The application of nanotechnology in the oil industry has become a useful approach in oil product... more The application of nanotechnology in the oil industry has become a useful approach in oil production. The main objective of this study is to investigate the effect of nanofluids on the recovery of heavy crude oil compared with waterflooding. The nanofluids are prepared by the addition of pure and mixed nanoparticles-silicon oxide, aluminum oxide, nickel oxide, and titanium oxide-at different concentrations to the formation water. The prepared nanofluids were screened to determine the suitable type for the heavy oil and rock samples subjected to the study. The effect of nanofluids on the interfacial tension and viscosity of emulsion were also investigated. Nanofluid-flooding tests were performed on a heavy-oil sample of 17.45 API by use of Berea sandstone core samples with average air permeability of 184 md, liquid permeability of 60 md, and porosity of 20%. After selection of the optimum type of nanofluid, additional tests were performed including effect on asphaltene precipitation by use of a flow-assurance system. Results from the experiments show that the aluminum oxide nanofluid at concentration of 0.05 wt% reduced the emulsion viscosity by 25%. The mixed nanofluid of silicon and aluminum oxides at 0.05 wt% has shown the highest incremental oil recovery among the other nanofluids. It is expected to be the best type of chemical flooding because of its performance in reservoir condition (high pressure, temperature, and water salinity) and its capability to oppose asphaltene precipitation. Experiments Materials. The physical properties of the four nanoparticles used in this study are reported in Table 1. Aluminum oxide (Al 2 O 3) and nickel oxide (NiO) were provided by Skyspring Nanomaterials Inc. (Houston, Texas). Silicon oxide (SiO 2) and titanium oxide (TiO 2) were supplied by MKnano (Missisauga, Ontario, Canada). The microscopic structures were observed by use of a field-emission scanning-electron microscope (FESEM) with a magnification of 25,000X, as shown in Fig. 1. The raw materials were used without any future treatment. The heavy-crude-oil sample was collected from an oil field in specially designed glass-stoppered bottles of 2.5-L capacity and was stored at 20 C. The oil sample was mixed with an emulsion breaker (commercial-grade Nalco demulsifier) and centrifuged to remove the traces of basic sediments and water by use of ASTM D4007 (1995) and finally
The effect of injection brine salinity on the displacement efficiency of low water salinity flood... more The effect of injection brine salinity on the displacement efficiency of low water salinity flooding was investigated using sea water at 35,000 ppm, and two field injection waters, namely, Um-Eradhuma (UER) at 171,585 ppm and simsima (SIM) at 243,155 ppm. The salinity of the employed waters was varied from original salinity to 1,000 ppm and used in the displacement of oil in selected core samples. The results of this set of experiments revealed that UER salinity of 5,000 ppm is the optimum system for the candidate reservoir. UER original water and its optimum water were then used in this project as the high and low salinity waters in the CO 2-WAG flooding experiments. Displacement efficiencies were evaluated under three injection modes: carbon dioxide WAG miscible flooding (CO 2-WAG, 1:1, 2:1, and 1:2), continuous CO 2 injection, and waterflood. The WAG performance parameters, such as secondary and tertiary displacement efficiencies, CO 2 flood utilization factor, and CO 2 performance during different WAG flood cycles were determined. To insure miscibility condition between the injected gas and the employed oil, all of the flooding experiments were conducted at 3,200 psia (which is 300 psia above the minimum miscibility pressure of CO 2 and used oil) and 250°F. Experimental results indicated that core length is a critical parameter in determining the optimum WAG process, and that a minimum core length of 29 cm is required to insure the generation of miscibility before breakthrough in CO2-WAG flooding experiments. On the other hand, core length had no effect on the performance of the low salinity flooding experiments. Using single core flooding low salinity CO 2-WAG of 1:2 flooding produced an improvement in the displacement efficiency of 29 % over the high salinity system. Also, composite core flooding experiments showed that the high salinity CO 2-2:1 WAG achieved a displacement efficiency of 98 %. These results indicate that achieving miscibility at the reservoir conditions is the dominant mechanism and that low salinity will have no major effect on the displacement efficiency of CO 2-Miscible WAG flooding. Results also indicate that oil recovery during different CO2-WAG cycles is a function of WAG ratios.
