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Understanding pore characteristics through core-based petrographic and petrophysical analysis in a heterogeneous carbonate reservoir:A case study from the Mumbai Offshore Basin,India

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Petroleum Research 2023年第4期8卷 469-480页

作者： Ilius Mondal kumar hemant singh Department of Earth Science Indian Institute of TechnologyBombayIndia

Carbonate rocks exhibit complex and heterogeneous pore structures;such heterogeneity is manifested by the occurrence of a wide variety of pore types with different sizes and geometries as a result of depositional and diagenetic *** complications substantially increase the uncertainty of predicted rock hydraulic parameters because samples with comparable porosities might have very different permeability *** this study,small-scale characterisation of porosity and permeability in heterogeneous Eocene limestone samples from the Bassein Formation of the B-X structure of the MK Field in Mumbai Offshore Basin,India,was carried out,employing an integrated framework that in-corporates thin-section petrography,routine core analysis,mercury injection capillary pressure and nuclear magnetic resonance *** pore characteristics of these carbonates range from poor to *** studied samples exhibited large ranges of porosity,permeability and other associated petrophysical *** pore types,as well as their orientations and connectivity,are the primary factors causing the *** of the complexity of the pore networks,a simple lithofacies classification alone would have been insufficient to link porosity and *** reservoir char-acteristics in the study area are strongly linked to the development and/or destruction of reservoir porosity-permeability during different phases of ***-four carbonate core samples from the limestone unit were studied and classified into microfacies and pore type classes,producing an accurate assessment of reservoir *** comprehensive workflow incorporates the pore volume distributions and pore throat attributes for each rock *** carbonate microfacies were identified by petrographic analysis and their petrophysical characteristics,such as porosity,permeability,pore throat size,pore volume and fluid flow factors,were *** study demonstrates how macro-porosity

关键词： Carbonatereservoir Permeability Mercury injection capillary pressure Nuclear magnetic resonance Porosity partitioning

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Fluid substitution in NMR T_(2)distribution and resistivity independent saturation computation using synthetic capillary pressure data

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Petroleum Research 2023年第1期8卷 77-86页

作者： Ilius Mondal kumar hemant singh Department of Earth Science Indian Institute of Technology BombayIndia

Petrophysicists and reservoir engineers utilise the capillary pressure and saturation-height function for calculating the water saturation of any reservoir,at a given height above the free water *** results have a big impact on reserve *** majority of capillary pressure studies are carried out in labs with core ***,on the other hand,are usually altered from their original state before being delivered to ***,the accuracy of discrete sets of core data in describing entire reservoir parameters,is still up for *** of the capillary pressure curve in reservoir condition is an important subject that is challenging to *** use of nuclear magnetic resonance(NMR)logs for oil and gas exploration has grown in popularity over the last few ***,most of the time the utilization of the data is limited for evaluating porosity-permeability,distributions and computation of irreducible water *** the advent of fluid substitution methods,NMR T_(2)distributions may now be used to synthesize core equivalent capillary pressure *** fluid substitution workflow,our study introduces a better approach for obtaining capillary pressure curves from the NMR T_(2)*** available core data has been used to calculate calibration parameters for better saturation height *** workflow introduces a novel approach in resistivity independent saturation *** the exploratory wells of our study area,computed water saturation derived from the saturation height function exhibits encouraging agreement with resistivity based water saturation from multi-mineral *** NMR based saturation height modelling approach has been included in study area for the first time so far.

关键词： Carbonate reservoir NMR fluid Substitution Capillary pressure Saturation height function Resistivity independent saturation

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Petrophysical insights into pore structure in complex carbonate reservoirs using NMR data

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Petroleum Research 2024年第3期9卷 439-450页

作者： Ilius Mondal kumar hemant singh Department of Earth Science Indian Institute of Technology BombayIndia

