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  • 1
    Online Resource
    Online Resource
    [San Rafael, California] : Morgan & Claypool Publishers | [Cham, Switzerland] : Springer
    UID:
    b3kat_BV048595036
    Format: 1 Online-Ressource (xx, 276 Seiten) , Illustrationen, Diagramme
    Edition: Second edition
    ISBN: 9783031017643
    Series Statement: Synthesis lectures on computer architecture #49
    Additional Edition: Erscheint auch als Druck-Ausgabe, Hardcover ISBN 978-3-031-00061-4
    Additional Edition: Erscheint auch als Druck-Ausgabe, Paperback ISBN 978-3-031-00636-4
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Cache-Speicher ; Speicher ; Konsistenz
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    Cambridge, Massachusetts :Gulf Professional Publishing,
    UID:
    almahu_9949697709702882
    Format: 1 online resource (434 pages)
    ISBN: 0-323-85466-4
    Series Statement: The Fundamentals and Sustainable Advances in Natural Gas Science and Eng
    Note: Intro -- Sustainable Geoscience for Natural Gas SubSurface Systems -- Copyright -- Contents -- Contributors -- Preface -- About The Fundamentals and Sustainable Advances in Natural Gas Science and Engineering Series -- About this volume 2: Sustainable geoscience for natural gas subsurface systems -- Chapter One: Pore-scale characterization and fractal analysis for gas migration mechanisms in shale gas reservoirs -- 1. Introduction -- 2. Pore-scale characterization from nitrogen adsorption-desorption data -- 3. Pore-scale characterization from SEM data -- 4. Definitions of fractal parameters -- 5. Fractal analysis of nitrogen adsorption isotherms -- 6. Fractal analysis of SEM images -- 7. Pore-scale and core-scale gas transport mechanisms -- 7.1. Gas transport in a single capillary -- 7.2. Gas transport in fractal porous media -- 8. Conclusions -- Acknowledgments -- References -- Chapter Two: Three-dimensional gas property geological modeling and simulation -- 1. Introduction -- 2. 3D modeling -- 3. Geological conditions of gas reservoirs -- 4. Typical earth data used in modeling -- 5. Modeling methods -- 6. Structural modeling -- 7. Facies modeling -- 8. Petrophysical modeling -- 9. Geomechanical modeling -- 10. Volumetric modeling -- 11. Case study -- 12. 3D structural modeling -- 13. 3D facies modeling -- 14. 3D petrophysical modeling -- 15. 3D geomechanical modeling -- 16. Summary -- References -- Chapter Three: Acoustic, density, and seismic attribute analysis to aid gas detection and delineation of reservoir properties -- 1. Introduction -- 2. Natural gas reservoirs detection -- 2.1. Poststack seismic attributes analysis -- 2.1.1. Acoustic and velocity attributes: Direct gas indicators -- 2.1.2. Bottom simulating reflector -- 2.1.3. Gas chimneys -- 2.1.4. Acoustic impedance -- 2.1.5. Other seismic attributes. , 2.2. Prestack seismic attributes analysis -- 3. Delineation and characterization of natural gas reservoirs -- 3.1. Porosity -- 3.2. Pore types -- 3.3. Water saturation -- 3.4. Hydraulic and electrical flow units -- 3.5. Rock mechanical properties -- 4. Summary -- References -- Chapter Four: Integrated microfacies interpretations of large natural gas reservoirs combining qualitative and quantitative ... -- 1. Introduction -- 2. Fundamental concepts and key principles -- 2.1. Principals of petrographic analysis -- 2.2. Thin section analysis -- 2.3. SEM analysis -- 2.4. The evolution of microfacies analysis -- 3. Advanced research and detailed techniques -- 3.1. Image preparation via histogram equalization -- 3.2. Grain size determination and grain-size distributions -- 3.3. Edges, features shapes, and boundaries detection -- 3.4. Applying image arithmetic to enhance features of specific interest -- 3.5. Gamma correction for birefringent minerals -- 3.6. K-means clustering to isolate and quantify two-dimensional porosity and specific surface area -- 3.7. Nearest neighbor (kNN) classifier facilitates features segmentation -- 4. Gas field case studies -- 4.1. South pars field -- 4.2. Salman field -- 4.3. Shah Deniz field -- 5. Summary -- Declarations -- References -- Chapter Five: Assessing the brittleness and total organic carbon of shale formations and their role in identifying optimu ... -- 1. Introduction -- 2. Fundamental concepts -- 2.1. Estimating shale brittleness and ``fracability´´ -- 2.2. Estimating total organic carbon from well-log data -- 3. Advanced methods -- 3.1. Machine learning approaches for predicting shale brittleness and TOC -- 3.2. Advantages of transparency and correlation-free machine learning algorithms -- 3.3. Optimizers suitable for TOB stage 2 predictions. , 3.4. Measures of BI and TOC prediction accuracy assessed for shale assessment -- 4. Case study: TOB machine learning to predict shale brittleness and TOC -- 4.1. Characterization of two lower Barnett Shale Wells sections -- 4.2. Results of TOB predictions of BIml and TOC for lower Barnett Shale Wells -- 5. Summary -- Declarations -- References -- Chapter Six: Shale kerogen kinetics from multiheating rate pyrolysis modeling with geological time-scale perspectives for ... -- 1. Fundamental concepts -- 1.1. Organic-rich shales and their gas and oil generation potential -- 1.2. Types of kerogen and their associated gas and oil generation reactions -- 1.3. Pyrolysis of organic-rich shales, kerogens and bitumens -- 2. Advanced techniques and applications -- 2.1. Modeling kerogen kinetics with the Arrhenius equation and its integral -- 2.2. Procedure for matching pyrolysis S2 curves with calculated TTIARR and SigmaTTIARR values -- 2.3. Controversy over methods used to fit multiheating rate shale pyrolysis S2 curves -- 2.4. Combining reaction peaks generated by various E-A combinations -- 2.5. Limitations of single-heating rate pyrolysis experiments -- 3. Case study kinetic models for immature Duvernay shale Western Canada -- 3.1. Case study overview -- 3.2. Late Devonian Duvernay shale (Western Canada) -- 3.3. Immature Duvernay shale sample SAP for reaction kinetic evaluations -- 4. Summary -- Declarations -- References -- Chapter Seven: Application of few-shot semi supervised deep learning in organic matter content logging evaluation -- 1. Introduction -- 2. Methodology -- 2.1. ELM-SAE model structure -- 2.2. Stacked ELM-SAE -- 2.3. RBM -- 2.4. DBM -- 2.5. Bagging algorithm -- 2.6. Network structure of the integrated deep learning model (IDLM) -- 3. Samples and experiments -- 3.1. Data sets and descriptions -- 3.2. Training. , 3.2.1. Determination of hyperparameter (SELM-SAE) -- 3.2.2. Determination of hyperparameter (DBM) -- 3.2.3. Hyperparameter determination results for models including bagging -- 4. Results: TOC Prediction comparisons for IDLM and other models -- 5. Conclusions -- Acknowledgment -- References -- Chapter Eight: Microseismic analysis to aid gas reservoir characterization -- 1. Introduction -- 2. Principle and workflow of microseismic monitoring -- 2.1. Basic principles -- 2.2. Technical workflow -- 3. Advanced processing and interpretation techniques -- 3.1. Processing -- 3.1.1. Microseismic detection and location -- 3.1.2. Source mechanism inversion -- 3.1.3. Stress inversion -- 3.2. Interpretation -- 3.2.1. Reservoir interpretation -- 3.2.2. Microseismic geomechanics -- 4. Case studies -- 4.1. Shale hydraulic fracturing -- 4.2. Coal-bed methane reservoir -- 5. Summary -- Declarations -- Acknowledgments -- References -- Chapter Nine: Coal-bed methane reservoir characterization using well-log data -- 1. Introduction -- 2. Fundamental concepts pertaining to CBM -- 2.1. Estimating coal composition and rank using well-log data -- 2.2. Estimating gas content, potential flow rates and recovery from coals with well-log data -- 3. Advanced assessment of coal bed methane properties -- 3.1. Coal structure and fracability -- 3.2. A geomechanically derived brittleness index -- 3.3. Horizontal stress regime influence on coal seam characteristics -- 3.4. Assessing the structure of coal and its influences on fracability -- 3.5. The presence of existing natural fractures improves coal fracability -- 3.6. Machine learning to improve coal property predictions -- 4. Case study: Assessing coal fracability based on well-log information -- 4.1. Application of fracability indicators to actual coal seams. , 4.2. Application of geomechanical coefficients to classify coal structure -- 5. Summary -- Declarations -- References -- Chapter Ten: Characterization of gas hydrate reservoirs using well logs and X-ray CT scanning as resources and environmen ... -- 1. Introduction -- 2. Fundamental concepts and key principles -- 2.1. Well logging -- 2.2. X-ray CT scanning -- 2.2.1. Gas hydrate pore habits in hydrate-bearing sediments -- 2.2.2. Basic physical properties in hydrate-bearing sediments -- 3. Advanced research/field applications -- 3.1. Well logging and X-ray CT scanning combination -- 3.2. X-ray CT based characterization of pore fractal characteristics in hydrate-bearing sediments -- 3.2.1. Maximal pore diameter -- 3.2.2. Pore area fractal dimension -- 3.2.3. Tortuosity fractal dimension -- 4. Case studies -- 4.1. Archie's saturation exponent for well-log data interpretation -- 4.2. Hydraulic permeability reduction in hydrate-bearing sediments -- 5. Summary and conclusions -- Acknowledgments -- Declarations -- References -- Chapter Eleven: Assessing the sustainability of potential gas hydrate exploitation projects by integrating commercial, en ... -- 1. Fundamental concepts -- 1.1. The potential and challenges facing natural gas hydrates as resources for development -- 1.1.1. Technical considerations -- 1.1.2. Economic, environmental, infrastructure, and social considerations -- 1.2. Multicriteria decision analysis (MCDA) techniques -- 1.2.1. MCDA techniques typically applied -- 1.2.2. ELECTRE -- 1.2.3. TOPSIS (the order of preference by similarity to an ideal solution) -- 2. Advanced TOPSIS techniques that incorporate uncertainty -- 2.1. Crisp, fuzzy and intuitionistic mathematical alternatives -- 2.2. Fuzzy TOPSIS calculations -- 2.3. Fuzzy TOPSIS analysis incorporating objective entropy weighting. , 2.4. Intuitionistic Fuzzy TOPSIS (IFT) with and without entropy weight adjustments.
    Additional Edition: ISBN 0-323-85465-6
    Language: English
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  • 3
    Online Resource
    Online Resource
    Cambridge, MA ; : Gulp Professional Publishing, an imprint of Elsevier,
    UID:
    almahu_9948026356202882
    Format: 1 online resource (678 pages)
    ISBN: 0-12-813783-5 , 0-12-813782-7
    Note: Front Cover -- Formation Damage During Improved Oil Recovery -- Copyright Page -- Dedication -- Contents -- List of Contributors -- Preface -- 1. Overview of Formation Damage During Improved and Enhanced Oil Recovery -- 1.1 Introduction -- 1.2 Summary of Formation Damage during EOR -- 1.3 Low-Salinity Water Flooding (LSWF) -- 1.4 Chemical Flooding -- 1.5 Thermal Recovery in Heavy Oil -- 1.6 Produced-Water-Re-Injection (PWRI) -- 1.7 CO2 Flooding -- 1.8 Hydraulic Fracturing in Shale Formations -- 1.9 Coal-Bed Methane (CBM) -- 1.10 Geothermal Reservoirs -- 1.11 Deepwater Reservoirs -- 1.12 Summary -- References -- 2. Low-Salinity Water Flooding: from Novel to Mature Technology -- 2.1 Introduction -- 2.2 Origins of LSWF and Identification of Reservoir Mechanism Driving Incremental Oil Recovery -- 2.3 Fines Migration: Detachment, Transport, and Redeposition -- 2.4 Clay Swelling, Detachment, and Pore Blocking Leading to Reductions in Permeability and Porosity -- 2.5 Salinity Thresholds and Reservoir Heterogeneity Influences on Particle Detachment -- 2.6 Exploiting Pore Plugging to Preferentially Enhance Oil Recovery -- 2.6.1 Quantifying and modeling fines migration and pore plugging -- 2.6.2 LSWF to induce fines-migration-related formation damage -- 2.6.3 Enhanced sweep efficiency by induced fines migration during LSW flooding -- 2.7 Factors Influencing EOR in Sandstone Reservoirs Subjected to LSWF -- 2.8 Relationships Between Oil Recovery, Salinity, and Wettability Variables -- 2.9 Wetting Mechanisms in Carbonates and Sandstones -- 2.10 Example Field Field-scale Tests and Outcomes of LSWF -- 2.11 Potential to Combine LSWF with Other IOR Mechanisms -- 2.11.1 LSWF combined with surfactants -- 2.11.2 LSWF combined with polymers -- 2.11.3 LSWF combined with