Journal of Petroleum and Mining Engineering, Dec 5, 2020
Petrophysical properties evaluation of shaly sandstone reservoirs is a challenging task in compar... more Petrophysical properties evaluation of shaly sandstone reservoirs is a challenging task in comparison to clean sand reservoirs. Logging derived porosity in shaly sands requires shale correction and Archie's formula cannot be used in shaly sands for the determination of water saturation, therefore many water saturation models were proposed to get accurate water saturation of shaly sand reservoirs. In this paper, three water saturation models were used; two empirical models (Simandoux and total shale) and one theoretical model (effective medium model). Shale corrected density log was used in all models. The use of computer-generated algorithm, fuzzy log neural network is of increasing interest in the petroleum industry. This paper presents artificial neural network (ANN) as an effective tool for determining porosity and water saturation in shaly sand reservoir using well logging data. ANN technique utilizes the prevailing unknown nonlinear relationship in data between input logging data and output petrophysical parameters. Results of this work showed that ANN can be supplement or replacement of the existing conventional techniques to determine porosity and water saturation using empirical or theoretical water saturation models. Two neural networks were presented to determine porosity and water saturation using GR, resistivity and density logging data and adapted cut off for porosity and water saturation. Water saturation and porosity were determined using conventional techniques and neural network approach for two wells in a shaly sand reservoir. Neural network approach was trained for porosity and water saturation using the available well logging data. The predicted porosity and water saturation values have shown good matching with the core data in the two wells in comparison to the porosity and water saturation derived from the conventional techniques. This work showed that developed neural network (ANN) could provide an accurate porosity and water saturation in shaly sands reservoirs, it is subject to volume of available well logging data.
2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)
Abstract Determination of water saturation in sandstone is vital question to determine initial oi... more Abstract Determination of water saturation in sandstone is vital question to determine initial oil or gas in place in reservoir rocks. Water saturation determination using electrical measurements is mainly on Archie’s formula. Consequently, accuracy of Archie’s formula parameters affects rigorously water saturation values. Determination of Archie’s parameters a, m and n is proceeded by three techniques conventional, CAPE and 3-D. This work introduces the hybrid system of parallel self-organizing neural network (PSONN) targeting an accepted value of Archie’s parameters and consequently reliable water saturation values. This work focuses on Archie’s parameters determination techniques; conventional technique, CAPE technique and 3-D technique and then calculation of water saturation using current. Using the same data, hybrid parallel self-organizing neural network (PSONN) algorithm is used to estimate Archie’s parameters and to predict water saturation. Results have shown that estimated Arche’s parameters m, an and n are highly accepted with statistical analysis indicating that PSONN model has lower statistical error and higher correlation coefficient. This study was conducted using high number of measurement points for 144 core plugs from sandstone reservoir. PSONN algorithm can provide reliable water saturation values and it can supplement or even replace the conventional techniques to determine Archie’s parameters and thereby calculation of water saturation profiles.
The accurate estimation of reservoir porosity plays a vital role in estimating the amount of hydr... more The accurate estimation of reservoir porosity plays a vital role in estimating the amount of hydrocarbon reserves and evaluating the economic potential of a reservoir. It also aids decision making during the exploration and development phases of oil and gas fields. This study evaluates the integration of artificial intelligence techniques, conventional well logs, and core analysis for the accurate prediction of porosity in carbonate reservoirs. In general, carbonate reservoirs are characterized by their complex pore systems, with the wide spatial variation and highly nonlinear nature of their petrophysical properties. Therefore, they require detailed well-log interpretations to accurately estimate their properties, making them good candidates for the application of machine learning techniques. Accordingly, a large database of (2100) well-log records and core-porosity measurements were integrated with four state-of-the-art machine learning techniques (multilayer perceptron artificial...
Geothermal energy is considered one of the most promising energy to replace oil and gas. In order... more Geothermal energy is considered one of the most promising energy to replace oil and gas. In order to enhance this type of energy from the geothermal reservoirs, an appropriate design and evaluation tool is required to assess the stimulation treatment for improving the reservoir permeability. This paper presents an innovative approach to evaluate the well placement and designed stimulation program under thermo poroelastic coupling process using momentum, mass and energy conservation. The proposed approach is applied on a selected volume of Soultz reservoir to assess the permeability enhancement over stimulation period of more than 3 month and fluid circulation period of 14 years. In this method, the change in fracture is caused by shear slippage. The proposed stimulation model evaluates different scenarios of well placement, hydraulic fracture geometry and injection program with an objective of economic heat recovery using different fracture parameters. Results show that the thermal ...
