Periodicals of Engineering and Natural Sciences, 2019
Water saturation is among important petrophysical properties of rock used to assess the initial h... more Water saturation is among important petrophysical properties of rock used to assess the initial hydrocarbon in an exploration well. This paper studies five formations from the main limestone carbonate reservoir belong to an exploration field located in the northern part of Iraq. Additionally, we review water saturation models to choose the best one to this exploration field. There are several techniques of water saturation determination applied to estimate reservoir quality. Archie equation is considered one of these techniques; however, applying this model in shale formation gives errors in water saturation estimation. Three different models of water saturation, Simandoux, Indonesian, and Modified Simandoux, were chosen to estimate water saturation in shale beds. Our results demonstrated that the water saturation obtained from the Archie equation is higher than all other models. Furthermore, the Indonesian water saturation model is higher than Simandoux and Modified Simandoux water saturation models. The outcome of the Simandoux and Modified Simandoux were lower than those of Archie and Indonesian models. The accuracy of the water saturation model is evaluated by tends to be close to that of Archie water saturation model is considered negative. The reason is there are no production test results or saturation data from core analysis. The lowest average of water saturation is found in Simandoux and Modified Simandoux models. Depending on water saturation value, the good positive model is modified Simandoux or Simandoux model due to its lowest average value of water saturation. Besides, it can be used for further reservoir studies.
13th International Conference on Recent Development in Engineering, Science, Humanities and Management, 2020
The estimation of the hydrocarbon reserve is an essential task for any production and exploration... more The estimation of the hydrocarbon reserve is an essential task for any production and exploration operations.Any exploration and production projects economic viability are based on the accuracy of their reserves estimates, which are made utilizing various input parameters as example porosity, water saturation and formation factor.These parameters can be derived from petrophysical data and well testes data.Because of uncertainties in the estimate of such parameter, both deterministic and stochastic methods must be used for estimating reserves. The input parameters for deterministic methods are certain individual value and thus the output represents single value. Because reservoir parameters are not standardized across entire reservoir, uncertainty reduce as data set increases. In such cases, stochastic approaches used, since random sampling can produce millions of random numbers and by properly analyzing this data set, these problems can be resolved very quickly.Simulation of Monte Carlo is an epitome of a stochastic method of this kind for estimating hydrocarbon resources.The success of a Monte Carlo simulation stochastic hydrocarbon reserve estimate depends on selecting model parameters andprecise controlling and understanding of model parameters that are important for successful outcomes. This study predicted how statistical distribution of porosity and water saturation affect the original simulated oil values for one Iraqi oil field, and discussed the results.
International Journal of Enhanced Research in Science, Technology & Engineering, 2016
This paper presents results of a study conducted to determine and evaluate the petrophysical prop... more This paper presents results of a study conducted to determine and evaluate the petrophysical properties of "Main Limestone" reservoir units in north Iraq with a view to understand their effects on the reservoirs hydrocarbon prospect and oil productivity of the field. The evaluated properties include porosity, fluid saturation and net / gross thickness, which are obtained from wire-line logs. A full set of wire-line logs including of gamma ray, resistivity, neutron and density logs for three wells from Bai-Hassan oil field were analyzed for reservoir characterization of the field. The analyses carried out involves description of lithologies, identification of reservoirs and fluid types, wells correlation and determination of petrophysical parameters of identified reservoirs. Petrophysical parameters of "Main Limestone" reservoir rocks revealed that the reservoir unit (B) has the better properties compared with the other units. The majority of total porosity is primary porosity through the whole succession within the studied area. The water saturation is affected significantly by increasing the volume of shale, which was often greater than 10 %.
Periodicals of Engineering and Natural Sciences, 2020
This paper introduces a comprehensive petrophysical study to re-evaluate reservoir quality of 'Ma... more This paper introduces a comprehensive petrophysical study to re-evaluate reservoir quality of 'Main Limestone' reservoir units for one Iraqi oil field using modern software and techniques. In this study, we discussed many subjects, such as petrophysical effects on hydrocarbon accumulation, hydrocarbon mobility, and hydrocarbon productivity of the field. The determining reservoir properties include formation porosity, hydrocarbon, and water saturation, as well as net/gross thickness ratio, which is determined depending on wire-line logs data. For reservoir description, full sets of well log data such as gamma-ray, resistivity, neutron log, form three wells were interpreted and analyzed. The performed analysis includes many subjects such as lithology description, reservoir identification, reservoir fluid type identification, well correlation, reservoir porosity, saturation (for hydrocarbon and water) determination. Petrophysical properties parameter of 'Main Limestone' reservoir rocks exposed that unit 'B' has better properties compared with other units. The most overall porosity type was primary porosity through the entire formations and units. Water saturation and shale volume estimations indicated the water saturation significantly affected by an increase in the shale quantity if shale volume exceeds 10%.
