, several studies have been carried out for the estimation of reservoir parameters using intelligent systems. These studies indicate the successful role of these methods such as fuzzy logic, neuro-fuzzy and genetic algorithms for reservoir characterization. In this study, we try to compare results of these two methods (empirical equations and intelligent systems) for permeability prediction in a carbonate reservoir. For this purpose, petrophysical and core data of four well in a carbonate reservoir in the Southern Iran were used. At first, using empirical equations permeability was calculated for the test well; then using data of three wells, intelligent models were constructed. A forth well (test well) from the field was used to evaluate the models. The results show that fuzzy logic result (with R2= 0.88) is the best method for prediction of permeability in the studied reservoir. Also between empirical equations, result of Wyllie-Rose equation is better than others. Finally we offer the constructed fuzzy model (as a best predictor) for permeability prediction in the studied reservoir. Manuscript profile

Open Access Article

11 - The application of clustering methods (MRGC, AHC, DC, SOM) determining permeability carbonate reservoir rocks Ilam Formation in South West Iran
Seyed Ali Moallemi farhad khoshbakht sakineh naghdi

20.1001.1.22518738.1394.5.10.5.9

The permeability of reservoir parameters is important in the calculation and modeling reservoir plays a role. Measured directly via cores taken from the reservoir layer can be achieved. But due to the limited amount of core taken in a field and laboratory methods as wel More

The permeability of reservoir parameters is important in the calculation and modeling reservoir plays a role. Measured directly via cores taken from the reservoir layer can be achieved. But due to the limited amount of core taken in a field and laboratory methods as well as high cost; use indirect methods to determine the wells without core permeability is great value. In this study, using clustering methods using petrophysical logs permeability values were measured and analyzed. For this purpose, petrophysical logs Ilam Formation selection of 8 wells and addition of data measured in vitro permeability 3-ring is used to compare the results. Log permeability effective porosity in the well using the parameters A with the core permeability data, estimates and then check the accuracy of estimates, calculations also took place in other fields of study. In the next step, using clustering method, was estimated permeability. Then the results with experimental data and correlation coefficient, the best method is introduced. Manuscript profile

Open Access Article

12 - Simulation of porosity and permeability reservoir parameters by using Co-Sequential Gaussian Simulation method in one of the oil field in the South West of Iran
Bahareh Fereidooni Mohammad Mokhtari

20.1001.1.22518738.1396.7.13.3.7

Three-dimensional study of petrophysical parameters of hydrocarbon reservoirs such as porosity and permeability is considered as an efficient and effective tool for comprehensive study of reservoirs as well as reservoir management. In this study, which was carried out o More

Three-dimensional study of petrophysical parameters of hydrocarbon reservoirs such as porosity and permeability is considered as an efficient and effective tool for comprehensive study of reservoirs as well as reservoir management. In this study, which was carried out on one of the oil fields in the southwest of Iran, the aim is to simulate the petrophysical parameters of effective porosity and permeability by using Co-Sequential Gaussian Simulation in part of Khatiyah reservoir. With this simulation, a three-dimensional model of petrophysical reservoir parameters can be presented which is important for simulating fluid flow and identifying areas that are prone with higher reservoir quality. For this purpose, effective porosity and permeability logs of seven wells with 3D seismic data and seismic inversion results have been used. After reservoir gridding and creating a structural model, up scaled petrophysical data has entered to model and its own cell. For three-dimensional distribution of effective porosity parameter, due to the correlation of effective porosity and acoustic impedance attribute of seismic inversion, 3D seismic data and up scaled effective porosity logs as the initial data and acoustic impedance attribute of seismic inversion as secondary data have entered in Sequential Gaussian Simulation. In order to simulate permeability, due to the good correlation between effective porosity simulation model and permeability log, simulated porosity as a secondary data and up scaled permeability and 3D seismic data as secondary data have been used. The results of validation indicate the accuracy of the present study and the efficiency of Sequential Gaussian Simulation method in effective porosity and permeability modeling in this reservoir. Manuscript profile

