|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | The impacts of gas impurities on the minimum miscibility pressure of injected CO_2-rich gas–crude oil systems and enhanced oil recovery potential显示文摘An effective parameter in the miscible-CO_2 enhanced oil recovery procedure is the minimum miscibility pressure(MMP)defined as the lowest pressure that the oil in place and the injected gas into reservoir achieve miscibility at a given temperature. Flue gases released from power plants can provide an available source of CO_2,which would otherwise be emitted to the atmosphere, for injection into a reservoir. However, the costs related to gas extraction from flue gases is potentially high. Hence, greater understanding the role of impurities in miscibility characteristics between CO_2 and reservoir fluids helps to establish which impurities are tolerable and which are not. In this study, we simulate the effects of the impurities nitrogen(N_2), methane(C_1), ethane(C_2) and propane(C_3) on CO_2 MMP. The simulation results reveal that,as an impurity, nitrogen increases CO_2–oil MMP more so than methane. On the other hand, increasing the propane(C_3)content can lead to a significant decrease in CO_2 MMP, whereas varying the concentrations of ethane(C_2) does not have a significant effect on the minimum miscibility pressure of reservoir crude oil and CO_2 gas. The novel relationships established are particularly valuable in circumstances where MMP experimental data are not available. | Abouzar Choubineh Abbas Helalizadeh David A.Wood | 2019 | Petroleum Science2019，16，1： | 2 |
| 2 | A new framework for selection of representative samples for special core analysis显示文摘Special core analysis(SCAL)measurements play a noteworthy role in reservoir engineering.Due to the time-consuming and costly character of these measurements,routine core analysis(RCAL)data should be inspected thoroughly to select a representative subset of samples for SCAL.There are no comprehensive guidelines on how representative samples should be selected.In this study,a new framework is presented for selection of representative samples for SCAL.The foundation of this framework is using methods of PSRTI,FZI*(FZI-star)and TEM-function for the early estimation of petrophysical static,dynamic,and pseudo-static rock types at RCAL stage.The global hydraulic element(GHE)approach is benefitted and a FZI*-based GHE method(i.e.,GHE*)is presented for partitioning data.The framework takes into consideration different laboratory,reservoir engineering,geological,petrophysical and statistical factors.A carbonate reservoir case is presented to support our methodology.We also show that the current forms of Lorenz and Stratigraphic Modified Lorenz Plots in reservoir engineering are not appropriate,and present new forms of them. | Abouzar Mirzaei-Paiaman Seyed Reza Asadolahpour Hadi Saboorian-Jooybari Zhangxin Chen Mehdi Ostadhassan | 2020 | Petroleum Research2020，5，3： | 2 |
| 3 | Evaluation of Genotype × Environment Interaction in Rice Based on AMMI Model in Iran显示文摘Identification of high-yielding stable promising rice lines and determination of suitable areas for rice lines would be done by additive main effects and multiplicative interaction(AMMI) model. Seven promising rice genotypes plus two check varieties Shiroudi and 843 were analyzed using a randomized complete block design with three replications in three consecutive years(2012, 2013 and 2014). Homogenous error variance was indicated in the nine environments for grain yield. The combined analysis of variance indicated significant effects of environment, genotype and genotype × environment(GE) interactions on grain yield. The significant effect of GE interaction reflected on the differential response of genotypes in various environments and demonstrated that GE interaction had remarkable effect on genotypic performance in different environments. The application of AMMI model for partitioning the GE interaction effects showed that only the first two terms of AMMI were significant based on Gollob's Ftest. The lowest AMMI-1 