The study delves into pore structure attributes within the complex Eocene carbonate of an Indian offshore field,encompassing pore throat,radius and their *** Magnetic Resonance(NMR)experimental data reveals crucial insights into pore structures and fluid *** study compares the NMR T_(2) distribution curve with capillary pressure data from the Mercury Injection Capillary Pressure(MICP)technique,deriving linear and nonlinear conversion coefficients to transform NMR T_(2) spectra into equivalent pore radius *** radius-dependent porosity partitioning,linked to permeability and the distribution of irreducible water,is conducted utilizing NMR-derived *** the T_(2) cut-off analysis,a two-segment fractal analysis of NMR T_(2) distribution is also carried *** analysis unveils associations between fractal dimensions and various petrophysical parameters,including permeability,porosity,T_(2)LM,irreducible water saturation and *** NMR-derived pore radius distribution is mostly unimodal,occasionally slightly *** different pore size classes(less than 0.05μm to more than 5μm)are analysed in relation to permeability,porosity and irreducible *** pores(<1μm)contribute more to irreducible water with low porosity and *** fractal dimension of large pores correlates strongly with porosity,permeability,T_(2)LM,irreducible water and Rso suggesting significant impact on reservoir seepage *** addition to porosity partitioning,the current study demonstrates effectiveness in modelling modified permeability and correlating it with in situ permeability when applied to field NMR log data from the study *** numerous studies focus on sandstone,our study marks the pioneering attempt at a comprehensive analysis on complex carbonate reservoirs.

关键词： Pore structure NMR T_(2)distribution Irreducible water Fractal analysis Permeability

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Core-log integration and application of machine learning technique for better reservoir characterisation of Eocene carbonates,Indian offshore

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Energy Geoscience 2022年第1期3卷 49-62页

作者： Ilius Mondal kumar hemant singh Indian Institute of Technology Bombay India

Rock types,pore structures and permeability are essential petrophysical outputs,and they contribute considerably to the highest degree of uncertainty in reservoir *** factors have a strong influence on exploration and field development *** analysis is the best approach for estimating permeability,assigning rock types and characterising pore *** logs are the most often employed method for estimating the parameters at each data point of reservoirs since there are more un-cored wells than cored *** intelligence,on the other hand,is gaining popularity in the geosciences due to the ever-increasing complexity and volume of available subsurface *** is also obvious in the demand for faster and more accurate interpretations in order to identify reservoir characteristics in increasingly difficult and complicated petroliferous *** Neural Networks and Self-Organizing Maps are examples of machine learning approaches that can be used in both supervised and unsupervised modes for modelling and *** carbonates of Mukta oilfield are the major pay rocks of strong geological heterogeneity in terms of their porosity and permeability relationship with pore *** paper outlines a novel method of rock fabric classification,pore structure characterization,flow unit classification and robust reservoir permeability modelling based on an integrated approach that incorporates core measurements,log data and machine learning *** pore structure has been characterised by the combination of conventional core,capillary pressure and nuclear magnetic resonance *** neural network has added an adequate benefit in accurate permeability modelling by utilizing the concepts of rock classifications and hydraulic flow units.

关键词： Permeability Microfacies MICP NMR Hydraulic flow unit Artificial neural network Reservoir characterisation

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Characterizing large-scale weak interlayer shear zones using conditional random field theory

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Journal of Rock Mechanics and Geotechnical Engineering 2023年第10期15卷 2611-2625页

作者： Gang Han Chuanqing Zhang hemant kumar singh Rongfei Liu Guan Chen Shuling Huang Hui Zhou Yuting Zhang Key Laboratory of Geotechnical Mechanics and Engineering of the Ministry of Water Resources Changjiang River Scientific Research InstituteWuhanChina State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhanChina University of Chinese Academy of Sciences BeijingChina Department of Petroleum Engineering and Geoengineering Rajiv Gandhi Institute of Petroleum TechnologyJaisAmethi229304India State Key Laboratory of Water Resources and Hydropower Engineering Science Institute of Engineering Risk and Disaster PreventionWuhan UniversityWuhan430072China Institute for Risk and Reliability Leibniz Universität HannoverHannover30167Germany

The shear behavior of large-scale weak intercalation shear zones(WISZs)often governs the stability of foundations,rock slopes,and underground ***,due to their wide distribution,undulating morphology,complex fabrics,and varying degrees of contact states,characterizing the shear behavior of natural and complex large-scale WISZs precisely is *** study proposes an analytical method to address this issue,based on geological fieldwork and relevant experimental *** analytical method utilizes the random field theory and Kriging interpolation technique to simplify the spatial uncertainties of the structural and fabric features for WISZs into the spatial correlation and variability of their mechanical *** Kriging conditional random field of the friction angle of WISZs is embedded in the discrete element software 3DEC,enabling activation analysis of WISZ C2 in the underground caverns of the Baihetan hydropower *** results indicate that the activation scope of WISZ C2 induced by the excavation of underground caverns is approximately 0.5e1 times the main powerhouse span,showing local ***,the overall safety factor of WISZ C2 follows a normal distribution with an average value of 3.697.

