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Effects of graphene oxide/TiO_(2) nanocomposite,graphene oxide nanosheets and Cedr extraction solution on IFT reduction and ultimate oil recovery from a carbonate rock

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petroleum 2022年第4期8卷 476-482页

作者： Amin Garmroudi Mahdi Kheirollahi Sayed Amirhosein Mousavi Moslem Fattahi Elaheh Hamed Mahvelati Department of Petroleum Engineering Abadan Faculty of Petroleum EngineeringPetroleum University of Technology(PUT)AbadanIran department of Chemical engineering Abadan Faculty of Petroleum EngineeringPetroleum University of Technology(PUT)AbadanIran department of Basic Sciences Abadan Faculty of Petroleum EngineeringPetroleum University of Technology(PUT)AbadanIran

Increasing the number of depleted reservoirs and global demand for energy have left us with low alternative but to use new ways to extract more hydrocarbon.Amongst different material used for tertiary oil recovery,surfactant injection has proved very promising solutions,such as interfacial tension reduction and wettability alteration.Without any harm to the environment and meanwhile being economically feasible,natural surfactants have been attracted researchers in recent years.Cedr extraction which is produced from Zizyphus Spina Christi leaves has shown some beneficial characteristics like IFT reduction and wettability alteration.However,the amount of IFT reduction is not considerable,so we decided to augment its effectiveness by adding two different nanoparticles.In this investigation,three concentrations(0.01,0.05 and 0.1 wt%)of both graphene oxide(GO)nanosheet and GO/TiO_(2) nanocomposite was added to Cedr extraction solution to study their potential on IFT reduction and improving the ultimate oil recovery.The concentration of 0.05 wt percent showed the lowest IFT in both solutions.At this concentration,the IFT of GO/TiO_(2)-augmented solution and GO-augmented solution were measured of 10.5 and 12.3 mN/m,respectively.While the bare Cedr solution showed 23.8 mN/m at its critical micelle concentration.The coreflooding tests were also performed at the aforementioned concentrations.Final oil recovery reached to 65%of original oil volume in GO/TiO_(2)-augmented solution,compared to 56% in GO-augmented solution case and 40%in bare Cedr solution case.Scanning Electron Microscopy images were also taken from the rock samples exposed to nanofluids to investigate any severe harm to the permeability.Images showed low tendency of both particles to adsorb on rock surface and plug large pores.

关键词： Cedr extraction Coreflooding GO nanosheet GO-TiO_(2)nanocomposite IFT reduction Enhanced oil recovery

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Review of application of artificial intelligence techniques in petroleum operations

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petroleum Research 2023年第2期8卷 167-182页

作者： Saeed Bahaloo Masoud Mehrizadeh Adel Najafi-Marghmaleki Department of Petroleum Engineering Amirkabir University of TechnologyTehranIran Department of Petroleum Engineering School of Science and EngineeringKhazar UniversityBakuAzerbaijan Department of Petroleum Engineering Ahwaz Faculty of PetroleumPetroleum University of TechnologyAhwazIran

In the last few years,the use of artificial intelligence(AI)and machine learning(ML)techniques have received considerable notice as trending technologies in the petroleum industry.The utilization of new tools and modern technologies creates huge volumes of structured and un-structured data.Organizing and processing of these information at faster pace for the performance assessment and forecasting for field development and management is continuously growing as an important field of investigation.Various difficulties which were faced in predicting the operative features by utilizing the conventional methods have directed the academia and industry toward investigations focusing on the applications of ML and data driven approaches in exploration and production operations to achieve more accurate predictions which improves decision-making processes.This research provides a review to examine the use cases and application of AI and ML techniques in petroleum industry for optimization of the upstream processes such as reservoir studies,drilling and production engineering.The challenges related to routine approaches for prognosis of operative parameters have been evaluated and the use cases of performance optimizations through employing data-driven approaches resulted in enhancement of decision-making workflows have been presented.Moreover,possible scenarios of the way that artificial intelligence will develop and influence the oil and gas industry and how it may change it in the future was discussed.