was observed for G7, G2 and G6. G7 and G6 had higher grain yield. According to the first eigenvalue, which benefits only the first interaction principal component scores, G1, G6, G2 and G9 were the most stable genotypes. The values of the sum of first two interaction principal component scores could be useful in identifying genotype stability, and G6, G5 and G2 were the most dynamic stable genotypes. AMMI stability value introduced G6 as the most stable one. According to AMMI biplot view, G6 was high yielding and highly stable genotype. In conclusion, this study revealed that GE interactions were an important source of rice yield variation, and its AMMI biplots were forceful for visualizing the response of genotypes to environments. | Peyman SHARIFI Hashem AMINPANAH Rahman ERFANI Ali MOHADDESI Abouzar ABBASIAN | 2017 | Rice science2017，24，3： | 1 |
| 4 | Adaptive block motion prediction 显示文摘 | Abouzar Eslami Massoud Babaeizadeh | 2006 | IEEE International Symposium on Signal Processing and Information Technology2006，8，： | 1 |
| 5 | Subsidence estimation utilizing various approaches – A case study: Tehran No. 3 subway line显示文摘 | Abouzar Darabi Kaveh Ahangari Ali Noorzad Alireza Arab | 2012 | Tunnelling and Underground Space Technology incorporating Trenchless Technology Research2012，，： | 1 |
| 6 | Penicil lin biosensor based on a capacitive field-effect structure func tionalized with a dendrimer/carbon nanotube multilayer显示文摘 | Siqueira J R Jr Abouzar M H Poghossian A | 2009 | Biosens Bioelectron2009，25，： | 1 |
| 7 | Dynamic Behavior of Granular Soils at Shallow Depths from 1 g Shaking Table Tests显示文摘 | Abouzar Sadrekarimi | 2013 | Journal of Earthquake Engineering2013，，2： | 1 |
| 8 | Ductile steel plate external end diaphragms for steel tub girder straight highway bridges显示文摘The end diaphragm of bridges are normally designed to resist lateral seismic forces imposed on the superstructure in earthquake prone regions.Using ductile diaphragms with high deformation capacity could reduce the seismic demands on the substructure and prevent costly damage under strong ground motions.The end diaphragms of steel tub girder bridges with high lateral stiffness and dominant shear behavior have a potential to be used as ductile fuse elements.In this study,a steel plate shear diaphragm(SPSD)is introduced as an external end diaphragm of tub girder steel bridges to reduce the seismic demands imposed on the substructure.Quasi static nonlinear analyses were conducted to evaluate responses of sixteen SPSDs with different boundary conditions,aspect ratios and diaphragm plate thicknesses.Moreover,nonlinear time history analyses were performed using three different ground motions corresponding to DBE and MCE level spectrums.Cyclic and time history analyses proved the proper behavior of SPSD and its efficiency to reduce seismic demands by more than 25%. | Shervin Maleki Abouzar Dolati | 2020 | Earthquake Engineering and Engineering Vibration2020，19，3： | 1 |
| 9 | The rela- tionship between Glasgow coma/outcome scores and ab- normal CT scan findings in chronic subdural hematoma 显示文摘 | Amirjamshidi A Eftekha B Abouzar M | 2007 | Clinical Neurology and Neurosurgery2007，109，： | 1 |
| 10 | Particle damage observed in ring shear tests on sands 显示文摘 | ABOUZAR SADREKARIMI SCOTT M OLSON | 2010 | Canadian Geateehnieal Journal2010，47，5： | 1 |
| 11 | Penicillin Biosensor Based on a Capacitive Field Effect Structure Functionalized with a Dendrimer/Carbon Nano- tube Multilayer显示文摘 | SiqueiraJ J R Abouzar M H Poghossian A | 2009 | Biosensors and Bioelectronics2009，25，： | 1 |
| 12 | Static and dynamic behavior of hunchbacked gravity quay walls显示文摘 | Abouzar Sadrekarimi Abbas Ghalandarzadeh Jamshid Sadrekarimi | 2007 | Soil Dynamics and Earthquake Engineering2007，，2： | 1 |
| 13 | Penicillin biosensor based on a capacitive field-effect structure functionalized with a dendrimer/carbon nanotube multilayer显示文摘 | Siqueira J R Abouzar M H Poghossian A | 2009 | Biosensors and Bioelectronics2009，25，2： | 1 |
