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Enhanced heavy and extra heavy oil recovery:Current status and new trends

Petroleum 2024年第3期10卷 399-410页

作者： Sayed gomaa khalaf g.salem A.N.El-hoshoudy Mining and Petroleum Engineering Department Faculty of EngineeringAl-Azhar UniversityEgypt Department of Reservoir Engineering South Valley Egyptian Petroleum Holding Company(GANOPE)CairoEgypt PVT Lab-Production Department Egyptian Petroleum Research Institute(EPRI)Cairo 11727Egypt PVT-Service Center Egyptian Petroleum Research Institute(EPRI)Cairo 11727Egypt

Due to the increased demand for energy resources these days,especially due to the Russian-Ukrainian war,the focus of the major countries is turning strongly towards improving oil production,especially heavy and extra heavy oil,which represents 40%of the world oil ***-based and thermal(EOR)procedures are promising techniques for recovering heavy oil reservoirs,but they suffer from a sequence of problems and complications that arise after long-term *** complications comprise steam breakthrough,steam overlap,and steam/rock *** research presents the currently applied techniques to maximize the productivity of heavy oil,such as steam injection,cyclic steam stimulation,in-situ combustion,and steam-assisted gravity *** technologies face numerous obstacles,as they are energy and water-intensive processes that are not environmentally *** research also presents future trends in energy-saving and environmentally friendly techniques that enhance heavy oil recovery through vapor extraction(VAPEX)steam-solvent hybrid techniques,electromagnetic energy,sonication,and *** findings of this review reported that all the presented techniques focus on how to reduce the oil viscosity and in-situ upgrade the crude oil *** turn,these enhance both the productivity rate and oil recovery and minimize the production *** article can be considered a comprehensive review of thermal recovery methods in heavy and extra-heavy oil,in addition to screening criteria used for each method.

关键词： Enhanced oil recovery Heavy crude oil Steam flood Hybrid techniques Nanotechnology

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Enhanced heavy and extra heavy oil recovery: Current status and new trends

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Petroleum 2024年第3期 399-410页

作者： Sayed gomaa khalaf g.salem A.N.El-hoshoudy Mining and Petroleum Engineering Department Faculty of Engineering Al-Azhar University Department of Reservoir Engineering South Valley Egyptian Petroleum Holding Company (GANOPE) PVT Lab-Production Department Egyptian Petroleum Research Institute (EPRI) PVT-Service Center Egyptian Petroleum Research Institute (EPRI)

Due to the increased demand for energy resources these days, especially due to the Russian-Ukrainian war, the focus of the major countries is turning strongly towards improving oil production, especially heavy and extra heavy oil, which represents 40% of the world oil reserve. Steam-based and thermal(EOR)procedures are promising techniques for recovering heavy oil reservoirs, but they suffer from a sequence of problems and complications that arise after long-term application. These complications comprise steam breakthrough, steam overlap, and steam/rock interactions. This research presents the currently applied techniques to maximize the productivity of heavy oil, such as steam injection, cyclic steam stimulation, in-situ combustion, and steam-assisted gravity drainage. Thermal technologies face numerous obstacles, as they are energy and water-intensive processes that are not environmentally friendly. The research also presents future trends in energy-saving and environmentally friendly techniques that enhance heavy oil recovery through vapor extraction(VAPEX) steam-solvent hybrid techniques, electromagnetic energy, sonication, and nanotechnology. The findings of this review reported that all the presented techniques focus on how to reduce the oil viscosity and in-situ upgrade the crude oil properties. In turn, these enhance both the productivity rate and oil recovery and minimize the production cost. This article can be considered a comprehensive review of thermal recovery methods in heavy and extra-heavy oil, in addition to screening criteria used for each method.

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Bifurcation phenomena and control for magnetohydrodynamic flows in a smooth expanded channel

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Chinese Physics B 2014年第11期23卷 374-383页

作者： g.C.Layek Mani Shankar Mandal H.A.khalaf Department of Mathematics The University of Burdwan Department of Mathematics Krishnagar Govt. College KrishnagarNadia 741101India Thi-Qar University Marshes Research Center Thi-QarIraq

This work reports the effects of magnetic field on an electrically conducting fluid with low electrical conductivity flowing in a smooth expanded channel. The governing nonlinear magnetohydrodynamic （MHD） equations in induction- free situations are derived in the framework of MHD approximations and solved numerically using the finite-difference technique. The critical values of Reynolds number （based on upstream mean velocity and channel height） for symmetry breaking bifurcation for a sudden expansion channel （1：4） is about 36, whereas the value in the case of the smooth expansion geometry used in this work is obtained as 298, approximately （non-magnetic case）. The flow of an electrically conducting fluid in the presence of an externally applied constant magnetic field perpendicular to the plane of the flow is reduced significantly depending on the magnetic parameter （M）. It is expansion （1：4） is about 475 for the magnetic parameter M found that the critical value of Reynolds number for smooth = 2. The separating regions developed behind the smooth symmetric expansion are decreased in length for increasing values of the magnetic parameter. The bifurcation diagram is shown for a symmetric smoothly expanding channel. It is noted that the critical values of Reynolds number increase with increasing magnetic field strength.