Open Access Article

13 - A case study of carbonate reservoir permeability determination using NMR log in one of the southwestern fields of Iran
Bahram Habibnia

20.1001.1.22518738.1396.7.13.4.8

Permeability is one of the most important parameters for characterization of hydrocarbon reservoirs that has a basic role in almost all of the petroleum engineering problems. Determination of reservoir permeability is usually done in core laboratories in a time consumin More

Permeability is one of the most important parameters for characterization of hydrocarbon reservoirs that has a basic role in almost all of the petroleum engineering problems. Determination of reservoir permeability is usually done in core laboratories in a time consuming process. In the well test, the obtained average permeability is related to the drainage area. Due to cost, these two methods are not performed in the all wells, whereas well logging tools are generally performed in all wells. With progress of well logging tools, some researchers tried to estimate permeability from special well logs such as NMR directly. The data obtained from NMR was used as lithology independent data to estimate the water saturation and porosity, and also for analysis of pore space. One of the important parameters obtained from NMR is the transversal relaxation time (T2). In this work, NMR log measurement in a carbonate field was used to estimate the permeability using Timur, SDR and regression models. The results of the methods were compared against core permeability. The results show that SDR method is more accurate with the accuracy of 44.1% and the error of 23.12%. Manuscript profile

Open Access Article

14 - Effect of sequential pressure on petrophysical properties of carbonate reservoir rocks
Ali Moradzadeh yaser Salimidelshad Ezatollah Kazemzadeh abbas Majdi

20.1001.1.22518738.1397.8.15.2.7

Today, oil industry significantly relies on the precise determination of rock reservoir properties, which reduces the costs and risks of production planning. The reservoir rock always is compacted by pressure drop of the reservoir, which rises effective stress, reservoi More

Today, oil industry significantly relies on the precise determination of rock reservoir properties, which reduces the costs and risks of production planning. The reservoir rock always is compacted by pressure drop of the reservoir, which rises effective stress, reservoir compaction and alterations of reservoir properties. As these pressure variations can considerably affect petrophysical properties, in this study, several carbonate reservoir rock samples with different fabric and porosity type (according to CT scan and Archie classification analysis) subjected to cyclic and short-term loading from 600 to 6000 psi. Their petrophysical and compressive properties including pore volume, permeability and compressibility were measured using CMS-300 apparatus. Moreover, structural analysis and heterogeneity of core samples were analyzed by CT scan images. By performing this study, it will be possible to identify the value of the hysteresis effect on the reservoir rock samples as a result of increasing and decreasing of the pressure during cyclic loading. The obtained results show that, pore volume and permeability are both decreased due to loading, whereas reduction of the permeability is several times than the pore volume ones. Moreover, this reduction of pore volume is less severe in vuggy porous samples that shows the effect of heterogeneity and porosity type on hysteresis. Also, the results obtained from the behavior of the reservoir rock under various pressure conditions can provide a suitable design for gas injection studies to enhance oil recovery and also natural gas storage. Manuscript profile

Open Access Article

15 - Permeability estimation using petrophysical logs and artificial intelligence methods: A case study in the Asmari reservoir of Ahvaz oil field
Abouzar Mohsenipour Bahman Soleimani iman Zahmatkesh Iman Veisi

20.1001.1.22518738.1399.10.20.4.3

Permeability is one of the most important petrophysical parameters that play a key role in the discussion of production and development of hydrocarbon fields. In this study, first, the magnetic resonance log in Asmari reservoir was evaluated and permeability was calcula More