Journal of Geophysics and Engineering, Jul 8, 2010
This study automates a type-curve technique for estimating the rock pore-geometric factor (λ) fro... more This study automates a type-curve technique for estimating the rock pore-geometric factor (λ) from capillary pressure measurements. The pore-geometric factor is determined by matching the actual rock capillary pressure versus wetting-phase saturation (P c-S w) profile with that obtained from the Brooks and Corey model (1966 J. Irrigation Drainage Proc. Am. Soc. Civ. Eng. 61-88). The pore-geometric factor values are validated by comparing the actual measured rock permeability to the permeability values estimated using the Wyllie and Gardner model (1958 World Oil (April issue) 210-28). Petrophysical data for both carbonate and sandstone rocks, along with the pore-geometric factor derived from the type-curve matching, are used in a discriminant analysis for the purpose of developing a model for rock typing. The petrophysical parameters include rock porosity (φ), irreducible water saturation (S wi), permeability (k), the threshold capillary-entry-pressure (P d), a pore-shape factor (β), and a flow-impedance parameter (n) which is a property that reflects the flow impedance caused by the irreducible wetting-phase saturation. The results of the discriminant analysis indicate that five of the parameters (φ, k, P d , λ and n) are sufficient for classifying rocks according to two broad lithology classes: sandstones and carbonates. The analysis reveals the existence of a significant discriminant function that is mostly sensitive to the pore-geometric factor values (λ). A discriminant-analysis classification model that honours both static and dynamic petrophysical rock properties is, therefore, introduced. When tested on two distinct data sets, the discriminant-analysis model was able to predict the correct lithofacies for approximately 95% of the tested samples. A comprehensive database of the experimentally collected petrophysical properties of 215 carbonate and sandstone rocks is provided with this study.
Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles, Jun 13, 2013
Re´sume´-Pre´diction de la pression miscibilite´minimum (MMP) du CO 2 en utilisant un algorithme ... more Re´sume´-Pre´diction de la pression miscibilite´minimum (MMP) du CO 2 en utilisant un algorithme base´sur l'ACE (Alternating Conditional Expectation)-L'injection de gaz miscibles est une des me´thodes les plus utilise´es pour ame´liorer la re´cupe´ration d'hydrocarbures (Enhanced Oil Recovery, EOR). En raison du couˆt important de cette technique, un haut degre´de pre´cision est requis pour pre´dire le processus. Une telle pre´cision comprend les parame`tres de de´pistage pre´liminaires pour le de´placement de gaz miscible, la pression minimale de miscibilite(Minimum Miscibility Pressure, MMP) et de la disponibilite´du gaz. Toutes les me´thodes de mesure du MMP conventionnelles sont des processus consommateurs de temps reque´rant de ce fait des couˆts importants. Par conse´quent, afin de re´pondre aux demandes de re´ponses rapides du secteur, une approche non parame´trique base´e sur l'algorithme ACE (Alternating Conditional Expectation) due a`Brieman et Friedman [Brieman L., Friedman J.H. (1985) J. Am. Stat. Assoc. 80, 391, 580-619], est utilise´e dans cette e´tude pour estimer les MMP. Cet algorithme recherche les transformations optimales d'un ensemble de facteurs pre´dictifs (ici C
This research presents a visualizing method to estimate capillary pressure relationship from cent... more This research presents a visualizing method to estimate capillary pressure relationship from centrifuge experiments using spinning disk geometry. The visualizing method consists of continuously recording the local saturation variation by using a video camera while centrifuging at any given time. The experimental procedure consists of recording sample images and fluid production at any given time and then determines local saturation by a simple correlation between production and gray level. Thus, a modified core holder was designed to adopt the new approach. The core holder must be transparent for visual interpretation of the experiments and strong to account for the high pressure during experiments. The traditional geometry for the centrifuge method is well-established in the industry. However, the benefits of using the spinning disk approach consist of validity of zero capillary pressure at the outlet face, ability of measuring local saturation at any given time, possibility of estimating drainage and spontaneous imbibition capillary pressure, and consideration of radial effect. Results of 24 rock samples show a good agreement between the capillary pressure relationships obtained from the new approach and those obtained from the porous-plate method. Relative errors of the capillary pressure were less than 5% for most samples. Furthermore, the entry pressures and irreducible wetting phase saturations obtained by this approach were agreed with the porous plate method.