关键词： weakly electrically conducting fluid flow bifurcation asymmetric flow smooth expansion

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Olive Leaf Disease Detection via Wavelet Transform and Feature Fusion of Pre-Trained Deep Learning Models

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Computers, Materials & Continua 2024年第3期78卷 3431-3448页

作者： Mahmood A.Mahmood khalaf Alsalem Department of Information Systems College of Computer and Information SciencesJouf UniversitySakakahKingdom of Saudi Arabia Department of Information Systems and Technology Faculty of Graduate Studies and ResearchCairo UniversityGizaEgypt

Olive trees are susceptible to a variety of diseases that can cause significant crop damage and economic *** detection of these diseases is essential for effective *** propose a novel transformed wavelet,feature-fused,pre-trained deep learning model for detecting olive leaf *** proposed model combines wavelet transforms with pre-trained deep-learning models to extract discriminative features from olive leaf *** model has four main phases:preprocessing using data augmentation,three-level wavelet transformation,learning using pre-trained deep learning models,and a fused deep learning *** the preprocessing phase,the image dataset is augmented using techniques such as resizing,rescaling,flipping,rotation,zooming,and *** wavelet transformation,the augmented images are decomposed into three frequency *** pre-trained deep learning models,EfficientNet-B7,DenseNet-201,and ResNet-152-V2,are used in the learning *** models were trained using the approximate images of the third-level sub-band of the wavelet *** the fused phase,the fused model consists of a merge layer,three dense layers,and two dropout *** proposed model was evaluated using a dataset of images of healthy and infected olive *** achieved an accuracy of 99.72%in the diagnosis of olive leaf diseases,which exceeds the accuracy of other methods reported in the *** finding suggests that our proposed method is a promising tool for the early detection of olive leaf diseases.

关键词： Olive leaf diseases wavelet transform deep learning feature fusion

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NTRU_SSS:Anew Method Signcryption Post Quantum Cryptography Based on Shamir’s Secret Sharing

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Computers, Materials & Continua 2023年第7期76卷 753-769页

作者： Asma Ibrahim Hussein Abeer Tariq MaoLood Ekhlas khalaf gbashi Ministry of Higher Education and Scientific Research BagdadIraq Affiliations Computer Science Univ.of TechnologyBagdad750004Iraq

With the advent of quantum computing,numerous efforts have been made to standardize post-quantum cryptosystems with the intention of(eventually)replacing Elliptic Curve Cryptography(ECC)and Rivets-Shamir-Adelman(RSA).A modified version of the traditional N-Th Degree Truncated Polynomial Ring(NTRU)cryptosystem called NTRU Prime has been developed to reduce the attack *** this paper,the Signcryption scheme was proposed,and it is most efficient than others since it reduces the complexity and runs the time of the code execution,and at the same time,provides a better security degree since it ensures the integrity of the sent message,confidentiality of the data,forward secrecy when using refreshed parameters for each *** to prevent the man-in-the-middle attack from being active or passive,and non-repudiation when the sender can’t deny the recently sent *** study aims to create a novel NTRU cryptography algorithm system that takes advantage of the security features of curve fitting operations and the valuable characteristics of chaotic *** proposed algorithm combines the(NTRU Prime)and Shamir’s Secret Sharing(SSS)features to improve the security of the NTRU encryption and key generation stages that rely on robust polynomial *** on experimental results and a comparison of the time required for crucial exchange between NTRU-SSS and the original NTRU,this study shows a rise in complexity with a decrease in execution time in the case when compared to the original ***’s encouraging to see signs that the suggested changes to the NTRU work to increase accuracy and efficiency.