2nd Conference on Geophysics for Mineral Exploration and Mining, 2018
In the evaluation of a petroleum reserve, it is necessary to accurately determine certain petroph... more In the evaluation of a petroleum reserve, it is necessary to accurately determine certain petrophysical properties such as porosity and permeability of the reservoir rocks and rock mechanical properties. Petrophysical properties are key factors in the reservoir description and geomechanical properties are determining parameters in drilling operations and in stimulation and hydraulic fracturing jobs and also the development plans for given reservoir. It is more convenient to use homogenous rock samples with nearly constant initial permeability; however, obtaining such cores is very difficult. In this paper a simulated natural and homogeneous compacted sandstone rock with known physical and petrophysical properties were used. Physical properties of reservoir rocks include pore size distribution; grain size, cementing material concentration, and confining pressure affect rock porosity and permeability. Sound wave velocity was measured using an ultra sound tool on different sandstone core samples. Good correlations have been developed between sound wave velocity (V P and V S) the petrophysical properties mainly porosity and permeability. Significant correlations have been found between seismic wave velocity (V P , V S and V P/ V S) and mechanical parameters namely Young's modulus, shear modulus, bulk modulus and Poison's ratio for sandstone core samples. This study has been carried out on dry core samples and core samples with different water saturations and results showed that there are changes in the correlation between seismic wave velocity and mechanical and petrophysical properties as function of water saturation change from dry rock to water wet rock.
International Journal of Mechanical Engineering and Robotics Research, 2019
Over the years, several enhanced oil recovery techniques were developed in order to recover the r... more Over the years, several enhanced oil recovery techniques were developed in order to recover the residual oil trapped in the reservoir. Conventional EOR techniques rely on injection of fluids and chemicals into the reservoir to improve recovery. Unconventional methods of enhancing oil recovery such as the use of flow divergent and flow pulsation have emerged. One of the unconventional EOR techniques of interest is the application of seismic wave. Despite the fact that EOR by seismic wave has shown some potential in pilot field studies as well as laboratory experiments, the working mechanism of this technique is not well understood. In this study, we aim to investigate the ability of the seismic wave excitation in releasing a trapped oil globule in a pore doublet model. We studied the ability of this model to trap oil in an imbibition process. However, the trapping did not occur. Therefore, we generated an oil globule that was already isolated in pore 2 of the pore doublet model. The inlet velocity causing the oil globule trapping was tested and determined for the given pore doublet model dimensions. A sinusoidal wave vibration was applied to the model as the seismic excitation. The positive half of the wave cycle resulted in a an adverse pressure gradient, which led to a reversed flow of the fluids in the domain. Consequently, we started the excitation at the negative half of the wave cycle, which applies a favorable pressure gradient. The favorable pressure gradient resulted in a viscous pressure that overcame the capillary pressure holding the oil globule. Consequently, the oil globule was squeezed out of pore 2 and mobilized. The trapped oil globule was successfully mobilized by the effect of the seismic wave excitation.
IOP Conference Series: Materials Science and Engineering, 2018
The characterization of carbonate formations is challenging as compared to sandstones, yet carbon... more The characterization of carbonate formations is challenging as compared to sandstones, yet carbonate reservoirs hold over 60% of the world's hydrocarbon reserves. Carbonate reservoirs exhibit a high level of heterogeneity at every scale; from core to field. To be able to manage heterogeneity for reservoir modelling, the formation has to be discretized into a few rock types, each of which having somewhat similar flow properties. Recently, the interest in extending the rock-typing approaches is increasing with the aim to identify the potential layers in complex lithology like carbonates. The approach becomes more rigorous if the geological description is coordinated with petrophysical data, an approach that has been followed in this study. The hydraulic flow units in Arab-D formation were identified and interpreted using both geological facies and petrophysical data. All three methods; histogram analysis, normal probability plot and least-squared regression were utilized to determine the optimum number of hydraulic flow units across Arab-D carbonate formation. Published routine core analysis data from ten wells of Arab-D formation was analyzed and six optimum hydraulic flow units were identified. The average porosity and average permeability of each hydraulic flow unit was then computed. The results were found to be in good agreement with the geological facies data of the Arab-D formation, thus validating the identified flow units.