关键词： Artificial intelligence Machine learning Upstream operation Oil and gas industry petroleum systems Decision-making

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Experimental assessment of hybrid smart carbonated water flooding for carbonate reservoirs

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petroleum 2021年第1期7卷 80-90页

作者： Payam Soleimani Seyed Reza Shadizadeh Riyaz Kharrat Department of Petroleum Engineering Ahwaz Faculty of Petroleum EngineeringPetroleum University of TechnologyAhwazIran Department of Petroleum Engineering Abadan Faculty of Petroleum EngineeringPetroleum University of TechnologyAbadanIran department petroleum engineering MontanuniversitatLeobenAustria

Different methods of enhanced oil recovery have been used to produce trapped oil.One of these methods is carbonated water injection in which CO2 contained water is injected in reservoirs in order to decrease free CO2 injection mobility,increase water viscosity and store/remove produced greenhouse CO2 gas safely.Another enhanced oil recovery method is smart water injection at which the ions in brine are modified in order to make controlled reactions with distributed ions on the surface of rock to cause more hydrocarbon recovery.Therefore,combination of these two methods may also have a great effect on enhancing oil recovery or may result in recovery factor less than each method used alone.In this paper hybrid smart carbonated water injection method is investigated to study its applicability in oil recovery using core flooding setup.The experimental core flooding setup was designed to perform different types of EOR methods for the sake of recovery comparison with the new hybrid method.The effect of both brine content and volume of CO2 is determining in hybrid EOR assessment.The main findings of this work show that the hybrid smart carbonated water results in the highest recovery factor in comparison to the most well-known EOR methods for carbonate cores.

关键词： Hybrid smart carbonated water Carbonated water Smart water Core flooding Carbonate core

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Effect of heterogeneity and injection rates on the recovery of oil from conventional sand packs:A simulation approach

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petroleum Research 2023年第1期8卷 96-102页

作者： Anurag Pandey Himanshu Kesarwani Amit Saxena Reza Azin Shivanjali Sharma Department of Petroleum Engineering and Geological Sciences Rajiv Gandhi Institute of Petroleum TechnologyIndia Department of Petroleum Engineering Faculty of PetroleumGas and Petrochemical EngineeringPersian Gulf UniversityBushehrIran

The study of flow through porous media has been of cardinal gravity in oil and gas applications like enhanced oil recovery(EOR),acidizing,fracturing,etc.One of the most anticipated apprehensions is that the core flooding and simulation have become prevalent to understand the flow through porous media.This study aims at simulating and analyzing the effect of alkaline surfactant flooding through heterogeneous permeability conditions in the lab-scale methods.The conventional methods of core flood deal with the effective permeability of the system without considering the effect of heterogeneity within the core.The heterogeneous studies are conducted by simulating a finely meshed 2-D axisymmetric model of the sand pack.The novel Karanj oil surfactant extracted from Pongamia Pinnata,and partially hydrolyzed polyacryl amide polymer are considered for the physicochemical properties of displacing fluid used in the simulations.Different heterogeneity combinations and displacing fluid injection flow rates are introduced for a single absolute permeability system.Results indicate a trend of oil recovery upright with increasing vertical permeability.A lower areal sweep efficiency and early breakthrough are observed in models with high horizontal permeabilities.Further,the effect of heterogeneity on oil recovery is reduced with the increase in injection flow rates of displacing fluid.The present work utilizes computational fluid dynamics to model multiphase flow through a heterogeneous permeability media and its effect on oil recovery.

关键词： Karanj oil Simulation Enhanced oil recovery(EOR) Heterogenous permeability ASP Flooding

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Improving TC drill bit's efficiency and resistance to wear by graphene coating

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petroleum Research 2022年第4期7卷 430-436页

作者： Reza Taheri Mohsen Jalali Ahmed Al-Yaseri George Yabesh petroleum engineering department University of WyomingWYUSA petroleum engineering department Tehran Azad UniversityTehranIran petroleum engineering Discipline Engineering SchoolEdith Cowan UniversityAustralia

