List of articles (by subject) Petrophysics
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Open Access Article
1 - Analysis of Electrical Rock Type Bangestan Reservoir in Marun Oil Field
Abouzar Mohsenipour Bahman Soleimani Ehsan Abharakpour Ghodratollah NikkhahStudies of the electrical Rock Type a very important role in the development process plays a field.In these studies, theporo-perm Cores data and well log data used for reservoir simulations. In the present research, the flow of four flow units was determined in the res MoreStudies of the electrical Rock Type a very important role in the development process plays a field.In these studies, theporo-perm Cores data and well log data used for reservoir simulations. In the present research, the flow of four flow units was determined in the reservoir using porosity and permeability data from well logging core by regional index method. In some wells, using well logging the basic model of electrical rocktype was determined with three methods of MRGC, SOM, and DYNAMIC. The determined facies by different methods were correlated with the flow unit. Finally, SOM method was selected, which has the best concordance. The initially created electrofacieswere reduced to 4 electrofacies due to the similarity of some parameters such as effective porosity and gamma logging. To ensure the accuracy of the electrical rock type by neural networks, these electrofacies were correlated with capillary pressure data. After confirming the determined electrofacies by capillary pressure, these facies were propagated in other wells in this field. This created a model, which was able to separate different parts of the reservoir. In this model, different parts of the reservoir were determined in terms of reservoir quality. Manuscript profile -
Open Access Article
2 - 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 MokhtariThree-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 MoreThree-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
3 - Modeling of Horizontal Extent of Pay zone Layer on the Basis of Petrophysical Parameters Variations Using Indicator Kriging Method in one of the Southwest Iranian Oil Fields
Farnaz Saberi Farhad Mohammad Torab Kioumars TaheriDetermining the position of the production zone is one of the best ways to reduce drilling costs as well as quick access to the reservoir and optimal production of hydrocarbon resources. The purpose of this study, is to estimate the porosity, water saturation and thickn MoreDetermining the position of the production zone is one of the best ways to reduce drilling costs as well as quick access to the reservoir and optimal production of hydrocarbon resources. The purpose of this study, is to estimate the porosity, water saturation and thickness of an oil field in Iran’s southwestern Basin , and ultimately to reach the production zone. Therefore, according to the data obtained from 76 wells of this field, variation of reservoir petrophysical parameters were modeled with variogram operation and using Geostatistical methods. By using ordinary Kriging method, the values of the parameters were estimated in the whole field. Subsequently, by using the indicator kriging method, the field boundaries were separated in order to obtain the exact area of the oil zone and the volume of oil in place and finally by considering the 80% probability level, The definite boundary of the presence of the production zone was determined in the block model and In this zone the volume of reservoir’s hydrocarbon was estimated about 147/5 million cubic foot. Manuscript profile -
Open Access Article
4 - Comparison of ΔlogR and mineralogy-based methods in estimating organic carbon content of Pabdeh formation in Ahwaz and Rag-e Sefid oilfields
Mahdi Shafie Seyed Hassan Tabatabaei Morteza Tabaei Nader Fathianpour Ali OperaOne of the most common and relatively accurate methods for determining the amount of organic carbon in rocks in the oil and gas exploration potential is the Pyrolysis family, a standard example of which is the first rock pyrolysis method. Based on the study of the core, MoreOne of the most common and relatively accurate methods for determining the amount of organic carbon in rocks in the oil and gas exploration potential is the Pyrolysis family, a standard example of which is the first rock pyrolysis method. Based on the study of the core, this method explores the potential of oil and gas resources in rocks. One of the important and valuable parameters in determining the potential of oil and gas resources is the determination of TOC. The purpose and motivation of this research is to compare the ΔlogR method and the mineralogy-based method for calculating the total amount of organic carbon in the source rock. It has the desired accuracy and relatively low cost. The fields studied in this study are two fields of Ahwaz and Rag-e sefid. These fields are among the potential fields of southwestern Iran for more detailed investigation and estimation of organic carbon content. In this research, software studies have been performed through IP software, using which the petrophysical data of each field have been calculated and compared, and finally, its results have been compared with actual TOC values. Input data in the mineralogical data method include density log, neutron porosity log and gamma log, and input data in the ΔlogR method include acoustic and resistivity logs. According to the fields, the most appropriate methods (in terms of R2) in Ahwaz and rag-e sefid fields are the mineralogical data method and the ΔlogR method, respectively. Also, in terms of cost, precision and accuracy parameters, the best method discussed in this research is R2 mineralogical data in Ahwaz and Rag-e sefid, 0.94 and 0.61, respectively. After this, the ΔlogR method comes second. Manuscript profile -
Open Access Article
5 - 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 VeisiPermeability 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 MorePermeability 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
6 - Designing an Ensemble model for estimating the permeability of a hydrocarbon reservoir by petrophysical lithology Labeling
abbas salahshoor Ahmad Gaeini Alireza shahin mossayeb kamariPermeability 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 MorePermeability 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
7 - Permeability improvement calculated from Stoneley-FZI method in Kangan reservoir, one of Iran's gas fields
hossein rezaie yegane doostPermeability 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 MorePermeability 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