Gas compressibility factor is necessary in most natural gas engineering calculations. The most co... more Gas compressibility factor is necessary in most natural gas engineering calculations. The most common sources of zfactor values are experimental measurements, equation of state and empirical correlations. There are more than twenty correlations available with two variables for calculating the z-factor from fitting Standing-Katz chart values in EOS or through fitting technique. The theory of corresponding states dictates that the Z-factor can be uniquely defined as function of reduced pressure and temperature. Natural gases frequently contain material other than hydrocarbon components, such as nitrogen, carbon dioxide and hydrogen sulfide. Hydrocarbon gases are classified as sweet or sour depending on the hydrogen sulfide content. Both sweet and sour gases may contain nitrogen, carbon dioxide or both. The compositions of most natural gases are hydrocarbon of the same family (paraffin hydrocarbons), so the correlation of this type is possible but containing non-hydrocarbon on the gases, make the prediction difficult. This paper focuses on evaluating the correlations which calculate gas compressibility factor for natural gas reservoirs contains non-hydrocarbon components. It is found that gas pseudo-critical temperature decreases with the increase of N 2 and H 2 S. Also, it is observed that in the tested gas reservoirs which contain C 7+ by Stewart Mixing Rules and Kay's there are some deviation on z factor between two methods that became negligible by using the correction method for non-hydrocarbon.
Archives of Petroleum & Environmental Biotechnology, 2016
Today, the global energy industry is facing a growing number of uncertainties, including price vo... more Today, the global energy industry is facing a growing number of uncertainties, including price volatility, rising demand and increasing costs which are leading to greater pressures for energy producers and consumers alike. Furthermore, almost a quarter of the world population has no access to modern energy and little hope of joining the world's energy consumers any time soon and unconventional energy resources can answer this question. Conventional and unconventional oil and gas come from the same original geologic formations multiple layers in sedimentary basins all over the world and the recovery rate may also vary significantly from one reservoir to another. Unlike conventional reservoirs, unconventional gas reservoirs typically have very fine grain rock texture and complex geological and petrophysical system. Unconventional oil is petroleum extracted using techniques other than the conventional oil well method. Oil industries across the globe are investing in unconventional oil sources due to the increasing scarcity of conventional oil reserves. Unconventional oil and gas reserves include: 1) Tight oil and gas reservoirs, 2) Oil shale is an organic-rich fine-grained sedimentary rock containing significant amounts of kerogen from which technology can extract liquid hydrocarbons (shale oil) and combustible shale gas and 3) Unconventional gas reserves refer to sources of natural gas production that are, in a given era and location, considered to be new and different such as coalbed methane and synthetic natural gas. This study presents comprehensive understanding of the latest advances in the exploitation and development of unconventional resources. It addresses all aspects of the exploitation and development process, from data mining and accounting to drilling, completion, stimulation, production, and environmental issues. It offers in-depth coverage of sub-surface measurements. This study concentrates on how to develop the conventional hydrocarbon reserve to keep its global production as effective as possible and how to activate the unconventional oil and gas reserve and proposing technology to optimize the recovery of the unconventional reserves as energy resources in 21 st century either compliment or new energy resources to the conventional hydrocarbon reserve.
Rock physical parameters such as porosity and water saturation play an important role in the mech... more Rock physical parameters such as porosity and water saturation play an important role in the mechanical behavior of hydrocarbon reservoir rocks. A valid and reliable prediction of these parameters from seismic data is essential for reservoir characterization, management, and also geomechanical modeling. In this paper, the application of conventional methods such as Bayesian inversion and computational intelligence methods, namely support vector regression (SVR) optimized by particle swarm optimization (PSO) and adaptive network-based fuzzy inference systemsubtractive clustering method (ANFIS-SCM), is demonstrated to predict porosity and water saturation. The prediction abilities offered by Bayesian inversion, SVR-PSO, and ANFIS-SCM were presented using a synthetic dataset and field data available from a gas carbonate reservoir in Iran. In these models, seismic pre-stack data and attributes were utilized as the input parameters, while the porosity and water saturation were the output parameters. Various statistical performance indexes were utilized to compare the performance of those estimation models. The results achieved indicate that the ANFIS-SCM model has strong potential for indirect estimation of porosity and water saturation with high degree of accuracy and robustness from seismic data and attributes in both synthetic and real cases of this study.