Journal of Petroleum Exploration and Production Technology, Jun 2, 2015
Viscosity and density are important physical properties of crude oil. However, no practical theor... more Viscosity and density are important physical properties of crude oil. However, no practical theory exists for the calculation of these properties for heavy oil at elevated temperatures. The principal objective of this paper is to obtain exact models that can successfully predict these two important fluid properties covering a wide range of temperatures. In this study, heavy oil density was predicted from API and temperature, and then the predicted values of the densities were used in the second step to develop the viscosity correlation. A total of 30 heavy oil samples of different API gravities ranging from 11.7 to 18.8 were tested. Viscosity and density were measured in the temperature range from 20 to 160°C. The accuracy of the experimental density data was determined using Standing and Katz method. Published correlations were also used to evaluate the experimental viscosity data. The comparison between the experimental data and the predicted values indicated that the proposed model successfully predicted the experimental data with an average absolute relative error of less than 8 % and correlation coefficients (R 2) of 0.97 and 0.92 at normal and high temperatures, respectively. The proposed model and the literature models were tested on heavy oil samples. It was found that it is not possible to generalize a correlation for the heavy oil viscosity using only API and temperature. However, the proposed model significantly minimizes the relative error and increases the correlation between the predicted and experimental data compared with other published methods.
Journal of Petroleum Science and Engineering, Oct 1, 2016
The dependence of the shear wave velocity (V s) of water-saturated reservoir rocks on petrophysic... more The dependence of the shear wave velocity (V s) of water-saturated reservoir rocks on petrophysical parameters was investigated. Two general regression neural network (GRNN) models were developed to predict V s of sandstones, shaly sands, and carbonate rocks as a function of the compressional velocity (V p), grain density (ρ g), clay content, porosity (ϕ), permeability (k), and the cementation exponent (m) at a fixed effective stress and frequency. A set of 59 sample measurements of clean and dirty sandstones and carbonate rocks was used to train and test the GRNN models. The first model predicts V s as a function of ϕ, k, ρ g , m, and the clay content expressed as a percentage. This GRNN model was trained using two data sets consisting of 80% and 70% of the data, respectively. The truncated portions of the data were used as blind test sets to validate the GRNN model. The analysis reveals that the porosity, clay content, grain density, permeability, and cementation exponent are essential variables for capturing the variance of the shear wave velocity. Porosity appears to be the most important variable for estimating V s , and the grain density is the second most important variable. The GRNN model was able to estimate V s from both the training and the blind test data sets within an average absolute error of approximately 6%. Models from the literature that predict V s as a function of porosity and clay content appear to be specific to particular lithologies, such as sandstones or carbonates. Modeling V s by including parameters such as grain density, cementation exponent, and permeability in addition to porosity and clay content appears to capture the dominating physics that affects V s. By including this comprehensive set of input parameters, we have developed a generalized model to predict the shear wave velocity V s value for all types of lithology, such as carbonates and clean and dirty siliciclastics. A second GRNN model predicts V s as a function of only V p. This model was also trained using two data sets that consisted of 80% and 70% of the data, respectively. Similar to the first model, the truncated portions of the data were used as blind test sets to validate this GRNN model. The second GRNN model was able to estimate V s as a function of V p from the training sets within an average absolute error of approximately 4% while the average absolute error was 3% for the blind test data sets. The compressional velocity alone appears to be sufficient to predict the shear wave velocity.