| 14 | Development of a Light Weight Reactive Powder Concrete显示文摘 | Abouzar Sadrekarimi | 2004 | Journal of Advanced Concrete Technology2004，2，3： | 1 |
| 15 | Assessing and Understanding the Key Risks in a PPP Power Station Projects显示文摘 | ADEL AZAR ABOUZAR ZANGOUEINEZHAD SHABAN E - LAHi | 2013 | Advances in Management & Applied Econom- mics2013，3，1： | 1 |
| 16 | Retraction Note to:Estimation of Load-Induced Damage and Repair Cost in Post-Tensioned Concrete Rocking Walls显示文摘The Editor-in-Chief has retracted this article after an investigation by the University of Michigan-Shanghai Jiao Tong University Joint Institute concluded that it overlaps significantly with Refs.[1-3]and is therefore redundant.Roberto Dugnani agrees with this retraction but not with the wording of the retraction notice.Abouzar Jafari has not responded to correspondence from the Journal about this retraction. | JAFARI Abouzar DUGNANI Roberto | 2022 | Journal of Shanghai Jiaotong university(Science)2022，27，4： | 0 |
| 17 | Transparent open-box learning network and artificial neural network predictions of bubble-point pressure compared显示文摘The transparent open box(TOB)learning network algorithm offers an alternative approach to the lack of transparency provided by most machine-learning algorithms.It provides the exact calculations and relationships among the underlying input variables of the datasets to which it is applied.It also has the capability to achieve credible and auditable levels of prediction accuracy to complex,non-linear datasets,typical of those encountered in the oil and gas sector,highlighting the potential for underfitting and overfitting.The algorithm is applied here to predict bubble-point pressure from a published PVT dataset of 166 data records involving four easy-tomeasure variables(reservoir temperature,gas-oil ratio,oil gravity,gas density relative to air)with uneven,and in parts,sparse data coverage.The TOB network demonstrates high-prediction accuracy for this complex system,although it predictions applied to the full dataset are outperformed by an artificial neural network(ANN).However,the performance of the TOB algorithm reveals the risk of overfitting in the sparse areas of the dataset and achieves a prediction performance that matches the ANN algorithm where the underlying data population is adequate.The high levels of transparency and its inhibitions to overfitting enable the TOB learning network to provide complementary information about the underlying dataset to that provided by traditional machine learning algorithms.This makes them suitable for application in parallel with neural-network algorithms,to overcome their black-box tendencies,and for benchmarking the prediction performance of other machine learning algorithms. | David A.Wood Abouzar Choubineh | 2020 | Petroleum2020，6，4： | 0 |
| 18 | Prediction of oil flow rate through an orifice flow meter: Artificial intelligence alternatives compared显示文摘Fluid-flow measurements of petroleum can be performed using a variety of equipment such as orifice meters and wellhead chokes.It is useful to understand the relationship between flow rate through orifice meters(Qv)and the five fluid-flow influencing input variables:pressure(P),temperature(T),viscosity(μ),square root of differential pressure(ΔP^0.5),and oil specific gravity(SG).Here we evaluate these relationships using a range of machine-learning algorithms applied to orifice meter data from a pipeline flowing from the Cheshmeh Khosh Iranian oil field.Correlation coefficients indicate that(Qv)has weak to moderate positive correlations with T,P,andμ,a strong positive correlation with theΔP^0.5,and a weak negative correlation with oil specific gravity.In order to predict the flow rate with reliable accuracy,five machine-learning algorithms are applied to a dataset of 1037 data records(830 used for algorithm training;207 used for testing)with the full input variable values for the data set provided.The algorithms evaluated are:Adaptive Neuro Fuzzy Inference System(ANFIS),Least Squares Support Vector Machine(LSSVM),Radial Basis Function(RBF),Multilayer Perceptron(MLP),and Gene expression