Analysis of heterogeneous gas sand reservoirs is one of the most difficult problems. These reserv... more Analysis of heterogeneous gas sand reservoirs is one of the most difficult problems. These reservoirs usually produce from multiple layers with different permeability and complex formation, which is often enhanced by natural fracturing. Therefore, using new well logging techniques like NMR or a combination of NMR and conventional openhole logs, as well as developing new interpretation methodologies are essential for improved reservoir characterization. Nuclear magnetic resonance (NMR) logs differ from conventional neutron, density, sonic and resistivity logs because the NMR measurements provide mainly lithology independent detailed porosity and offer a good evaluation of the hydrocarbon potential. NMR logs can also be used to determine formation permeability and capillary pressure. In heterogeneous reservoirs classical methods face problems in determining accurately the relevant petrophysical parameters. Applications of artificial intelligence have recently made this challenge a pos...
Journal of Applied Biotechnology & Bioengineering, 2017
P c , critical pressure; P pr , pseudo-reduced pressure; P pc , pseudo critical pressure; P' pc ,... more P c , critical pressure; P pr , pseudo-reduced pressure; P pc , pseudo critical pressure; P' pc , corrected pseudo critical pressure; T c , critical temperature; T pr , pseudo reduced temperature; T pc , pseudo-critical temperature; T' pc , corrected pseudo critical temperature; Ɛ, pseudo-critical temperature adjustment factor; CO 2 , carbon dioxide; SK, standing and Katz; DK, dranchuk-abou-kassem; SBV, stewart-burkhardt-voo
Journal of Petroleum and Mining Engineering, Dec 5, 2020
Petrophysical properties evaluation of shaly sandstone reservoirs is a challenging task in compar... more Petrophysical properties evaluation of shaly sandstone reservoirs is a challenging task in comparison to clean sand reservoirs. Logging derived porosity in shaly sands requires shale correction and Archie's formula cannot be used in shaly sands for the determination of water saturation, therefore many water saturation models were proposed to get accurate water saturation of shaly sand reservoirs. In this paper, three water saturation models were used; two empirical models (Simandoux and total shale) and one theoretical model (effective medium model). Shale corrected density log was used in all models. The use of computer-generated algorithm, fuzzy log neural network is of increasing interest in the petroleum industry. This paper presents artificial neural network (ANN) as an effective tool for determining porosity and water saturation in shaly sand reservoir using well logging data. ANN technique utilizes the prevailing unknown nonlinear relationship in data between input logging data and output petrophysical parameters. Results of this work showed that ANN can be supplement or replacement of the existing conventional techniques to determine porosity and water saturation using empirical or theoretical water saturation models. Two neural networks were presented to determine porosity and water saturation using GR, resistivity and density logging data and adapted cut off for porosity and water saturation. Water saturation and porosity were determined using conventional techniques and neural network approach for two wells in a shaly sand reservoir. Neural network approach was trained for porosity and water saturation using the available well logging data. The predicted porosity and water saturation values have shown good matching with the core data in the two wells in comparison to the porosity and water saturation derived from the conventional techniques. This work showed that developed neural network (ANN) could provide an accurate porosity and water saturation in shaly sands reservoirs, it is subject to volume of available well logging data.