Journal of Petroleum Exploration and Production Technology, Aug 20, 2015
This study introduces a general regression neural network (GRNN) model consisting of a one-pass l... more This study introduces a general regression neural network (GRNN) model consisting of a one-pass learning algorithm with a parallel structure for estimating the minimum miscibility pressure (MMP) of crude oil as a function of crude oil composition and temperature. The GRNN model was trained with 91 samples and was successfully validated with a blind testing data set of 22 samples. The MMP for six of these data samples was experimentally measured at the Petroleum Fluid Research Centre at Kuwait University. The remaining data consisted of experimental MMP data collected from the literature. The GRNN model was used to estimate the MMP from the training data set with an average absolute error of 0.2 %. The GRNN model was used to predict the MMP for the blind test data set with an average absolute error of 3.3 %. The precision of the introduced model and models in the literature was evaluated by comparing the predicted MMP values with the measured MMP values and using training and testing data sets. The GRNN model significantly outperformed the prominent models that have been published in the literature and commonly used for estimating MMP. The use of the GRNN model was reliable over a large range of crude oil compositions, impurities, and temperature conditions. The GRNN model provides a cost-effective alternative for estimating the MMP, which is commonly, measured using experimental displacement procedures that are costly and time consuming. The results provided in this study support the use of artificial neural networks for predicting the MMP of CO 2. Keywords General regression neural network Á Enhanced oil recovery Á Minimum miscibility pressure Á Carbon dioxide Á Gas injection
Journal of Petroleum Science and Engineering, Feb 1, 2005
In conventional centrifuge tests, the relative permeability of just one phase is obtainedthe phas... more In conventional centrifuge tests, the relative permeability of just one phase is obtainedthe phase with the lowest mobility. As a result, centrifuge tests are most often used for obtaining relative permeabilities of a liquid in a gas-liquid pair. In order to obtain more relative permeability insight from a centrifuge test, data in addition to production data must be obtained. In this paper, we discuss measurements of evolving air-water saturation profiles for a spinning-disk geometry. The saturation profiles were obtained by processing video images of the spinning rock sample, which was held in a transparent rotor assembly. Relative permeabilities of the water and the air were obtained by historymatching the saturation profiles and the production data. Critical gas saturation can be approximately estimated from the saturation profiles. In addition to the relative permeability results, we show a comparison of capillary pressures measured with the centrifuge (standard geometry and the spinning disk geometry), with a porous plate, and with mercury injection. For one of the samples, all four methods agreed well. For most samples, the centrifuge and the porous-plate methods agreed well.
An onshore oil well in Japan, referred to as Well M-1 in this paper, experienced a serious emulsi... more An onshore oil well in Japan, referred to as Well M-1 in this paper, experienced a serious emulsion problem soon after the introduction of artificial lift using a hydraulic jet pump. Even though the problem was resolved after switching to a new demulsifier, it is possible that the operator could experience another emulsion problem as the production condition changes in the future and accordingly, the new demulsifier becomes less effective. Therefore, a laboratory case study was conducted to understand not only the cause of the emulsion problem encountered, but also the relative magnitude of several factors affecting emulsion stability. Knowing the conditions that lead to the emulsion problem helps in understanding how to remove the emulsion and in designing intervention treatments to restore long-term well productivity. At first, the oil and brine samples from Well M-1 were mixed and agitated to form emulsion, and subsequently emulsion stability was evaluated. Subsequently, the mixing conditions were altered to investigate the individual impact on the emulsion stability: (1a) replace Well M-1 oil with another field's oil, (1b) replace Well M-1 brine with another field's brine, (2) change concentrations of asphaltene, (3) change concentrations of wax, (4) change concentrations of toluene insolubles, (5) vary temperature between 20 and 70 C, (6) vary shear stress (rotational speed between 3,500 and 15,000 rev/min), and (7) vary water cut between zero and 100%. The result of the emulsion stability in every test was different. All the above factors showed some impact on emulsion stability, except for brine composition and toluene insolubles, which had little impact on emulsion stability in this study. Operationally speaking, because it was found that the emulsion was stabilized by multiple factors, multiple preventative approaches are required to sustain stable production, free of emulsion. Oil Water Emulsion Fig. 1-Photograph of the fluid sample collected from the water tank (left) and microscopic view of the emulsion phase (right).
SPE/DGS Saudi Arabia Section Technical Symposium and Exhibition, 2011
This paper was selected for presentation by an SPE program committee following review of informat... more This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The ...