Periodicals of Engineering and Natural Sciences, 2020
One crucial parameter related to subsurface formations fluid flowing is the rock permeability. Ge... more One crucial parameter related to subsurface formations fluid flowing is the rock permeability. Generally, rock permeability reflects the formation capability to transmit fluid. Its significance reflected through several methods existing utilized to predict it, including rock core measurements, empirical correlation, statistical techniques, and other methods. The best and more exact permeability findings are acquired in the laboratory from core plug cored from a subsurface formation. Unfortunately, these experiments are expensive and tedious in comparison to the electrical and electronic survey techniques as wireline well logging methods, for example, not exclusively. The current study compares and discusses different methods and approaches for predicting permeability via wireline logs data. These approaches include empirical correlations, non-parametric statistical approaches, flow zone indicator FZI approach. In this research, we introduced a comparatively new process to predict permeability by the combination of FZI method and the artificial neural networks method. All these approaches are performed using well logs data to the non-homogenous formation, and findings are placed in comparison with permeability from laboratory experiments, which is regarded to be standard. Several statistical criteria, such as ANOVA test and regression analysis, were used to determine the reliability of calculated permeability results. 1. Introduction Formation permeability represents a formation property that reflects the capability of fluids (gas or liquid) flowing through the formation. Where high permeability value will allow liquids to flow quickly through rocks. Permeability represents significant [1] formation property and most complex to predict and determine all petrophysical characteristics [2]. An exact permeability estimation is substantial since it is an important parameter that controls the direction of liquids flowing and the rate of liquids flow through formation. Laboratory experiments of permeability estimations are traditionally utilized for evaluating permeability. Kozeny (1927) [3] and Archie (1941) [4] were among the first scientists who calculated permeability based upon electrical measurements applied on core samples. Often, these experiments are costly and tedious, or they are rare either because of the high cost of these types of investigations. Therefore, different attempts were made over the years to predict permeability utilizing various methods. One of the relatively reasonable and readily available sources for estimation permeability was wireline well logging techniques. Several models and correlations were developed to achieve this objective, such as Leverett, Tixier, Wyllie-Rose, Timur, and Coates-Dumanoir [5-9]. Using statistical methods to predict permeability depending on well log data was developed in the nineties of the last century, such as Lin et al. work, Balan et al. work, and Zhang et al., work [10-12]. The flexibility of statistical approaches is that it predicts an expected permeability value depending on to set of data resulted from well logs and analytical parameters. In models with general practical application, several researchers [4-9] have attempted to capture the complexities of permeability behaviour. As this research leading to better explaining the permeability influence variables, they indicate that it is a misconception to consider a "general" association between permeability and wireline log variables. However, core permeability data exists in many cases for research; statistical models
International Research Journal of Engineering, IT & Scientific Research, 2020
The complexity of porous media makes the classical methods used to study hydrocarbon reservoirs i... more The complexity of porous media makes the classical methods used to study hydrocarbon reservoirs inaccurate and insufficient to predict the performance and behavior of the reservoir. Recently, fluid flow simulation and modeling used to decrease the risks in the decision of the evaluation of the reservoir and achieve the best possible economic feasibility. This study deals with a brief review of the fundamental equations required to simulate fluid flow through porous media. In this study, we review the derivative of partial differential equations governing the fluid flow through pores media. The physical interpretation of partial differential equations (especially the pressures diffusive nature) and discretization with finite differences are studied. We restricted theoretic research to slightly compressible fluids, single-phase flow through porous media, and these are sufficient to show various typical aspects of subsurface flow numerical simulation. Moreover, only spatial and time discretization with finite differences will be considered. In this study, a mathematical model is formulated to express single-phase fluid flow in a one-dimensional porous medium. The formulated mathematical model is a partial differential equation of pressure change concerning distance and time. Then this mathematical model converted into a numerical model using the finite differences method. The numerical solution and the mechanism of pressure diffusivity are presented to simulate the studied model.