programming(GEP).The prediction performance analysis reveals that all of the applied methods provide predictions at acceptable levels of accuracy.The MLP algorithm achieves the most accurate predictions of orifice meter flow rates for the dataset studied.GEP and RBF also achieve high levels of accuracy.ANFIS and LSSVM perform less well,particularly in the lower flow rate range(i.e.,<40,000 stb/day).Some machine learning algorithms have the potential to overcome the limitations of idealized streamline analysis applying the Bernoulli equation when predicting flow rate across an orifice meter,particularly at low flow rates and in turbulent flow conditions.Further studies on additional datasets are required to confirm this. | Hamzeh Ghorbani David A.Wood Abouzar Choubineh Afshin Tatar Pejman Ghazaeipour Abarghoyi Mohammad Madani Nima Mohamadian | 2020 | Petroleum2020，6，4： | 0 |
| 19 | Investigating dynamic rock quality in two-phase flow systems using TEM-function: A comparative study of different rock typing indices显示文摘Constructing a reservoir simulation model requires an accurate definition of saturation functions,including capillary pressure and relative permeability data.Usually,these saturation functions are available only for a limited number of samples.Assigning saturation functions to the simulation model requires finding a clear relationship between them and a 3D predictable property of grid cells.Different indices are usually evaluated to describe such a relationship.It was recently shown that each petrophysical dynamic rock type should form similar True Effective Mobility(TEM)curves.In this study,TEMfunction was used to evaluate the reliability and performance of different rock typing indices in defining dynamic rock types.FZI,FZIM,MFZI,and FZI*(FZI-star)indices were considered and tested on a collection of laboratory-derived core-flooding data from an Iranian carbonate reservoir.Results showed that FZI-star had a better performance than FZI,MFZI,and FZIM. | Mohsen Faramarzi-Palangar Abouzar Mirzaei-Paiaman | 2021 | Petroleum Research2021，6，1： | 0 |
| 20 | Impact of umbelliprenin-containing niosome nanoparticles on VEGF-A and CTGF genes expression in retinal pigment epithelium cells显示文摘AIM:To investigate the impact of niosome nanoparticles carrying umbelliprenin(UMB),an anti-angiogenic and anti-inflammatory plant compound,on the expression of vascular endothelial growth factor(VEGF-A)and connective tissue growth factor(CTGF)genes in a human retinal pigment epithelium(RPE)-like retina-derived cell line.METHODS:UMB-containing niosomes were created,optimized,and characterized.RPE-like cells were treated with free UMB and UMB-containing niosomes.The IC_(50)values of the treatments were determined using an MTT assay.Gene expression of VEGF-A and CTGF was evaluated using real-time polymerase chain reaction after RNA extraction and cDNA synthesis.Niosomes’characteristics,including drug entrapment efficiency,size,dispersion index,and zeta potential were assessed.Free UMB had an IC_(50)of 96.2μg/mL,while UMB-containing niosomes had an IC_(50)of 25μg/mL.RESULTS:Treatment with UMB-containing niosomes and free UMB resulted in a significant reduction in VEGF-A expression compared to control cells(P=0.001).Additionally,UMB-containing niosomes demonstrated a significant reduction in CTGF expression compared to control cells(P=0.05).However,there was no significant reduction in the expression of both genes in cells treated with free UMB.CONCLUSION:Both free UMB and niosome-encapsulated UMB inhibits VEGF-A and CTGF genes expression.However,the latter demonstrates significantly greater efficacy,potentially due to the lower UMB dosage and gradual delivery.These findings have implications for anti-angiogenesis therapeutic approaches targeting age-related macular degeneration. | Farzad Dastaviz Akram Vahidi Teymoor Khosravi Ayyoob Khosravi Mehdi Sheikh Arabi Abouzar Bagheri Mohsen Rashidi Morteza Oladnabi | 2024 | International Journal of Ophthalmology(English edition)2024，17，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员