关键词： Interlayer shear weakness zone Baihetan hydropower station Conditional random field Kriging interpolation technique Activation analysis

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A Classification Algorithm to Improve the Design of Websites

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Journal of Software Engineering and Applications 2012年第7期5卷 492-499页

作者： hemant kumar singh Brijendra singh Department of Computer Applications Azad Institute of Engineering & Technology Lucknow India Department of Computer Science University of Lucknow Lucknow India

In very short time today web has become an enormously important tool for communicating ideas, conducting business and entertainment. At the time of navigation, web users leave various records of their action. This vast amount of data can be a useful source of knowledge for predicting user behavior. A refined method is required to carry out this task. Web usages mining (WUM) is the tool designed to do this task. WUM system is used to extract the knowledge based on user behavior during the web navigation. The extracted knowledge can be used for predicting the users’ future request when user is browsing the web. In this paper we advanced the online recommender system by using a Longest Common Subsequence (LCS) classification algorithm to classify users’ navigation pattern. Classification using the proposed method can improve the accuracy of recommendation and also proposed an algorithm that uses LCS method to know the user behavior for improvement of design of a website.

关键词： Web Usage Mining Web Personalization Recommender Systems Classification Algorithms

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Energy and Emission Reduction Potential for Bank ATM Units in India

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Open Journal of Energy Efficiency 2016年第4期5卷 107-120页

作者： hemant kumar singh Ravi Prakash Karunesh kumar Shukla Department of Mechanical Engineering Motilal Nehru National Institute of Technology Allahabad India Department of Applied Mechanics Motilal Nehru National Institute of Technology Allahabad India

With the growing economy of India, banking sector growth has led to installation of thousands of Automatic Teller Machines (ATMs) throughout the country. ATMs provide 24 × 7 services as well as operate at low-temperature ranges of cooling, hence have high operating energy costs. Insulating an ATM’s envelope is not a prevalent technique in India. In the present study, an effort has been made to determine the optimum insulation thickness for three different insulation materials for the typical ATM envelope in four different climatic zones of India. Life cycle savings and payback periods for various insulation materials are also evaluated. Further, these optimally insulated ATM envelopes can be integrated with grid connected rooftop solar PV systems. The energy saving and emissions reduction potential due to these two interventions have been estimated on the national basis. Altogether in the four selected climate zones, energy saving of 17% - 30% provides the annual economic benefit of Indian National Rupees (Rs.) 3570 million with annual carbon reduction potential of about 0.60 million tCO2. From this study, it is observed that properly insulated ATMs integrated with rooftop solar PV systems, can significantly reduce the energy costs as well as carbon emissions in India’s context.

关键词： Life Cycle Cost Optimum Insulation Thickness Life Cycle Saving Solar PV Payback Period Carbon Emissions

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Impact of Climate Change on Diseases of Crops and Their Management-A Review

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Journal of Agricultural Science and Technology(B) 2022年第1期12卷 1-15页

作者： Manish kumar Maurya Vikash kumar Yadav Sumant Pratap singh Rajender Jatoth hemant kumar singh Dinesh singh Department of Plant Pathology Acharya Narendra Deva University of Agriculture and TechnologyKumarganjAyodhya 224229(U.P.)India Department of Plant Molecular Biology and Genetic Engineering Acharya Narendra Deva University of Agriculture and TechnologyKumarganjAyodhya 224229(U.P.)India Division of Plant Pathology ICAR-Indian Agricultural Research InstituteNew Delhi110012 India

Change in global climate is primarily due to rising concentrations of greenhouse gases in the atmosphere that is mostly caused by human *** important factors affecting the occurrence and spread of the plant diseases are temperature,moisture,light,and CO_(2) *** factors cause physiological changes in plants that result in increase in intensity of crop *** change causes a significant impact on germination,reproduction,sporulation and spore dispersal of *** change affects all life stages of the pathogen as well as its host to cause impact on host-pathogen interaction which facilitates the emergence of new races of the pathogen ultimately breakdowns the host *** also affects the microbial community in the soil which is beneficial to the plants in various *** minor diseases become major ones due to alteration in climatic parameters thus posing a threat to the food security.