Displaying a two-dimensional pure crystal carbon structure,Graphene is the strongest,yet thinnest substance discovered by scientists.Coating tungsten carbide(TC)drill bits with graphene to evaluate the effect of graphene on the wear,as well as the rate of penetration of the drilling bit was examined in this research.Two evaluation approaches were employed:one with employing ANSYS Software and the second by employing atomic pressure chemical vapor deposition(APCVD synthesis)in the laboratory to produce a monolayer graphene coating.The simultaneous software-based and lab-based testing were performed to increase the credibility of the results and minimize the potential errors.Conducting the simulation using ANSYS,the maximum shear elastic strain,equivalent elastic strain,equivalent(von mises)stress,total deformation and maximum shear stress were investigated prior and after the gra-phene coating was applied on TC simulated bit.Total deformation was only slightly increased,while the maximum shear elastic strain was almost doubled,reflecting that the bit's wear was significantly reduced after the coating.Lab-based APCVD synthesis results showed 34%increase in compressive strength of the coated bit,in comparison to the uncoated one.The failure occurred for uncoated bit at 35 MPa,where the coated bit experienced failure at 46.9 MPa.The Von Mises stress test conducted on the coated and uncoated samples also indicated that this stress was 41%less for the coated bit,in comparison to the uncoated one.Finally,two small-scale drilling operations,one using a 1inch graphene-coated TC bit and the other using a 1inch non-coated TC bit,were performed on a granite block,to evaluate the performance of the graphene-coated bit in practice.In a chosen 120-min time frame,27 consecutive holes could be drilled by the graphene-coated TC bit,while 19 consecutive holes could be drilled by the uncoated TC bit,in identical drilling conditions.This implies a 42%increase in ROP.

关键词： Drill bit's efficiency Graphene-coated ANSYS APCVD Wear reduction Penetration rate

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Application of thermotolerant petroleum microbes at reservoir conditions for enhanced oil recovery

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petroleum 2023年第2期9卷 223-236页

作者： Emmanuel E.Okoro Ewarezi A.Efajemue Samuel E.Sanni Oluwasanmi A.Olabode Oyinkepreye D.Orodu Temiloluwa Ojo petroleum engineering department University of Port HarcourtChobaNigeria petroleum engineering department Covenant UniversityOtaNigeria Chemical engineering department Covenant UniversityOtaNigeria

Primary oil recovery is the first stage of hydrocarbon production in which a reservoir uses its natural energy to force hydrocarbon to its wellbore.Secondary oil recovery comes to play when hydrocarbons can no longer be further produced by natural means.The purpose of secondary recovery is to maintain reservoir pressure so as to displace hydrocarbons toward the wellbore.Both primary and secondary recovery processes cannot displace more than 50%of the available hydrocarbons in a reservoir.The remaining hydrocarbons are further recovered through Tertiary/Enhanced Oil Recovery techniques.According to literature,microbial enhanced oil recovery has been identified as a tertiary method used to improve the efficiency of hydrocarbon production from reservoirs.Microbial enhanced oil recovery is a feasible reservoir technology,which has not been widely used in the oil and gas industry owing to the attainment of the requisite reservoir conditions such as temperature within which microbes can thrive.Literature has shown that thermotolerant microbes can withstand optimum temperatures of 50e90℃,while deep and ultra-deep hydrocarbon reservoir temperatures are often above 100℃.This study identifies some isolated thermotolerant microbes from a sandstone reservoir that can withstand temperatures as high as 110℃via conventional methods and molecular analysis.The identified thermotolerant petroleum microbes:Bacillus amyloliquefaciens(A)and Bacillus nealsonii(B)were used to enhance oil recovery from a reservoir.The results showed that the microbial species A and B at a confined pressure of 3.0 MPa and temperature of 27℃,gave 46.4%and 48.6%oil recoveries,respectively,which is comparably higher than the value(26.9%)obtained for the water flooded samples.At temperatures of 80,90,100,110 and 120℃,the oil recovery results show that the recovery factor(55.2%e64.1%)of species B were higher compared to the range(46.7e57.5%)recorded for species A.At the onset of the core flooding experiments,there was an initial increment in oil recovery fact

关键词： Microbial enhanced oil recovery Thermotolerant petroleum microbes Recovery factor Microbe isolation/identification Sandstone reservoir