2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)
Abstract Determination of water saturation in sandstone is vital question to determine initial oi... more Abstract Determination of water saturation in sandstone is vital question to determine initial oil or gas in place in reservoir rocks. Water saturation determination using electrical measurements is mainly on Archie’s formula. Consequently, accuracy of Archie’s formula parameters affects rigorously water saturation values. Determination of Archie’s parameters a, m and n is proceeded by three techniques conventional, CAPE and 3-D. This work introduces the hybrid system of parallel self-organizing neural network (PSONN) targeting an accepted value of Archie’s parameters and consequently reliable water saturation values. This work focuses on Archie’s parameters determination techniques; conventional technique, CAPE technique and 3-D technique and then calculation of water saturation using current. Using the same data, hybrid parallel self-organizing neural network (PSONN) algorithm is used to estimate Archie’s parameters and to predict water saturation. Results have shown that estimated Arche’s parameters m, an and n are highly accepted with statistical analysis indicating that PSONN model has lower statistical error and higher correlation coefficient. This study was conducted using high number of measurement points for 144 core plugs from sandstone reservoir. PSONN algorithm can provide reliable water saturation values and it can supplement or even replace the conventional techniques to determine Archie’s parameters and thereby calculation of water saturation profiles.
The accurate estimation of reservoir porosity plays a vital role in estimating the amount of hydr... more The accurate estimation of reservoir porosity plays a vital role in estimating the amount of hydrocarbon reserves and evaluating the economic potential of a reservoir. It also aids decision making during the exploration and development phases of oil and gas fields. This study evaluates the integration of artificial intelligence techniques, conventional well logs, and core analysis for the accurate prediction of porosity in carbonate reservoirs. In general, carbonate reservoirs are characterized by their complex pore systems, with the wide spatial variation and highly nonlinear nature of their petrophysical properties. Therefore, they require detailed well-log interpretations to accurately estimate their properties, making them good candidates for the application of machine learning techniques. Accordingly, a large database of (2100) well-log records and core-porosity measurements were integrated with four state-of-the-art machine learning techniques (multilayer perceptron artificial...
Geothermal energy is considered one of the most promising energy to replace oil and gas. In order... more Geothermal energy is considered one of the most promising energy to replace oil and gas. In order to enhance this type of energy from the geothermal reservoirs, an appropriate design and evaluation tool is required to assess the stimulation treatment for improving the reservoir permeability. This paper presents an innovative approach to evaluate the well placement and designed stimulation program under thermo poroelastic coupling process using momentum, mass and energy conservation. The proposed approach is applied on a selected volume of Soultz reservoir to assess the permeability enhancement over stimulation period of more than 3 month and fluid circulation period of 14 years. In this method, the change in fracture is caused by shear slippage. The proposed stimulation model evaluates different scenarios of well placement, hydraulic fracture geometry and injection program with an objective of economic heat recovery using different fracture parameters. Results show that the thermal ...
2nd Conference on Geophysics for Mineral Exploration and Mining, 2018
In the evaluation of a petroleum reserve, it is necessary to accurately determine certain petroph... more In the evaluation of a petroleum reserve, it is necessary to accurately determine certain petrophysical properties such as porosity and permeability of the reservoir rocks and rock mechanical properties. Petrophysical properties are key factors in the reservoir description and geomechanical properties are determining parameters in drilling operations and in stimulation and hydraulic fracturing jobs and also the development plans for given reservoir. It is more convenient to use homogenous rock samples with nearly constant initial permeability; however, obtaining such cores is very difficult. In this paper a simulated natural and homogeneous compacted sandstone rock with known physical and petrophysical properties were used. Physical properties of reservoir rocks include pore size distribution; grain size, cementing material concentration, and confining pressure affect rock porosity and permeability. Sound wave velocity was measured using an ultra sound tool on different sandstone core samples. Good correlations have been developed between sound wave velocity (V P and V S) the petrophysical properties mainly porosity and permeability. Significant correlations have been found between seismic wave velocity (V P , V S and V P/ V S) and mechanical parameters namely Young's modulus, shear modulus, bulk modulus and Poison's ratio for sandstone core samples. This study has been carried out on dry core samples and core samples with different water saturations and results showed that there are changes in the correlation between seismic wave velocity and mechanical and petrophysical properties as function of water saturation change from dry rock to water wet rock.