Iraqi Journal of Chemical and Petroleum Engineering, 2018
Geologic modeling is the art of constructing a structural and stratigraphic model of a reservoir ... more Geologic modeling is the art of constructing a structural and stratigraphic model of a reservoir from analyses and interpretations of seismic data, log data, core data, etc. [1]. A static reservoir model typically involves four main stages, these stages are Structural modeling, Stratigraphic modeling, Lithological modeling and Petrophysical modeling [2]. Ismail field is exploration structure, located in the north Iraq, about 55 km northwest of Kirkuk city, to the northwest of the Bai Hassan field, the distance between the Bai Hassan field and Ismael field is about one kilometer [3]. Tertiary period reservoir sequences (Main Limestone), which comprise many economically important units particularly reservoir pay zone, in Ismail field are belong to middle Miocene age and Oligocene age, which includes six formations, Jeribe, Bajwan, Baba, Baba/palani and Palani formation. The information of Ismail field such as final well report, drill stem test, completion test and well logs data also previous studies and results of core data, indicated that hydrocarbons are accumulated in the Baba formation. The main purpose of this study is to make use of all the available sets of data acquired from Ismail field to build a static geological model for Baba formation in Ismail field to get full description for this reservoir. The most important phase of a reservoir study is probably the definition of a static model of the reservoir rock, given both the large number of activities involved, and its impact on the end results. As we know, the production capacity of a reservoir depends on its geometrical/structural and petrophysical characteristics. The availability of a representative static model is therefore an essential condition for the subsequent dynamic modeling phase. A static reservoir study typically involves four main stages, carried out by experts in the various disciplines, these stages are Structural modeling, Stratigraphic modeling, Lithological modeling and Petrophysical modeling [2]. 2-Model Design Petrel 2009 software was chosen to build geological model for exploration Ismail field. Petrel is a software application package for subsurface interpretation and modeling, allowing building and updating reliable subsurface models. It is a latest reservoirs modeling software recently deployed by schlumberger information solutions Inc. For the purpose of this study, a data base was created within petrel, clearly delineating the different information and data needed to complete the study. The geological, and petrophysical data were imported to petrel within the main data base. This made it possible to generate and visualize the imported data in 2D as well as 3D. The work flow design used for the study and wide range of functional tools in the petrel software include: 3D visualization, well correlation, 3D mapping, and 3D grid design for geology simulation, well log up scaling, petrophysical modeling, data analysis, and volume calculation. 3-Data Preparation Data preparation is the basis for geologic model. This geologic model building chiefly applies software of petrel. On the basis of software demand and research area characteristic, the data prepare for this 3D-geological model are well heads, well tops, well logs (Raw data and CPI), and core analysis.
Periodicals of Engineering and Natural Sciences, 2019
Water saturation is among important petrophysical properties of rock used to assess the initial h... more Water saturation is among important petrophysical properties of rock used to assess the initial hydrocarbon in an exploration well. This paper studies five formations from the main limestone carbonate reservoir belong to an exploration field located in the northern part of Iraq. Additionally, we review water saturation models to choose the best one to this exploration field. There are several techniques of water saturation determination applied to estimate reservoir quality. Archie equation is considered one of these techniques; however, applying this model in shale formation gives errors in water saturation estimation. Three different models of water saturation, Simandoux, Indonesian, and Modified Simandoux, were chosen to estimate water saturation in shale beds. Our results demonstrated that the water saturation obtained from the Archie equation is higher than all other models. Furthermore, the Indonesian water saturation model is higher than Simandoux and Modified Simandoux water saturation models. The outcome of the Simandoux and Modified Simandoux were lower than those of Archie and Indonesian models. The accuracy of the water saturation model is evaluated by tends to be close to that of Archie water saturation model is considered negative. The reason is there are no production test results or saturation data from core analysis. The lowest average of water saturation is found in Simandoux and Modified Simandoux models. Depending on water saturation value, the good positive model is modified Simandoux or Simandoux model due to its lowest average value of water saturation. Besides, it can be used for further reservoir studies.
13th International Conference on Recent Development in Engineering, Science, Humanities and Management, 2020
The estimation of the hydrocarbon reserve is an essential task for any production and exploration... more The estimation of the hydrocarbon reserve is an essential task for any production and exploration operations.Any exploration and production projects economic viability are based on the accuracy of their reserves estimates, which are made utilizing various input parameters as example porosity, water saturation and formation factor.These parameters can be derived from petrophysical data and well testes data.Because of uncertainties in the estimate of such parameter, both deterministic and stochastic methods must be used for estimating reserves. The input parameters for deterministic methods are certain individual value and thus the output represents single value. Because reservoir parameters are not standardized across entire reservoir, uncertainty reduce as data set increases. In such cases, stochastic approaches used, since random sampling can produce millions of random numbers and by properly analyzing this data set, these problems can be resolved very quickly.Simulation of Monte Carlo is an epitome of a stochastic method of this kind for estimating hydrocarbon resources.The success of a Monte Carlo simulation stochastic hydrocarbon reserve estimate depends on selecting model parameters andprecise controlling and understanding of model parameters that are important for successful outcomes. This study predicted how statistical distribution of porosity and water saturation affect the original simulated oil values for one Iraqi oil field, and discussed the results.