关键词： Post-quantum cryptography NTRU Shamir’s secret sharing public key

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Remote Sensing Monitoring Method Based on BDS-Based Maritime Joint Positioning Model

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Computer Modeling in Engineering & Sciences 2021年第5期127卷 801-818页

作者： Xiang Wang Jingxian Liu Osamah Ibrahim khalaf Zhao Liu Hubei Key Laboratory of Inland Shipping Technology School of NavigationWuhan University of TechnologyWuhan430063China Donghai Navigation Safety Administration Ministry of Transport of the People’s Republic of ChinaShanghai201206China Al-Nahrain Nanorenewable Energy Research Centre Al-Nahrain UniversityBaghdadIraq

Complicated sea conditions have a serious impact on ship navigation safety and even maritime ***,this paper proposes a remote sensing monitoring method based on the Beidou Navigation Satellite System(BDS)maritime joint positioning *** method is mainly based on the BDS and multiple global Navigation Satellite Systems(gNSS)to build a data fusion model,which can capture more steady positioning,navigation,and timing(PNT)*** with the current global Positioning System(gPS)and global Navigation Satellite System(gLONASS)mandatory used by the International Maritime Organization(IMO),this model has the characteristics of more accurate positioning data and stronger *** static and dynamic measurement show that such a model works for maritime ships and maritime *** with the Ship’s Automatic Identification System(AIS)and geographic Information System(gIS),a BDS-based remote sensing monitoring method can cover the world,serve maritime ships and construct maritime engineering.

关键词： Ship navigation AIS BDS gPS data fusion

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Optimal Artificial Intelligence Based Automated Skin Lesion Detection and Classification Model

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Computer Systems Science & Engineering 2023年第1期44卷 693-707页

作者： Kingsley A.Ogudo R.Surendran Osamah Ibrahim khalaf Faculty of Engineering and the Built Environment Department of Electrical and Electronics Engineering TechnologyUniversity of JohannesburgJohannesburg2006South Africa Center for Artificial Intelligence and Research(CAIR) Chennai Institute of TechnologyChennai600069India Al-Nahrain Nanorenewable Energy Research Center Al-Nahrain UniversityBaghdad64074Iraq

Skin lesions have become a critical illness worldwide,and the earlier identification of skin lesions using dermoscopic images can raise the survival *** of the skin lesion from those dermoscopic images will be a tedious *** accuracy of the classification of skin lesions is improved by the use of deep learning ***,convolutional neural networks(CNN)have been established in this domain,and their techniques are extremely established for feature extraction,leading to enhanced *** this motivation,this study focuses on the design of artificial intelligence(AI)based solutions,particularly deep learning(DL)algorithms,to distinguish malignant skin lesions from benign lesions in dermoscopic *** study presents an automated skin lesion detection and classification technique utilizing optimized stacked sparse autoen-coder(OSSAE)based feature extractor with backpropagation neural network(BPNN),named the OSSAE-BPNN *** proposed technique contains a multi-level thresholding based segmentation technique for detecting the affected lesion *** addition,the OSSAE based feature extractor and BPNN based classifier are employed for skin lesion ***,the parameter tuning of the SSAE model is carried out by the use of sea gull optimization(SgO)*** showcase the enhanced outcomes of the OSSAE-BPNN model,a comprehensive experimental analysis is performed on the benchmark *** experimentalfindings demonstrated that the OSSAE-BPNN approach outper-formed other current strategies in terms of several assessment metrics.

关键词： Deep learning dermoscopic images intelligent models machine learning skin lesion

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Tauroursodeoxycholic acid: a potential therapeutic tool in neurodegenerative diseases

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Translational Neurodegeneration 2022年第1期11卷 444-460页

作者： Kareem khalaf Paolo Tornese Antoniangela Cocco Alberto Albanese Department of Neurology IRCCS Humanitas Research HospitalRozzanoMIItaly

Most neurodegenerative disorders are diseases of protein homeostasis, with misfolded aggregates accumulating. The neurodegenerative process is mediated by numerous metabolic pathways, most of which lead to apoptosis. In recent years, hydrophilic bile acids, particularly tauroursodeoxycholic acid (TUDCA), have shown important anti-apoptotic and neuroprotective activities, with numerous experimental and clinical evidence suggesting their possible therapeutic use as disease-modifiers in neurodegenerative diseases. Experimental evidence on the mechanisms underlying TUDCA’s neuroprotective action derives from animal models of Alzheimer’s disease, Parkinson’s disease, Huntington’s diseases, amyotrophic lateral sclerosis (ALS) and cerebral ischemia. Preclinical studies indicate that TUDCA exerts its effects not only by regulating and inhibiting the apoptotic cascade, but also by reducing oxidative stress, protecting the mitochondria, producing an anti-neuroinflammatory action, and acting as a chemical chaperone to maintain the stability and correct folding of proteins. Furthermore, data from phase II clinical trials have shown TUDCA to be safe and a potential disease-modifier in ALS. ALS is the first neurodegenerative disease being treated with hydrophilic bile acids. While further clinical evidence is being accumulated for the other diseases, TUDCA stands as a promising treatment for neurodegenerative diseases.