International Journal of Mechanical Engineering and Robotics Research, 2019
Over the years, several enhanced oil recovery techniques were developed in order to recover the r... more Over the years, several enhanced oil recovery techniques were developed in order to recover the residual oil trapped in the reservoir. Conventional EOR techniques rely on injection of fluids and chemicals into the reservoir to improve recovery. Unconventional methods of enhancing oil recovery such as the use of flow divergent and flow pulsation have emerged. One of the unconventional EOR techniques of interest is the application of seismic wave. Despite the fact that EOR by seismic wave has shown some potential in pilot field studies as well as laboratory experiments, the working mechanism of this technique is not well understood. In this study, we aim to investigate the ability of the seismic wave excitation in releasing a trapped oil globule in a pore doublet model. We studied the ability of this model to trap oil in an imbibition process. However, the trapping did not occur. Therefore, we generated an oil globule that was already isolated in pore 2 of the pore doublet model. The inlet velocity causing the oil globule trapping was tested and determined for the given pore doublet model dimensions. A sinusoidal wave vibration was applied to the model as the seismic excitation. The positive half of the wave cycle resulted in a an adverse pressure gradient, which led to a reversed flow of the fluids in the domain. Consequently, we started the excitation at the negative half of the wave cycle, which applies a favorable pressure gradient. The favorable pressure gradient resulted in a viscous pressure that overcame the capillary pressure holding the oil globule. Consequently, the oil globule was squeezed out of pore 2 and mobilized. The trapped oil globule was successfully mobilized by the effect of the seismic wave excitation.
IOP Conference Series: Materials Science and Engineering, 2018
The characterization of carbonate formations is challenging as compared to sandstones, yet carbon... more The characterization of carbonate formations is challenging as compared to sandstones, yet carbonate reservoirs hold over 60% of the world's hydrocarbon reserves. Carbonate reservoirs exhibit a high level of heterogeneity at every scale; from core to field. To be able to manage heterogeneity for reservoir modelling, the formation has to be discretized into a few rock types, each of which having somewhat similar flow properties. Recently, the interest in extending the rock-typing approaches is increasing with the aim to identify the potential layers in complex lithology like carbonates. The approach becomes more rigorous if the geological description is coordinated with petrophysical data, an approach that has been followed in this study. The hydraulic flow units in Arab-D formation were identified and interpreted using both geological facies and petrophysical data. All three methods; histogram analysis, normal probability plot and least-squared regression were utilized to determine the optimum number of hydraulic flow units across Arab-D carbonate formation. Published routine core analysis data from ten wells of Arab-D formation was analyzed and six optimum hydraulic flow units were identified. The average porosity and average permeability of each hydraulic flow unit was then computed. The results were found to be in good agreement with the geological facies data of the Arab-D formation, thus validating the identified flow units.
Gas compressibility factor is necessary in most natural gas engineering calculations. The most co... more Gas compressibility factor is necessary in most natural gas engineering calculations. The most common sources of zfactor values are experimental measurements, equation of state and empirical correlations. There are more than twenty correlations available with two variables for calculating the z-factor from fitting Standing-Katz chart values in EOS or through fitting technique. The theory of corresponding states dictates that the Z-factor can be uniquely defined as function of reduced pressure and temperature. Natural gases frequently contain material other than hydrocarbon components, such as nitrogen, carbon dioxide and hydrogen sulfide. Hydrocarbon gases are classified as sweet or sour depending on the hydrogen sulfide content. Both sweet and sour gases may contain nitrogen, carbon dioxide or both. The compositions of most natural gases are hydrocarbon of the same family (paraffin hydrocarbons), so the correlation of this type is possible but containing non-hydrocarbon on the gases, make the prediction difficult. This paper focuses on evaluating the correlations which calculate gas compressibility factor for natural gas reservoirs contains non-hydrocarbon components. It is found that gas pseudo-critical temperature decreases with the increase of N 2 and H 2 S. Also, it is observed that in the tested gas reservoirs which contain C 7+ by Stewart Mixing Rules and Kay's there are some deviation on z factor between two methods that became negligible by using the correction method for non-hydrocarbon.