CO2 water-alternating gas injection -- 2.11.4 LSWF combined with nanofluid treatments. , 2.12 Conclusions -- Nomenclature -- References -- 3. Formation Damage by Fines Migration: Mathematical and Laboratory Modeling, Field Cases -- 3.1 Introduction -- 3.2 Governing Equations for Flow with Fines Migration -- 3.2.1 Torque balance of forces acting on particle -- 3.2.2 Using the torque balance to derive expressions for the maximum retention function -- 3.2.2.1 Internal filter cake of multilayer with mono-sized fine particles -- 3.2.2.2 Monolayer of multisized fine particles -- 3.2.3 Single-phase equations for fines transport -- 3.3 Fines Migration Resulting from High Fluid Velocities -- 3.3.1 Formulation of mathematical model -- 3.3.2 Exact analytical solution for 1D problem -- 3.3.3 Qualitative analysis of the solution -- 3.3.4 Analysis of laboratory data -- 3.4 Productivity Decline due to Fines Migration -- 3.4.1 Mathematical formulation -- 3.4.2 Analytical solution -- 3.4.3 Calculation of impedance -- 3.5 Fines Detachment and Migration at Low Salinity -- 3.5.1 1D analytical solution with instant fines detachment -- 3.5.1.1 Qualitative analysis of the model -- 3.5.2 Tuning experimental data -- 3.5.3 Well injectivity decline during low-salinity water injection -- 3.5.3.1 Qualitative analysis of the model -- 3.5.3.2 Injectivity decline prediction -- 3.5.4 Field cases -- 3.6 Effects of Nonequilibrium/Delay in Particle Detachment on Fines Migration -- 3.6.1 Introduction of a delay in detachment -- 3.6.2 Exact solution for 1D problem accounting for delay with detachment -- 3.6.3 Analysis of laboratory data and tuning of the model coefficients -- 3.6.4 Semianalytical model for axisymmetric flow -- 3.6.5 Prediction of injection well behavior -- 3.7 Two-Phase Fines Migration During Low-Salinity Waterflood: Analytical Modeling -- 3.7.1 Fines migration in two-phase flow -- 3.7.2 Splitting method for integration of two-phase systems. , 3.7.3 Exact solution for the auxiliary system -- 3.7.4 Lifting equation -- 3.7.5 Inverse mapping -- 3.7.6 Implementation of fines migration using reservoir simulators -- 3.8 Conclusions -- Nomenclature -- Greek symbols -- Super/Subscripts -- References -- 4. Using Nanofluids to Control Fines Migration in Porous Systems -- 4.1 Introduction -- 4.2 Laboratory Proof and Field Cases -- 4.3 Nanoparticles Transport in Porous Media: Adsorption, Straining, and Detachment Behaviors -- 4.4 Effectiveness of Nanoparticles Utilization to Mitigate Fines Migration in Water Flow -- 4.4.1 Approach I: Coinjection of nanoparticles and fines into porous media -- 4.4.2 Approach II: Precoat porous media with nanofluids prior to fines invasion -- 4.5 Using Nanoparticles to Control Fines Suspension in Oil and Water-Saturated Porous Systems -- 4.5.1 Nanofluid coinjection to reduce fines migration in two mobile fluids -- 4.5.2 Nanofluid preflush to control fines migration in a radial flow system saturated with two immiscible fluids -- 4.6 Combined Nanofluids with Low-Salinity Waterflooding -- 4.7 Conclusions -- Nomenclature -- References -- Appendix A: Method of Characteristics to Solve System of Quasilinear First-order Partial Differential Equations (PDEs) -- 5. Formation Damage by Inorganic Deposition -- 5.1 Introduction -- 5.2 Types of Scales in Formation Damage -- 5.2.1 Carbonate scales -- 5.2.2 Sulfate scales -- 5.2.3 Other inorganic solids -- 5.3 Processes of Scale Formation -- 5.3.1 Solubility and supersaturation -- 5.3.2 Dynamics of scale formation -- 5.3.3 Formation damage from scale deposition -- 5.3.4 Scale inhibitors -- 5.4 Management of Scaling in Development and Production -- 5.4.1 Water sampling and analysis -- 5.4.2 Options for scale prevention and remediation -- 5.4.2.1 Removal of the scaling ions before mixing occurs. , 5.4.2.2 Passive scale treatment in well completion -- 5.4.2.3 Periodic squeeze treatments -- 5.5 Summary -- References -- 6. Formation Damage by Organic Deposition -- 6.1 Introduction, Definition, Existence State of Asphaltene in Crude Oil, Molecular Structure of Asphaltene, Monitoring, an... -- 6.1.1 Introduction -- 6.1.2 Definition -- 6.1.3 Molecular structure of asphaltene -- 6.1.4 Monitoring and remediation -- 6.1.5 Experimental techniques to determine asphaltene-onset-pressure and wax-appearance-temperature -- 6.2 Asphaltene Formation Mechanisms Review: Precipitation, Aggregation and Deposition Mechanism, Solubility -- 6.2.1 Asphaltene precipitation -- 6.2.2 Solubility parameter -- 6.2.3 Asphaltene precipitation models -- 6.2.3.1 Coloidal model -- 6.2.3.2 Thermodynamic model -- 6.2.4 Asphaltene deposition -- 6.3 Issues With Asphaltene Deposition -- 6.3.1 Asphaltene issues during oil production -- 6.3.2 Formation damage and field experience -- 6.3.3 Asphaltene deposition during CO2 flooding -- 6.4 Deposition in Porous Media -- 6.4.1 Microfluidic experiments -- 6.4.1.1 Asphaltene depostion in capillary flow -- 6.4.2 Taylor Couette device studies -- 6.4.3 (Imaging) Core flood experiments -- 6.4.4 Porous media studies -- 6.5 Permeability Damage Models -- 6.5.1 Permeability reduction: effect of surface deposition and pore plugging -- 6.5.2 Plugging and nonplugging parallel pathways model -- 6.5.3 Power-law permeability reduction -- 6.5.4 Case studies: evaluation of surface deposition and pore plugging effects -- 6.5.4.1 Particle to pore size ratio -- 6.5.5 Effect of flow rate-particle entrainment -- 6.6 Conclusions -- References -- Further Reading -- 7. Formation Damage During Chemical Flooding -- 7.1 Introduction -- 7.2 Formation Damage by Polymer Flooding -- 7.2.1 The retention of polymers in the porous medium -- 7.2.1.1 Adsorption retention. , 7.2.1.1.1 Mechanism of polymer adsorption retention -- 7.2.1.1.2 Factors influencing adsorption retention -- 7.2.1.2 Mechanical trapping -- 7.2.1.3 Hydraulic retention -- 7.2.2 Incompatibility of polymer solution with formation -- 7.2.2.1 Incompatibility of polymer solution with formation fluids -- 7.2.2.1.1 Incompatibility of polymer solution with formation water -- 7.2.2.1.2 Incompatibility of polymer solution with crude oil -- 7.2.2.1.3 Incompatibility of polymer solution with formation rocks -- 7.3 Formation Damage by Surfactant/Polymer Binary Combination Flooding -- 7.3.1 Precipitation of the surfactants -- 7.3.2 Emulsification -- 7.3.3 Phase separation -- 7.4 Formation Damage by Ternary Combination Flooding -- 7.4.1 Roles of each component in ASP system -- 7.4.1.1 Roles of alkali in ASP systems -- 7.4.1.2 Role of surfactant in ASP system -- 7.4.1.3 Role of polymer in ASP system -- 7.4.2 Formation damage by ASP flooding -- 7.4.2.1 Scale formation due to alkaline -- 7.4.2.2 Scale formation due to surfactant -- 7.4.2.3 Scale formation due to polymer -- 7.4.3 Main factors affecting the scaling during ASP flooding -- 7.4.3.1 Mineral composition -- 7.4.3.2 Ionic concentration -- 7.4.3.3 Colloidal matters -- 7.4.3.4 Temperature and pressure -- 7.4.3.5 pH value -- 7.4.3.6 Flow velocity and flow state -- 7.4.4 Scaling mitigation and prevention techniques -- 7.4.4.1 Chemical techniques to prevent scaling -- 7.4.4.2 Physical techniques to prevent scaling -- 7.5 Summary and Conclusions -- References -- 8. Formation Damage Problems Associated With CO2 Flooding -- 8.1 Introduction -- 8.1.1 Review of CO2 flooding sites -- 8.1.2 Formation damage in CO2 EOR fields -- 8.2 CO2 Flooding Formation Damage Mechanisms -- 8.2.1 Overview of formation damage induced by CO2 injection -- 8.2.2 Interactions between CO2 and rock minerals -- 8.2.2.1 Dissolution. , 8.2.2.2 Precipitation.
    Language: English
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  • 4
    UID:
    b3kat_BV046867905
    Format: 1 Online-Ressource (843 Seiten) , Illustrationen, Diagramme
    Edition: Fifteenth edition, global edition
    ISBN: 9781292353289
    Note: Auf der E-Book Central Frontpage: "Enhanced EBook, global edition"
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-1-292-35336-4
    Language: English
    Subjects: Computer Science , Economics
    RVK:
    RVK:
    Keywords: Rechnungswesen ; Informationssystem
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  • 5
    UID:
    almahu_9949497684302882
    Format: 1 online resource (XX, 276 p.)
    Edition: 2nd ed. 2020.