关键词： Amyotrophic lateral sclerosis Alzheimer’s disease Bile acids Disease-modifying Huntington’s disease Neurodegeneration Neuroprotection Parkinson’s disease Ursodeoxycholic acid Tauroursodeoxycholic acid

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Deep Learning Based Intelligent Industrial Fault Diagnosis Model

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Computers, Materials & Continua 2022年第3期70卷 6323-6338页

作者： R.Surendran Osamah Ibrahim khalaf Carlos Andres Tavera Romero Center for Artificial Intelligence&Research(CAIR) Chennai Institute of TechnologyChennai600069India Al-Nahrain Nanorenewable Energy Research Center Al-Nahrain UniversityBaghdad64074Iraq COMBA I+D Research group of Universidad Santiago de Cali Santiago de CaliColombia

In the present industrial revolution era,the industrial mechanical system becomes incessantly highly intelligent and ***,it is necessary to develop data-driven and monitoring approaches for achieving quick,trustable,and high-quality analysis in an automated *** diagnosis is an essential process to verify the safety and reliability operations of rotating *** advent of deep learning(DL)methods employed to diagnose faults in rotating machinery by extracting a set of feature vectors from the vibration *** paper presents an Intelligent Industrial Fault Diagnosis using Sailfish Optimized Inception with Residual Network(IIFD-SOIR)*** proposed model operates on three major processes namely signal representation,feature extraction,and *** proposed model uses a Continuous Wavelet Transform(CWT)is for preprocessed representation of the original vibration *** addition,Inception with ResNet v2 based feature extraction model is applied to generate high-level ***,the parameter tuning of Inception with the ResNet v2 model is carried out using a sailfish ***,a multilayer perceptron(MLP)is applied as a classification technique to diagnose the faults *** experimentation takes place to ensure the outcome of the presented model on the gearbox dataset and a motor bearing *** experimental outcome indicated that the IIFD-SOIR model has reached a higher average accuracy of 99.6%and 99.64%on the applied gearbox dataset and bearing *** simulation outcome ensured that the proposed model has attained maximum performance over the compared methods.

关键词： Intelligent models fault diagnosis industrial control deep learning feature extraction

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Web Attack Detection Using the Input Validation Method:DPDA Theory

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Computers, Materials & Continua 2021年第9期68卷 3167-3184页

作者： Osamah Ibrahim khalaf Munsif Sokiyna Youseef Alotaibi Abdulmajeed Alsufyani Saleh Alghamdi Al-Nahrain University Al-Nahrain Nano Renewable Energy Research CenterBaghdadIraq Department of Management Information Systems Faculty of Science&Information TechnologyCyprus International UniversityNicosiaCyprus Department of Computer Science College of Computers and Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computers and Information Technology Taif UniversityTaif21944Saudi Arabia

A major issue while building web applications is proper input validation and *** can quickly exploit errors and vulnerabilities that lead to malicious behavior in web application validation *** are rapidly improving their capabilities and technologies and now focus on exploiting vulnerabilities in web applications and compromising ***-site scripting(XSS)and SQL injection attack(SQLIA)are attacks in which a hacker sends malicious inputs(cheat codes)to confuse a web application,to access or disable the application’s back-end without user *** this paper,we explore the problem of detecting and removing bugs from both client-side and server-side code.A new idea that allows assault detection and prevention using the input validation mechanism is *** addition,the project supports web security tests by providing easy-to-use and accurate models of vulnerability prediction and methods for *** these attributes imply a program statement that is vulnerable in an SQLIA,this can be evaluated and checked for a set of static code ***,we provide a script whitelisting interception layer built into the browser’s JavaScript engine,where the SQLIA is eventually detected and the XSS attack resolved using the method of input validation and script whitelisting under pushdown *** framework was tested under a scenario of an SQL attack and *** is demonstrated to offer an extensive improvement over the current *** framework’s main ability lies in the decrease of bogus *** has been demonstrated utilizing new methodologies,nevertheless giving unique access to sites dependent on the peculiarity score related to web *** proposed input validation framework is shown to identify all anomalies and delivers better execution in contrast with the current program.

关键词： Static dynamic detection prevention input validation deterministic push down automata

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