The application of nanotechnology in the oil industry has become a useful approach in oil product... more The application of nanotechnology in the oil industry has become a useful approach in oil production. The main objective of this study is to investigate the effect of nanofluids on the recovery of heavy crude oil compared with waterflooding. The nanofluids are prepared by the addition of pure and mixed nanoparticles-silicon oxide, aluminum oxide, nickel oxide, and titanium oxide-at different concentrations to the formation water. The prepared nanofluids were screened to determine the suitable type for the heavy oil and rock samples subjected to the study. The effect of nanofluids on the interfacial tension and viscosity of emulsion were also investigated. Nanofluid-flooding tests were performed on a heavy-oil sample of 17.45 API by use of Berea sandstone core samples with average air permeability of 184 md, liquid permeability of 60 md, and porosity of 20%. After selection of the optimum type of nanofluid, additional tests were performed including effect on asphaltene precipitation by use of a flow-assurance system. Results from the experiments show that the aluminum oxide nanofluid at concentration of 0.05 wt% reduced the emulsion viscosity by 25%. The mixed nanofluid of silicon and aluminum oxides at 0.05 wt% has shown the highest incremental oil recovery among the other nanofluids. It is expected to be the best type of chemical flooding because of its performance in reservoir condition (high pressure, temperature, and water salinity) and its capability to oppose asphaltene precipitation. Experiments Materials. The physical properties of the four nanoparticles used in this study are reported in Table 1. Aluminum oxide (Al 2 O 3) and nickel oxide (NiO) were provided by Skyspring Nanomaterials Inc. (Houston, Texas). Silicon oxide (SiO 2) and titanium oxide (TiO 2) were supplied by MKnano (Missisauga, Ontario, Canada). The microscopic structures were observed by use of a field-emission scanning-electron microscope (FESEM) with a magnification of 25,000X, as shown in Fig. 1. The raw materials were used without any future treatment. The heavy-crude-oil sample was collected from an oil field in specially designed glass-stoppered bottles of 2.5-L capacity and was stored at 20 C. The oil sample was mixed with an emulsion breaker (commercial-grade Nalco demulsifier) and centrifuged to remove the traces of basic sediments and water by use of ASTM D4007 (1995) and finally
The effect of injection brine salinity on the displacement efficiency of low water salinity flood... more The effect of injection brine salinity on the displacement efficiency of low water salinity flooding was investigated using sea water at 35,000 ppm, and two field injection waters, namely, Um-Eradhuma (UER) at 171,585 ppm and simsima (SIM) at 243,155 ppm. The salinity of the employed waters was varied from original salinity to 1,000 ppm and used in the displacement of oil in selected core samples. The results of this set of experiments revealed that UER salinity of 5,000 ppm is the optimum system for the candidate reservoir. UER original water and its optimum water were then used in this project as the high and low salinity waters in the CO 2-WAG flooding experiments. Displacement efficiencies were evaluated under three injection modes: carbon dioxide WAG miscible flooding (CO 2-WAG, 1:1, 2:1, and 1:2), continuous CO 2 injection, and waterflood. The WAG performance parameters, such as secondary and tertiary displacement efficiencies, CO 2 flood utilization factor, and CO 2 performance during different WAG flood cycles were determined. To insure miscibility condition between the injected gas and the employed oil, all of the flooding experiments were conducted at 3,200 psia (which is 300 psia above the minimum miscibility pressure of CO 2 and used oil) and 250°F. Experimental results indicated that core length is a critical parameter in determining the optimum WAG process, and that a minimum core length of 29 cm is required to insure the generation of miscibility before breakthrough in CO2-WAG flooding experiments. On the other hand, core length had no effect on the performance of the low salinity flooding experiments. Using single core flooding low salinity CO 2-WAG of 1:2 flooding produced an improvement in the displacement efficiency of 29 % over the high salinity system. Also, composite core flooding experiments showed that the high salinity CO 2-2:1 WAG achieved a displacement efficiency of 98 %. These results indicate that achieving miscibility at the reservoir conditions is the dominant mechanism and that low salinity will have no major effect on the displacement efficiency of CO 2-Miscible WAG flooding. Results also indicate that oil recovery during different CO2-WAG cycles is a function of WAG ratios.