Permeability is one of the most important petrophysical parameters that play a key role in the discussion of production and development of hydrocarbon fields. In this study, first, the magnetic resonance log in Asmari reservoir was evaluated and permeability was calculated using two conventional methods, free fluid model (Coates) and Schlumberger model or mean T2 (SDR). Then, by constructing a simple model of artificial neural network and also combining it with Imperialist competition optimization (ANN-ICA) and particle swarm (ANN-PSO) algorithms, the permeability was estimated. Finally, the results were compared by comparing the estimated COATES permeability and SDR permeability with the actual value, and the estimation accuracy was compared in terms of total squared error and correlation coefficient. The results of this study showed an increase in the accuracy of permeability estimation using a combination of optimization algorithms with artificial neural network. The results of this method can be used as a powerful method to obtain other petrophysical parameters. Manuscript profile

Open Access Article

16 - Designing an Ensemble model for estimating the permeability of a hydrocarbon reservoir by petrophysical lithology Labeling
abbas salahshoor Ahmad Gaeini Alireza shahin mossayeb kamari

20.1001.1.22518738.1399.10.20.6.5

Permeability is one of the important characteristics of oil and gas reservoirs that is difficult to predict. In the present solution, experimental and regression models are used to predict permeability, which includes time and high costs associated with laboratory measu More

Permeability is one of the important characteristics of oil and gas reservoirs that is difficult to predict. In the present solution, experimental and regression models are used to predict permeability, which includes time and high costs associated with laboratory measurements. Recently, machine learning algorithms have been used to predict permeability due to better predictability. In this study, a new ensemble machine learning model for permeability prediction in oil and gas reservoirs is introduced. In this method, the input data are labeled using the lithology information of the logs and divided into a number of categories and each category was modeled by machine learning algorithm. Unlike previous studies that worked independently on models, here we were able to predict the accuracy of such a square mean error by designing a group model using ETR, DTR, GBR algorithms and petrophysical data. Improve dramatically and predict permeability with 99.82% accuracy. The results showed that group models have a great effect on improving the accuracy of permeability prediction compared to individual models and also the separation of samples based on lithology information was a reason to optimize the Trojan estimate compared to previous studies. Manuscript profile

Open Access Article

17 - Permeability improvement calculated from Stoneley-FZI method in Kangan reservoir, one of Iran's gas fields
hossein rezaie yegane doost

10.61186/ispg.38526.11.22.39

20.1001.1.22518738.1400.11.22.2.2

Permeability in fluid flow is for a porous rock, which is exactly what causes the problem. core analysis and well testing are two most commonly used methods of permeability measurement, but in-vitro measurement of permeability by applying core analysis on all wells in a More

Permeability in fluid flow is for a porous rock, which is exactly what causes the problem. core analysis and well testing are two most commonly used methods of permeability measurement, but in-vitro measurement of permeability by applying core analysis on all wells in a specific field is very time consuming and costly and even impossible when dealing with Horizontal wells. Wells testing, on the other hand, is not cost-effective for reasons such as; High costs and zero production during the testing process. Therefore, thanks to their low cost, comprehensiveness and availability, permeability estimation methods developed according to conventional logs land DSI diagrams are of critical importance. Taking this into account, in the present study, permeability was first estimated using multi-resolution graph-based clustering (MRGC) and the results were compared with permeability rates obtained from core analysis. In the second stage, permeability was measured by ST-FZI method and the results were compared with permeability rates obtained from core analysis. In the third stage, the multi-resolution graph-based clustering (MRGC) method was used to improve the permeability calculated by the ST-FZI method and overcome the reservoir heterogeneity. First the flow units were identified, and then the ST-FZI method was applied on each flow unit to calculate permeability and finally the calculated permeabilities were combined to obtain an accurate permeability graph of the studied well. The correlation coefficients of permeability rates estimated via core analysis in the multi-resolution graph-based clustering method (R2 = 77), ST-FZI method (R2 = 47) and improved method (R2 = 84) were measured. The afore-mentioned method was able to improve the permeability calculated in the previous step by 37% and was recognized as the best permeability measurement method in the Kangan reservoir of the well subjected to study. Manuscript profile

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