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Oil-water interfacial tension, wettability alteration and foaming studies of natural surfactant extracted from Vernonia Amygdalina

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petroleum Research 2022年第3期7卷 350-356页

作者： Happiness Imuetinyan Augustine Agi Afeez Gbadamosi Radzuan Junin Jeffrey Osehd Department of Petroleum Engineering College of Engineering and TechnologyFederal University of Petroleum ResourcesEfurunNigeria Department of Petroleum Engineering School of Chemical and Energy EngineeringFaculty of EngineeringUniversiti Teknologi Malaysia81310Skuda JohorMalaysia Center for Integrative petroleum Research King Fahd University of Petroleum and MineralsDhahran31262Saudi Arabia Department of Petroleum Engineering Federal University of Technology OwerriNigeria

Surfactant flooding is an enhanced oil recovery(EOR)method for recovering residual oil in the reservoir through mechanism of interfacial tension(IFT)reduction and wettability alteration.Due to toxicity and high cost associated with conventional surfactants,recent research has focussed on developing low-cost and environmentally benign surfactants.Herein,a low-cost green surfactant is extracted from Vernonia Amygdalina(VA)and appraised for EOR applications.The extracted surfactant was characterized using Fourier Transform Infrared(FTIR)and High-Pressure Liquid Chromatography(HPLC).The IFT of the synthesized surfactant at the oil-water interface was determined using Kruss tensiometer.Additionally,the foam stability of the synthesized surfactant was examined.Moreover,the wettability of the saponin based natural surfactant(SBNS)at the rock-fluid interface was analysed using Dataphysics drop shape analyser.Experimental result revealed that SBNS(1 wt%concentration)stabilized foam for longer periods with half-life of 1100 min.Furthermore,the synthesized surfactant was effective in lowering the IFT of oil-water interface from 18 mN/m to 0.97 mN/m.Finally,SBNS altered the wettability of sandstone cores to water-wetting condition by reducing the contact angle from 118.5° to 45.7°.Overall,SBNS exhibit excellent properties desirable for EOR and thereby recommended as supplementary alternative to conventional surfactants.

关键词： Enhanced oil recovery Surfactant Interfacial tension Wettability Saponin Foam

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Statistical prediction of waterflooding performance by K-means clustering and empirical modeling

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petroleum Science 2022年第3期19卷 1139-1152页

作者： Qin-Zhuo Liao Liang Xue Gang Lei Xu Liu Shu-Yu Sun Shirish Patil Department of Petroleum Engineering King Fahd University of Petroleum and MineralsDhahranSaudi Arabia Department of Petroleum Engineering China University of Petroleum-BeijingBeijing102240China Faculty of engineering China University of GeosciencesWuhan430074HubeiChina Center for Integrative petroleum Research King Fahd University of Petroleum and MineralsDhahranSaudi Arabia Department of Petroleum Engineering King Abdullah University of Science and TechnologyThuwalSaudi Arabia

Statistical prediction is often required in reservoir simulation to quantify production uncertainty or assess potential risks.Most existing uncertainty quantification procedures aim to decompose the input random field to independent random variables,and may suffer from the curse of dimensionality if the correlation scale is small compared to the domain size.In this work,we develop and test a new approach,K-means clustering assisted empirical modeling,for efficiently estimating waterflooding performance for multiple geological realizations.This method performs single-phase flow simulations in a large number of realizations,and uses K-means clustering to select only a few representatives,on which the two-phase flow simulations are implemented.The empirical models are then adopted to describe the relation between the single-phase solutions and the two-phase solutions using these representatives.Finally,the two-phase solutions in all realizations can be predicted using the empirical models readily.The method is applied to both 2D and 3D synthetic models and is shown to perform well in the P10,P50 and P90 of production rates,as well as the probability distributions as illustrated by cumulative density functions.It is able to capture the ensemble statistics of the Monte Carlo simulation results with a large number of realizations,and the computational cost is significantly reduced.