Journal of Geophysics and Engineering, Jul 8, 2010
This study automates a type-curve technique for estimating the rock pore-geometric factor (λ) fro... more This study automates a type-curve technique for estimating the rock pore-geometric factor (λ) from capillary pressure measurements. The pore-geometric factor is determined by matching the actual rock capillary pressure versus wetting-phase saturation (P c-S w) profile with that obtained from the Brooks and Corey model (1966 J. Irrigation Drainage Proc. Am. Soc. Civ. Eng. 61-88). The pore-geometric factor values are validated by comparing the actual measured rock permeability to the permeability values estimated using the Wyllie and Gardner model (1958 World Oil (April issue) 210-28). Petrophysical data for both carbonate and sandstone rocks, along with the pore-geometric factor derived from the type-curve matching, are used in a discriminant analysis for the purpose of developing a model for rock typing. The petrophysical parameters include rock porosity (φ), irreducible water saturation (S wi), permeability (k), the threshold capillary-entry-pressure (P d), a pore-shape factor (β), and a flow-impedance parameter (n) which is a property that reflects the flow impedance caused by the irreducible wetting-phase saturation. The results of the discriminant analysis indicate that five of the parameters (φ, k, P d , λ and n) are sufficient for classifying rocks according to two broad lithology classes: sandstones and carbonates. The analysis reveals the existence of a significant discriminant function that is mostly sensitive to the pore-geometric factor values (λ). A discriminant-analysis classification model that honours both static and dynamic petrophysical rock properties is, therefore, introduced. When tested on two distinct data sets, the discriminant-analysis model was able to predict the correct lithofacies for approximately 95% of the tested samples. A comprehensive database of the experimentally collected petrophysical properties of 215 carbonate and sandstone rocks is provided with this study.
Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles, Jun 13, 2013
Re´sume´-Pre´diction de la pression miscibilite´minimum (MMP) du CO 2 en utilisant un algorithme ... more Re´sume´-Pre´diction de la pression miscibilite´minimum (MMP) du CO 2 en utilisant un algorithme base´sur l'ACE (Alternating Conditional Expectation)-L'injection de gaz miscibles est une des me´thodes les plus utilise´es pour ame´liorer la re´cupe´ration d'hydrocarbures (Enhanced Oil Recovery, EOR). En raison du couˆt important de cette technique, un haut degre´de pre´cision est requis pour pre´dire le processus. Une telle pre´cision comprend les parame`tres de de´pistage pre´liminaires pour le de´placement de gaz miscible, la pression minimale de miscibilite(Minimum Miscibility Pressure, MMP) et de la disponibilite´du gaz. Toutes les me´thodes de mesure du MMP conventionnelles sont des processus consommateurs de temps reque´rant de ce fait des couˆts importants. Par conse´quent, afin de re´pondre aux demandes de re´ponses rapides du secteur, une approche non parame´trique base´e sur l'algorithme ACE (Alternating Conditional Expectation) due a`Brieman et Friedman [Brieman L., Friedman J.H. (1985) J. Am. Stat. Assoc. 80, 391, 580-619], est utilise´e dans cette e´tude pour estimer les MMP. Cet algorithme recherche les transformations optimales d'un ensemble de facteurs pre´dictifs (ici C
This research presents a visualizing method to estimate capillary pressure relationship from cent... more This research presents a visualizing method to estimate capillary pressure relationship from centrifuge experiments using spinning disk geometry. The visualizing method consists of continuously recording the local saturation variation by using a video camera while centrifuging at any given time. The experimental procedure consists of recording sample images and fluid production at any given time and then determines local saturation by a simple correlation between production and gray level. Thus, a modified core holder was designed to adopt the new approach. The core holder must be transparent for visual interpretation of the experiments and strong to account for the high pressure during experiments. The traditional geometry for the centrifuge method is well-established in the industry. However, the benefits of using the spinning disk approach consist of validity of zero capillary pressure at the outlet face, ability of measuring local saturation at any given time, possibility of estimating drainage and spontaneous imbibition capillary pressure, and consideration of radial effect. Results of 24 rock samples show a good agreement between the capillary pressure relationships obtained from the new approach and those obtained from the porous-plate method. Relative errors of the capillary pressure were less than 5% for most samples. Furthermore, the entry pressures and irreducible wetting phase saturations obtained by this approach were agreed with the porous plate method.