International Journal of Enhanced Research in Science, Technology & Engineering, 2016
This paper presents results of a study conducted to determine and evaluate the petrophysical prop... more This paper presents results of a study conducted to determine and evaluate the petrophysical properties of "Main Limestone" reservoir units in north Iraq with a view to understand their effects on the reservoirs hydrocarbon prospect and oil productivity of the field. The evaluated properties include porosity, fluid saturation and net / gross thickness, which are obtained from wire-line logs. A full set of wire-line logs including of gamma ray, resistivity, neutron and density logs for three wells from Bai-Hassan oil field were analyzed for reservoir characterization of the field. The analyses carried out involves description of lithologies, identification of reservoirs and fluid types, wells correlation and determination of petrophysical parameters of identified reservoirs. Petrophysical parameters of "Main Limestone" reservoir rocks revealed that the reservoir unit (B) has the better properties compared with the other units. The majority of total porosity is primary porosity through the whole succession within the studied area. The water saturation is affected significantly by increasing the volume of shale, which was often greater than 10 %.
Periodicals of Engineering and Natural Sciences, 2020
This paper introduces a comprehensive petrophysical study to re-evaluate reservoir quality of 'Ma... more This paper introduces a comprehensive petrophysical study to re-evaluate reservoir quality of 'Main Limestone' reservoir units for one Iraqi oil field using modern software and techniques. In this study, we discussed many subjects, such as petrophysical effects on hydrocarbon accumulation, hydrocarbon mobility, and hydrocarbon productivity of the field. The determining reservoir properties include formation porosity, hydrocarbon, and water saturation, as well as net/gross thickness ratio, which is determined depending on wire-line logs data. For reservoir description, full sets of well log data such as gamma-ray, resistivity, neutron log, form three wells were interpreted and analyzed. The performed analysis includes many subjects such as lithology description, reservoir identification, reservoir fluid type identification, well correlation, reservoir porosity, saturation (for hydrocarbon and water) determination. Petrophysical properties parameter of 'Main Limestone' reservoir rocks exposed that unit 'B' has better properties compared with other units. The most overall porosity type was primary porosity through the entire formations and units. Water saturation and shale volume estimations indicated the water saturation significantly affected by an increase in the shale quantity if shale volume exceeds 10%.
Periodicals of Engineering and Natural Sciences, 2020
One crucial parameter related to subsurface formations fluid flowing is the rock permeability. Ge... more One crucial parameter related to subsurface formations fluid flowing is the rock permeability. Generally, rock permeability reflects the formation capability to transmit fluid. Its significance reflected through several methods existing utilized to predict it, including rock core measurements, empirical correlation, statistical techniques, and other methods. The best and more exact permeability findings are acquired in the laboratory from core plug cored from a subsurface formation. Unfortunately, these experiments are expensive and tedious in comparison to the electrical and electronic survey techniques as wireline well logging methods, for example, not exclusively. The current study compares and discusses different methods and approaches for predicting permeability via wireline logs data. These approaches include empirical correlations, non-parametric statistical approaches, flow zone indicator FZI approach. In this research, we introduced a comparatively new process to predict permeability by the combination of FZI method and the artificial neural networks method. All these approaches are performed using well logs data to the non-homogenous formation, and findings are placed in comparison with permeability from laboratory experiments, which is regarded to be standard. Several statistical criteria, such as ANOVA test and regression analysis, were used to determine the reliability of calculated permeability results. 1. Introduction Formation permeability represents a formation property that reflects the capability of fluids (gas or liquid) flowing through the formation. Where high permeability value will allow liquids to flow quickly through rocks. Permeability represents significant [1] formation property and most complex to predict and determine all petrophysical characteristics [2]. An exact permeability estimation is substantial since it is an important parameter that controls the direction of liquids flowing and the rate of liquids flow through formation. Laboratory experiments of permeability estimations are traditionally utilized for evaluating permeability. Kozeny (1927) [3] and Archie (1941) [4] were among the first scientists who calculated permeability based upon electrical measurements applied on core samples. Often, these experiments are costly and tedious, or they are rare either because of the high cost of these types of investigations. Therefore, different attempts were made over the years to predict permeability utilizing various methods. One of the relatively reasonable and readily available sources for estimation permeability was wireline well logging techniques. Several models and correlations were developed to achieve this objective, such as Leverett, Tixier, Wyllie-Rose, Timur, and Coates-Dumanoir [5-9]. Using statistical methods to predict permeability depending on well log data was developed in the nineties of the last century, such as Lin et al. work, Balan et al. work, and Zhang et al., work [10-12]. The flexibility of statistical approaches is that it predicts an expected permeability value depending on to set of data resulted from well logs and analytical parameters. In models with general practical application, several researchers [4-9] have attempted to capture the complexities of permeability behaviour. As this research leading to better explaining the permeability influence variables, they indicate that it is a misconception to consider a "general" association between permeability and wireline log variables. However, core permeability data exists in many cases for research; statistical models