Archives of Petroleum & Environmental Biotechnology, 2016
Today, the global energy industry is facing a growing number of uncertainties, including price vo... more Today, the global energy industry is facing a growing number of uncertainties, including price volatility, rising demand and increasing costs which are leading to greater pressures for energy producers and consumers alike. Furthermore, almost a quarter of the world population has no access to modern energy and little hope of joining the world's energy consumers any time soon and unconventional energy resources can answer this question. Conventional and unconventional oil and gas come from the same original geologic formations multiple layers in sedimentary basins all over the world and the recovery rate may also vary significantly from one reservoir to another. Unlike conventional reservoirs, unconventional gas reservoirs typically have very fine grain rock texture and complex geological and petrophysical system. Unconventional oil is petroleum extracted using techniques other than the conventional oil well method. Oil industries across the globe are investing in unconventional oil sources due to the increasing scarcity of conventional oil reserves. Unconventional oil and gas reserves include: 1) Tight oil and gas reservoirs, 2) Oil shale is an organic-rich fine-grained sedimentary rock containing significant amounts of kerogen from which technology can extract liquid hydrocarbons (shale oil) and combustible shale gas and 3) Unconventional gas reserves refer to sources of natural gas production that are, in a given era and location, considered to be new and different such as coalbed methane and synthetic natural gas. This study presents comprehensive understanding of the latest advances in the exploitation and development of unconventional resources. It addresses all aspects of the exploitation and development process, from data mining and accounting to drilling, completion, stimulation, production, and environmental issues. It offers in-depth coverage of sub-surface measurements. This study concentrates on how to develop the conventional hydrocarbon reserve to keep its global production as effective as possible and how to activate the unconventional oil and gas reserve and proposing technology to optimize the recovery of the unconventional reserves as energy resources in 21 st century either compliment or new energy resources to the conventional hydrocarbon reserve.
Rock physical parameters such as porosity and water saturation play an important role in the mech... more Rock physical parameters such as porosity and water saturation play an important role in the mechanical behavior of hydrocarbon reservoir rocks. A valid and reliable prediction of these parameters from seismic data is essential for reservoir characterization, management, and also geomechanical modeling. In this paper, the application of conventional methods such as Bayesian inversion and computational intelligence methods, namely support vector regression (SVR) optimized by particle swarm optimization (PSO) and adaptive network-based fuzzy inference systemsubtractive clustering method (ANFIS-SCM), is demonstrated to predict porosity and water saturation. The prediction abilities offered by Bayesian inversion, SVR-PSO, and ANFIS-SCM were presented using a synthetic dataset and field data available from a gas carbonate reservoir in Iran. In these models, seismic pre-stack data and attributes were utilized as the input parameters, while the porosity and water saturation were the output parameters. Various statistical performance indexes were utilized to compare the performance of those estimation models. The results achieved indicate that the ANFIS-SCM model has strong potential for indirect estimation of porosity and water saturation with high degree of accuracy and robustness from seismic data and attributes in both synthetic and real cases of this study.
Analysis of heterogeneous gas sand reservoirs is one of the most difficult problems. These reserv... more Analysis of heterogeneous gas sand reservoirs is one of the most difficult problems. These reservoirs usually produce from multiple layers with different permeability and complex formation, which is often enhanced by natural fracturing. Therefore, using new well logging techniques like NMR or a combination of NMR and conventional openhole logs, as well as developing new interpretation methodologies are essential for improved reservoir characterization. Nuclear magnetic resonance (NMR) logs differ from conventional neutron, density, sonic and resistivity logs because the NMR measurements provide mainly lithology independent detailed porosity and offer a good evaluation of the hydrocarbon potential. NMR logs can also be used to determine formation permeability and capillary pressure. In heterogeneous reservoirs classical methods face problems in determining accurately the relevant petrophysical parameters. Applications of artificial intelligence have recently made this challenge a pos...
Journal of Applied Biotechnology & Bioengineering, 2017
P c , critical pressure; P pr , pseudo-reduced pressure; P pc , pseudo critical pressure; P' pc ,... more P c , critical pressure; P pr , pseudo-reduced pressure; P pc , pseudo critical pressure; P' pc , corrected pseudo critical pressure; T c , critical temperature; T pr , pseudo reduced temperature; T pc , pseudo-critical temperature; T' pc , corrected pseudo critical temperature; Ɛ, pseudo-critical temperature adjustment factor; CO 2 , carbon dioxide; SK, standing and Katz; DK, dranchuk-abou-kassem; SBV, stewart-burkhardt-voo
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