Journal of Petroleum Exploration and Production Technology, Jun 2, 2015
Viscosity and density are important physical properties of crude oil. However, no practical theor... more Viscosity and density are important physical properties of crude oil. However, no practical theory exists for the calculation of these properties for heavy oil at elevated temperatures. The principal objective of this paper is to obtain exact models that can successfully predict these two important fluid properties covering a wide range of temperatures. In this study, heavy oil density was predicted from API and temperature, and then the predicted values of the densities were used in the second step to develop the viscosity correlation. A total of 30 heavy oil samples of different API gravities ranging from 11.7 to 18.8 were tested. Viscosity and density were measured in the temperature range from 20 to 160°C. The accuracy of the experimental density data was determined using Standing and Katz method. Published correlations were also used to evaluate the experimental viscosity data. The comparison between the experimental data and the predicted values indicated that the proposed model successfully predicted the experimental data with an average absolute relative error of less than 8 % and correlation coefficients (R 2) of 0.97 and 0.92 at normal and high temperatures, respectively. The proposed model and the literature models were tested on heavy oil samples. It was found that it is not possible to generalize a correlation for the heavy oil viscosity using only API and temperature. However, the proposed model significantly minimizes the relative error and increases the correlation between the predicted and experimental data compared with other published methods.
Journal of Petroleum Science and Engineering, Oct 1, 2016
The dependence of the shear wave velocity (V s) of water-saturated reservoir rocks on petrophysic... more The dependence of the shear wave velocity (V s) of water-saturated reservoir rocks on petrophysical parameters was investigated. Two general regression neural network (GRNN) models were developed to predict V s of sandstones, shaly sands, and carbonate rocks as a function of the compressional velocity (V p), grain density (ρ g), clay content, porosity (ϕ), permeability (k), and the cementation exponent (m) at a fixed effective stress and frequency. A set of 59 sample measurements of clean and dirty sandstones and carbonate rocks was used to train and test the GRNN models. The first model predicts V s as a function of ϕ, k, ρ g , m, and the clay content expressed as a percentage. This GRNN model was trained using two data sets consisting of 80% and 70% of the data, respectively. The truncated portions of the data were used as blind test sets to validate the GRNN model. The analysis reveals that the porosity, clay content, grain density, permeability, and cementation exponent are essential variables for capturing the variance of the shear wave velocity. Porosity appears to be the most important variable for estimating V s , and the grain density is the second most important variable. The GRNN model was able to estimate V s from both the training and the blind test data sets within an average absolute error of approximately 6%. Models from the literature that predict V s as a function of porosity and clay content appear to be specific to particular lithologies, such as sandstones or carbonates. Modeling V s by including parameters such as grain density, cementation exponent, and permeability in addition to porosity and clay content appears to capture the dominating physics that affects V s. By including this comprehensive set of input parameters, we have developed a generalized model to predict the shear wave velocity V s value for all types of lithology, such as carbonates and clean and dirty siliciclastics. A second GRNN model predicts V s as a function of only V p. This model was also trained using two data sets that consisted of 80% and 70% of the data, respectively. Similar to the first model, the truncated portions of the data were used as blind test sets to validate this GRNN model. The second GRNN model was able to estimate V s as a function of V p from the training sets within an average absolute error of approximately 4% while the average absolute error was 3% for the blind test data sets. The compressional velocity alone appears to be sufficient to predict the shear wave velocity.