关键词： Climate change greenhouse gases temperature elevated CO_(2) pathogens sporulation

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Spray Prediction Model for Aonla Rust Disease Using Machine Learning

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Journal of Agricultural Science and Technology(B) 2023年第1期13卷 1-12页

作者： hemant kumar singh Bhanu Pratap S.K.Maheshwari Ayushi Gupta Anuradha Chug Amit Prakash singh Dinesh singh Acharya Narendra Deva University of Agriculture and Technology Ayodhya 224229U.P.India ICAR-Central Institute for Arid Horticulture Bikaner 334006RajasthanIndia University School of Information Communication&TechnologyGGSIPUNew Delhi 110012India ICAR-Indian Agricultural Research Institute New Delhi 110012India

Disease prediction in plants has acquired much attention in recent *** factors such as:temperature,relative humidity,rainfall,sunshine play an important role in a plan’s growth only if they are present in adequate amounts as required by the *** the other hand,if the factors are inadequate,they may also support the growth of a disease in the *** current study focuses on the Rust disease in Aonla fruits and leaves by utilizing a real time dataset of weather *** different models are tested for spray prediction on conducive *** resampling techniques,random over sampling(ROS)and synthetic minority oversampling technique(SMOTE)have been used to balance the dataset and five different classifiers:support vector machine(SVM),logistic regression(LR),k-nearest neighbor(kNN),decision tree(DT)and random forest(RF)have been used to classify a particular day based on weather conditions as conducive or *** classifiers are then evaluated based on four performance metrics:accuracy,precision,recall and *** results indicate that for imbalanced dataset,kNN is appropriate with high precision and recall *** both balanced and imbalanced dataset models,the proposed model SMOTE-RF performs best among all models with 94.6%accuracy and can be used in a real time application for spray ***,timely fungicide spray prediction without over spraying will help in better productivity and will prevent the yield loss due to rust disease in Aonla crop.

关键词： Aonla Internet of Things machine learning plant disease rust spray prediction.

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Grid Tied Solar PV System with Power Quality Enhancement Using Adaptive Generalized Maximum Versoria Criterion

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CSEE Journal of Power and Energy Systems 2023年第2期9卷 722-732页

作者： Manoj Badoni Alka singh Ankit kumar singh hemant Saxena Rajeev kumar Delhi Technological University Delhi 110042India.A.K.Singh is with Netaji Subhas University of TechnologyDelhi 110078India Netaji Subhas University of Technology Delhi 110078India Electrical and Electronics Engineering Department KIET Group of InstitutionsGhaziabadIndia Electrical Engineering Department Jamia Millia IslamiaNew DelhiIndia

A three phase grid tied solar photovoltaic(PV)system with power quality compensation features is presented in this *** system is used to transfer power generated from a solar PV array to feed linear and nonlinear loads along with compensation for several power quality(PQ)issues,such as harmonics,redundant reactive power and load *** generated DC power from the PV array is converted into AC by implementing a three-phase voltage source converter(VSC).In order to transfer active power and mitigate PQ problems,an efficient control technique is required for the grid tied solar PV *** study presents the use of an adaptive generalized maximum Versoria criterion(AGMVC)controller for VSC used in a solar PV energy conversion *** utilization of the solar PV array is accomplished by using the Perturb and Observe based maximum power point tracking(MPPT)*** experimental setup of the grid integrated PV system is implemented in the laboratory using an IGBT based VSC and DSP(dSPACE DS-1202).The performance of the AGMVC control technique is verified experimentally using laboratory *** control technique is compared with different conventional controllers,such as synchronous reference frame theory(SRFT)and instantaneous reactive power theory(IRPT)along with recently developed weight-based controllers viz.,least mean square(LMS),least mean mixed norm(LMMN)and normalized kernel least mean fourth-neural network(NKLMFNN).Numerous terms,such as fundamental weight convergence,steady state error,computational complexity,phase lock loop(PLL)requirement and harmonic compensation capability,are considered for comparison purposes of AGMVC with the above listed control *** system performance is verified according to the IEEE-519 standard.

关键词： Harmonics maximum versoria criterion power factor corection(PFC) solar photovoltaic

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