关键词： Waterflooding Statistical prediction K-means clustering Empirical modeling Uncertainty quantification

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Super gas wet and gas wet rock surface: State of the art evaluation through contact angle analysis

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petroleum 2023年第1期9卷 1-7页

作者： Mohammad Azadi Tabar Abolfazl Dehghan Monfared Flor Shayegh Farzad Barzegar Mohammad Hossein Ghazanfari department of Chemical and petroleum engineering Sharif University of TechnologyTehran11155-9564Iran Department of Petroleum Engineering Faculty of PetroleumGas and Petrochemical EngineeringPersian Gulf UniversityBushehr75169-13817Iran Research Institute of petroleum Industry Tehran14665-137Iran

Recently,super gas wet and gas wet surfaces have been extensively attended in petroleum industry,as supported by the increasing number of publications in the last decade related to wettability alteration in gas condensate reservoirs.In many cases,contact angle measurement has been employed to assess the wettability alteration.Even though contact angle measurement seems to be a straightforward approach,there exist many misuses of this technique and consequently misinterpretation of the corresponding results.In this regard,a critical inspection of the most recent updated concepts and the intervening parameters in the contact angle based wettability evaluation of liquid-solid-gas systems could aid to provide some remediation to alleviate this problem.To this end,this work presents a survey on the accurate terms and rigorous protocols based on the community of surface science and chemistry.As a preliminary step,advancing,receding,static,and the most stable contact angle terminology are defined.The study is followed by the definition of the contact angle hysteresis effect.The application of surface free energy in the selection of the best gas wet agent is then analyzed.Afterward,the impact of the size-dependent behavior of drop on contact angle is discussed.Finally,a sessile drop experiment is explained to achieve the defined parameters.For future contributions to petroleum industry journals,like this journal,this work could offer an easy use of the conceptual framework for analyzing the results and comparative evaluations in chemical wettability modifier agents.

关键词： Contact angle hysteresis Size-dependent behavior Surface free energy Stick-slip Wettability alteration Condensate reservoirs

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Application of artificial intelligence in predicting the dynamics of bottom hole pressure for under-balanced drilling:Extra tree compared with feed forward neural network model

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petroleum 2022年第2期8卷 227-236页

作者： Emmanuel E.Okoro Tamunotonjo Obomanu Samuel E.Sanni David I.Olatunji Paul Igbinedion petroleum engineering department Covenant UniversityOtaNigeria petroleum engineering department Federal Polytechnic of Oil and GasBonnyNigeria Chemical engineering department Covenant UniversityOtaNigeria

This study used six fields data alongside correlation heat map to evaluate the field parameters that affect the accuracy of bottom hole pressure(BHP)estimation.The six oil field data were acquired using measurement while drilling device to collect surface measurements of the downhole pressure data while drilling.For the two case studies,measured field data of the wellbore filled with gasified mud system was utilized,and the wellbores were drilled using rotary jointed drill strings.Extremely Randomized Tree and feed forward neural network algorithms were used to develop models that can predict with high accuracy,BHP from measured field data.For modeling purpose,an extensive data from six fields was used,and the proposed model was further validated with two data from two new fields.The gathered data encompasses a variety of well data,general information/data,depths,hole size,and depths.The developed model was compared with data obtained from two new fields based on its capability,stability and accuracy.The result and model’s performance from the error analysis revealed that the two proposed Extra Tree and Feed Forward models replicate the bottom hole pressure data with R2 greater than 0.9.The high values of R^(2) for the two models suggest the relative reliability of the modelling techniques.The magnitudes of mean squared error and mean absolute percentage error for the predicted BHPs from both models range from 0.33 to 0.34 and 2.02%-2.14%,for the Extra tree model and 0.40-0.41 and 3.90%e3.99%for Feed Forward model respectively;the least errors were recorded for the Extra Tree model.Also,the mean absolute error of the Extra Tree model for both fields(9.13-10.39 psi)are lower than that of the Feed Forward model(10.98-11 psi),thus showing the higher precision of the Extra Tree model relative to the Feed Forward model.Literature has shown that underbalanced operation does not guarantee the improvement of horizontal well’s extension ability,because it mainly depends on the relationship between the bottomhole pressure

关键词： Artificial intelligence Bottom hole pressure Extra tree Predictive model Oil and gas Feed forward algorithms

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