Journal of Petroleum Exploration and Production Technology, Aug 20, 2015
This study introduces a general regression neural network (GRNN) model consisting of a one-pass l... more This study introduces a general regression neural network (GRNN) model consisting of a one-pass learning algorithm with a parallel structure for estimating the minimum miscibility pressure (MMP) of crude oil as a function of crude oil composition and temperature. The GRNN model was trained with 91 samples and was successfully validated with a blind testing data set of 22 samples. The MMP for six of these data samples was experimentally measured at the Petroleum Fluid Research Centre at Kuwait University. The remaining data consisted of experimental MMP data collected from the literature. The GRNN model was used to estimate the MMP from the training data set with an average absolute error of 0.2 %. The GRNN model was used to predict the MMP for the blind test data set with an average absolute error of 3.3 %. The precision of the introduced model and models in the literature was evaluated by comparing the predicted MMP values with the measured MMP values and using training and testing data sets. The GRNN model significantly outperformed the prominent models that have been published in the literature and commonly used for estimating MMP. The use of the GRNN model was reliable over a large range of crude oil compositions, impurities, and temperature conditions. The GRNN model provides a cost-effective alternative for estimating the MMP, which is commonly, measured using experimental displacement procedures that are costly and time consuming. The results provided in this study support the use of artificial neural networks for predicting the MMP of CO 2. Keywords General regression neural network Á Enhanced oil recovery Á Minimum miscibility pressure Á Carbon dioxide Á Gas injection
Journal of Petroleum Science and Engineering, Feb 1, 2005
In conventional centrifuge tests, the relative permeability of just one phase is obtainedthe phas... more In conventional centrifuge tests, the relative permeability of just one phase is obtainedthe phase with the lowest mobility. As a result, centrifuge tests are most often used for obtaining relative permeabilities of a liquid in a gas-liquid pair. In order to obtain more relative permeability insight from a centrifuge test, data in addition to production data must be obtained. In this paper, we discuss measurements of evolving air-water saturation profiles for a spinning-disk geometry. The saturation profiles were obtained by processing video images of the spinning rock sample, which was held in a transparent rotor assembly. Relative permeabilities of the water and the air were obtained by historymatching the saturation profiles and the production data. Critical gas saturation can be approximately estimated from the saturation profiles. In addition to the relative permeability results, we show a comparison of capillary pressures measured with the centrifuge (standard geometry and the spinning disk geometry), with a porous plate, and with mercury injection. For one of the samples, all four methods agreed well. For most samples, the centrifuge and the porous-plate methods agreed well.
An onshore oil well in Japan, referred to as Well M-1 in this paper, experienced a serious emulsi... more An onshore oil well in Japan, referred to as Well M-1 in this paper, experienced a serious emulsion problem soon after the introduction of artificial lift using a hydraulic jet pump. Even though the problem was resolved after switching to a new demulsifier, it is possible that the operator could experience another emulsion problem as the production condition changes in the future and accordingly, the new demulsifier becomes less effective. Therefore, a laboratory case study was conducted to understand not only the cause of the emulsion problem encountered, but also the relative magnitude of several factors affecting emulsion stability. Knowing the conditions that lead to the emulsion problem helps in understanding how to remove the emulsion and in designing intervention treatments to restore long-term well productivity. At first, the oil and brine samples from Well M-1 were mixed and agitated to form emulsion, and subsequently emulsion stability was evaluated. Subsequently, the mixing conditions were altered to investigate the individual impact on the emulsion stability: (1a) replace Well M-1 oil with another field's oil, (1b) replace Well M-1 brine with another field's brine, (2) change concentrations of asphaltene, (3) change concentrations of wax, (4) change concentrations of toluene insolubles, (5) vary temperature between 20 and 70 C, (6) vary shear stress (rotational speed between 3,500 and 15,000 rev/min), and (7) vary water cut between zero and 100%. The result of the emulsion stability in every test was different. All the above factors showed some impact on emulsion stability, except for brine composition and toluene insolubles, which had little impact on emulsion stability in this study. Operationally speaking, because it was found that the emulsion was stabilized by multiple factors, multiple preventative approaches are required to sustain stable production, free of emulsion. Oil Water Emulsion Fig. 1-Photograph of the fluid sample collected from the water tank (left) and microscopic view of the emulsion phase (right).
SPE/DGS Saudi Arabia Section Technical Symposium and Exhibition, 2011
This paper was selected for presentation by an SPE program committee following review of informat... more This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The ...
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