International Research Journal of Engineering, IT & Scientific Research, 2020
The complexity of porous media makes the classical methods used to study hydrocarbon reservoirs i... more The complexity of porous media makes the classical methods used to study hydrocarbon reservoirs inaccurate and insufficient to predict the performance and behavior of the reservoir. Recently, fluid flow simulation and modeling used to decrease the risks in the decision of the evaluation of the reservoir and achieve the best possible economic feasibility. This study deals with a brief review of the fundamental equations required to simulate fluid flow through porous media. In this study, we review the derivative of partial differential equations governing the fluid flow through pores media. The physical interpretation of partial differential equations (especially the pressures diffusive nature) and discretization with finite differences are studied. We restricted theoretic research to slightly compressible fluids, single-phase flow through porous media, and these are sufficient to show various typical aspects of subsurface flow numerical simulation. Moreover, only spatial and time discretization with finite differences will be considered. In this study, a mathematical model is formulated to express single-phase fluid flow in a one-dimensional porous medium. The formulated mathematical model is a partial differential equation of pressure change concerning distance and time. Then this mathematical model converted into a numerical model using the finite differences method. The numerical solution and the mechanism of pressure diffusivity are presented to simulate the studied model.
Iraqi Journal of Chemical and Petroleum Engineering, 2018
Geologic modeling is the art of constructing a structural and stratigraphic model of a reservoir ... more Geologic modeling is the art of constructing a structural and stratigraphic model of a reservoir from analyses and interpretations of seismic data, log data, core data, etc. [1]. A static reservoir model typically involves four main stages, these stages are Structural modeling, Stratigraphic modeling, Lithological modeling and Petrophysical modeling [2]. Ismail field is exploration structure, located in the north Iraq, about 55 km northwest of Kirkuk city, to the northwest of the Bai Hassan field, the distance between the Bai Hassan field and Ismael field is about one kilometer [3]. Tertiary period reservoir sequences (Main Limestone), which comprise many economically important units particularly reservoir pay zone, in Ismail field are belong to middle Miocene age and Oligocene age, which includes six formations, Jeribe, Bajwan, Baba, Baba/palani and Palani formation. The information of Ismail field such as final well report, drill stem test, completion test and well logs data also previous studies and results of core data, indicated that hydrocarbons are accumulated in the Baba formation. The main purpose of this study is to make use of all the available sets of data acquired from Ismail field to build a static geological model for Baba formation in Ismail field to get full description for this reservoir. The most important phase of a reservoir study is probably the definition of a static model of the reservoir rock, given both the large number of activities involved, and its impact on the end results. As we know, the production capacity of a reservoir depends on its geometrical/structural and petrophysical characteristics. The availability of a representative static model is therefore an essential condition for the subsequent dynamic modeling phase. A static reservoir study typically involves four main stages, carried out by experts in the various disciplines, these stages are Structural modeling, Stratigraphic modeling, Lithological modeling and Petrophysical modeling [2]. 2-Model Design Petrel 2009 software was chosen to build geological model for exploration Ismail field. Petrel is a software application package for subsurface interpretation and modeling, allowing building and updating reliable subsurface models. It is a latest reservoirs modeling software recently deployed by schlumberger information solutions Inc. For the purpose of this study, a data base was created within petrel, clearly delineating the different information and data needed to complete the study. The geological, and petrophysical data were imported to petrel within the main data base. This made it possible to generate and visualize the imported data in 2D as well as 3D. The work flow design used for the study and wide range of functional tools in the petrel software include: 3D visualization, well correlation, 3D mapping, and 3D grid design for geology simulation, well log up scaling, petrophysical modeling, data analysis, and volume calculation. 3-Data Preparation Data preparation is the basis for geologic model. This geologic model building chiefly applies software of petrel. On the basis of software demand and research area characteristic, the data prepare for this 3D-geological model are well heads, well tops, well logs (Raw data and CPI), and core analysis.
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