    ISBN: 3-031-01764-1
    Series Statement: Synthesis Lectures on Computer Architecture,
    Content: Many modern computer systems, including homogeneous and heterogeneous architectures, support shared memory in hardware. In a shared memory system, each of the processor cores may read and write to a single shared address space. For a shared memory machine, the memory consistency model defines the architecturally visible behavior of its memory system. Consistency definitions provide rules about loads and stores (or memory reads and writes) and how they act upon memory. As part of supporting a memory consistency model, many machines also provide cache coherence protocols that ensure that multiple cached copies of data are kept up-to-date. The goal of this primer is to provide readers with a basic understanding of consistency and coherence. This understanding includes both the issues that must be solved as well as a variety of solutions. We present both high-level concepts as well as specific, concrete examples from real-world systems. This second edition reflects a decade of advancements since the first edition and includes, among other more modest changes, two new chapters: one on consistency and coherence for non-CPU accelerators (with a focus on GPUs) and one that points to formal work and tools on consistency and coherence.
    Note: Preface to the Second Edition -- Preface to the First Edition -- Introduction to Consistency and Coherence -- Coherence Basics -- Memory Consistency Motivation and Sequential Consistency -- Total Store Order and the \lowercase {X -- Relaxed Memory Consistency -- Coherence Protocols -- Snooping Coherence Protocols -- Directory Coherence Protocols -- Advanced Topics in Coherence -- Consistency and Coherence for Heterogeneous Systems -- Specifying and Validating Memory Consistency Models and Cache Coherence -- Authors' Biographies .
    Additional Edition: ISBN 3-031-00061-7
    Additional Edition: ISBN 3-031-00636-4
    Language: English
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  • 6
    Online Resource
    Online Resource
    Cambridge, Massachusetts ; : Gulf Professional Publishing,
    UID:
    almahu_9949225639002882
    Format: 1 online resource (412 pages)
    ISBN: 0-323-85956-9
    Series Statement: Fundamentals and sustainable advances in natural gas science and engineering series ; 1
    Note: Includes index. , Intro -- Sustainable Natural Gas Reservoir and Production Engineering -- Copyright -- Contents -- Contributors -- Preface -- About the fundamentals and sustainable advances in natural gas science and engineering series -- About volume 1: sustainable natural gas reservoir and production engineering -- Chapter One: Gas properties, fundamental equations of state and phase relationships -- 1. Introduction to natural gas -- 1.1. Composition of natural gas -- 1.2. Classification of natural gas -- 1.3. Measurement standards -- 2. Gas equation of state -- 2.1. Equation of state -- 2.2. Calculation of compressibility factor -- 3. Physical and thermodynamic properties of natural gas -- 3.1. Relative molecular mass -- 3.2. Density of natural gas -- 3.3. Critical parameters and reduced parameters -- 3.4. Enthalpy of natural gas -- 3.5. Entropy of natural gas -- 3.6. Specific heat capacity of natural gas -- 3.7. Joule-Thompson coefficient -- 3.8. Calorific value of natural gas -- 3.9. Explosion limit of natural gas -- 3.10. Viscosity of natural gas -- 3.11. Thermal conductivity coefficient of natural gas -- 4. Phase relationships of natural gas -- 4.1. Dew point and bubble point of natural gas -- 4.2. Vaporization rate of natural gas -- 5. Summary -- References -- Chapter Two: Natural gas demand prediction: Methods, time horizons, geographical scopes, sustainability issues, and scenarios -- 1. Introduction -- 2. Fundamentals of natural gas demand prediction requirements -- 3. Advanced aspects of natural gas demand prediction methodologies -- 3.1. Identifying relevant published research on gas prediction -- 3.2. Analysis of gas prediction methodologies applied based on the relevant published research identified -- 3.2.1. Questions addressed in the analysis -- 3.2.2. Insight gained from analysis of published gas prediction studies. , 3.2.3. Prediction time horizons and geographical scopes -- 3.2.4. Sustainable development features considered in published studies -- 4. Case study: A learning scenario development model providing sustainable global natural gas demand predictions -- 5. Summary -- A. Appendix -- References -- Chapter Three: Machine learning to improve natural gas reservoir simulations -- 1. Introduction -- 2. Fundamental concepts and key principles -- 2.1. Reservoir simulation -- 2.2. Governing equations of gas reservoir simulations -- 3. Advanced research/field applications -- 3.1. Application of ML in data preprocessing and prediction of properties -- 3.2. Application of ML in governing equations and numerical solutions -- 3.3. Application of ML in history matching -- 3.4. Application of ML in proxy modeling and optimization -- 4. Case study: Dew point prediction for gas condensate reservoirs -- 4.1. Dew point pressure -- 4.2. Data analysis -- 4.3. ANN-TLBO model design -- 4.4. CNN model design -- 4.5. Overfitting and appropriate remedies -- 4.6. Evaluation and discussion -- 5. Summary -- Chapter Three. References -- References -- Chapter Three. References -- References -- Chapter Four: In situ stress and mechanical properties of unconventional gas reservoirs -- 1. Introduction -- 2. Fundamental concepts and key principles -- 2.1. In situ stress -- 2.2. Mechanical properties of unconventional reservoirs -- 2.2.1. Calculation of static mechanical parameters -- 2.2.2. Dynamic mechanical parameters calculation -- 3. Advanced research/field applications -- 3.1. Brittleness evaluation index application -- 3.2. Field applications -- 4. Case study -- 4.1. Geological background -- 4.2. Samples and data processing -- 4.3. Reservoir characteristics -- 4.4. Geomechanical parameters -- 4.4.1. Static mechanical test results -- 4.4.2. Conversion of dynamic and static parameters. , 4.5. Brittleness analysis of shale -- 4.6. In-situ stress magnitude -- 5. Summary and conclusions -- Declarations -- Chapter Four. References -- References -- Chapter Five: Hydraulic fracturing of unconventional reservoirs aided by simulation technologies -- 1. Introduction -- 2. Mathematical models for hydraulic fracturing -- 2.1. Governing equations -- 2.1.1. Deformation of the rock matrix and the fractures -- 2.1.2. Fracture propagation -- 2.1.3. Fluid flow in fractures and pores -- 2.1.4. Thermal transport -- 2.2. Analytical and semi-analytical solutions for the propagation of a single hydraulic fracture -- 3. Numerical methods for simulation of hydraulic fracturing -- 4. Case study: Simulation of hydraulic fracture propagation in a shale formation -- 4.1. Model generation -- 4.2. Effects of 3D stress on induced fracture propagation -- 4.3. Effects of natural fracture orientations on induced fracture propagation -- 4.4. Effects of natural fracture state on induced fracture propagation -- 4.5. Effects of drilling direction on induced fracture propagation -- 5. Summary and conclusions -- Chapter Five. References -- References -- Chapter Six: Experimental methods in fracturing mechanics focused on minimizing their environmental footprint -- 1. Introduction -- 2. Experimental methods in fracturing mechanics -- 2.1. Micromechanical tests of rock -- 2.1.1. Grid nanoindentation tests -- 2.1.2. Atomic force microscope for micromechanical properties mapping -- SEM and EDS -- Atomic force microscopy (AFM) -- High resolution characterization of individual mineral aggregates -- 2.2. Triaxial tests for rocks with SC-CO2 -- 2.3. Triaxial direct shear test for rocks and shear induced permeability evolution -- 2.3.1. Experimental setup -- 2.3.2. Experimental scheme and procedure -- 2.4. Mechanical test of rock sample treated by liquid nitrogen. , 2.4.1. Macro-scale mechanical tests under LN2 freezing condition -- 2.4.2. Cryo-scanning electron microscopy test -- 3. Experimental methods for waterless fracturing -- 3.1. Triaxial fracturing system -- 3.1.1. True triaxial-loading and heating vessel -- 3.1.2. Pumping system for supercritical CO2 -- 3.1.3. Pumping system for liquid nitrogen -- 3.2. Triaxial fracturing for supercritical CO2 -- 3.2.1. Rock specimen preparation -- 3.2.2. Experimental procedures -- 3.2.3. Experimental results -- 3.3. Triaxial fracturing for liquid nitrogen -- 3.3.1. Experimental procedures -- 3.3.2. Fracturing experiment results -- 3.4. High-speed imaging of multiple fract propagation using homogenous transparent solids -- 3.4.1. Transparent material selection -- 3.4.2. Modified triaxial vessel and transparent solids for high-speed imaging -- 3.4.3. Scaling laws and parameter design -- 3.4.4. Experiment procedures -- 4. Fracture monitoring and analysis methods -- 4.1. Manual optical observation method -- 4.2. Acoustic emission monitoring method -- 4.3. 2D slice image analysis -- 4.4. 3D profilometry technique -- 4.5. 3D CT image reconstruction -- 4.6. CT images for characterization of fracture parameters -- 4.7. Other fracture evaluating approach -- Chapter Six. References -- References -- Chapter Seven: Production decline curve analysis and reserves forecasting for conventional and unconventional gas reservoirs -- 1. Introduction -- 2. Fundamental concepts and key principles -- 2.1. Historical decline curve fitting methods -- 2.2. Arps model -- 2.3. Rate-cumulative relationships to establish reserves and EUR -- 2.4. Constraints and assumption applied with Arps models -- 3. Advanced research/field applications -- 3.1. Segmented decline curves suited to unconventional reservoirs -- 3.2. Power law exponential decline (PLE) -- 3.3. Stretched exponential decline (SEPD). , 3.4. Duong's method -- 3.5. Logistic growth analysis (LGA) -- 3.6. Fetkovich type curve -- 3.7. Wattenbarger type curve -- 3.8. Blasingame type curve -- 3.9. Agarwal-Gardner type curve -- 3.10. Normalized pressure integral (NPI) -- 4. Case studies -- 4.1. Tip-top field conventional gas/vertical well case -- 4.2. Unconventional gas/horizontal well -- 5. Summary -- References -- Chapter Eight: Well test analysis for characterizing unconventional gas reservoirs -- 1. Introduction -- 2. Reservoir flow regimes -- 3. Pressure transient analysis (PTA) -- 3.1. Well test analysis for radial flow regime -- 3.2. Well test analysis for linear and elliptical flow regimes -- 3.3. Field example: Well test analysis for a multifractured shale gas reservoir -- 4. Rate transient analysis (RTA) -- 4.1. RTA field example: Multifractured shale gas reservoir -- 5. Uncertainties of SRV characterization using analytical methods -- 6. Characterizing SRV according to dual-permeability model -- 7. Effect of multiphase flow on PTA in unconventional Wells -- 8. A typical example in multiphase producing well test -- 9. Temperature transient analysis -- 10. Conclusions -- References -- Chapter Nine: Carbon-nanotube-polymer nanocomposites enable wellbore cements to better inhibit gas migration and enhance ... -- 1. Fundamental concepts -- 1.1. The key role of cement in achieving well integrity -- 1.2. Application of polymer additives in wellbore cement -- 1.3. Application of nanoparticles as wellbore cement additives -- 1.4. Wellbore cement reinforcement by CNT-polymer nanocomposite additive -- 2. Advanced consideration in controlling wellbore gas migration -- 2.1. Potential gas migration occurrences in wellbores -- 2.2. Major mechanisms in the emergence of gas migration in cement -- 2.2.1. Cement gelatinization in transient time. , 2.2.2. Effective removal of mud-cake from the wellbore wall before cementing.
    Additional Edition: ISBN 0-12-824495-X
    Language: English
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  • 7
    UID:
    b3kat_BV046879621
    Format: 843 Seiten , Illustrationen, Diagramme
    Edition: Fifteenth edition, global Edition
    ISBN: 9781292353364
    Content: This title is a Pearson Global Edition. The Editorial team at Pearson has worked closely with educators around the world to include content, which is especially relevant to students outside the United States. For one-semester undergraduate or graduate courses in accounting information systems
    Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-1-292-35328-9
    Language: English
    Subjects: Computer Science , Economics
    RVK:
    RVK:
    Keywords: Rechnungswesen ; Informationssystem
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  • 8
    UID:
    gbv_1841140864
    Format: 1 Online-Ressource (276 p.)
    ISBN: 9783031017643
    Series Statement: Synthesis Lectures on Computer Architecture
    Content: Many modern computer systems, including homogeneous and heterogeneous architectures, support shared memory in hardware. In a shared memory system, each of the processor cores may read and write to a single shared address space. For a shared memory machine, the memory consistency model defines the architecturally visible behavior of its memory system. Consistency definitions provide rules about loads and stores (or memory reads and writes) and how they act upon memory. As part of supporting a memory consistency model, many machines also provide cache coherence protocols that ensure that multiple cached copies of data are kept up-to-date. The goal of this primer is to provide readers with a basic understanding of consistency and coherence. This understanding includes both the issues that must be solved as well as a variety of solutions. We present both high-level concepts as well as specific, concrete examples from real-world systems. This second edition reflects a decade of advancements since the first edition and includes, among other more modest changes, two new chapters: one on consistency and coherence for non-CPU accelerators (with a focus on GPUs) and one that points to formal work and tools on consistency and coherence. This is an open access book. This is an open access book
    Note: English
    Language: Undetermined
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  • 9
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer
    UID:
    b3kat_BV045860698
    Format: 1 Online-Ressource (XII, 142 p)
    ISBN: 9783030130428
    Series Statement: Petroleum Engineering
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-13041-1
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-13043-5
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-13044-2
    Language: English
    Subjects: Engineering
    RVK:
    RVK:
    Keywords: Geologie ; Erdöllagerstätte
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 10
    UID:
    b3kat_BV037482750
    Format: XIII, 195 S. , graph. Darst.
    ISBN: 9781608455645
    Series Statement: Synthesis lectures on computer architecture 16
    Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-1-608-45565-2
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Speicher ; Konsistenz ; Pufferspeicher
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