LEADER 04994nam 22006495 450 001 9910874668803321 005 20240716093741.0 010 $a9783031527159 024 7 $a10.1007/978-3-031-52715-9 035 $a(CKB)32970842600041 035 $a(MiAaPQ)EBC31529364 035 $a(Au-PeEL)EBL31529364 035 $a(DE-He213)978-3-031-52715-9 035 $a(EXLCZ)9932970842600041 100 $a20240715d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligent Approaches in Petroleum Geosciences /$fedited by Constantin Cranganu 205 $a2nd ed. 2024. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2024. 215 $a1 online resource (288 pages) 311 08$a9783031527142 327 $aPreface to the 2nd edition -- Preface to the 1st Edition -- 1. Applications of Data-Driven Techniques in Reservoir Modeling and Management -- Part 1: Waterflooding -- Part 2: Water Alternating Gas Injection, CO2 Storage, and Property Estimations -- 2. Comparison of three machine learning approaches in determining Total Organic Carbon (TOC): A case study from Marcellus shale formation, New York state -- 3. Gated Recurrent Units for Lithofacies Classification based on Seismic Inversion -- 4. Application of Artificial Neural Networks in Geoscience and Petroleum Industry -- 5. On Support Vector Regression to Predict Poisson?s Ratio and Young?s Modulus of Reservoir Rock -- 6. Use of Active Learning Method to Determine the Presence and Estimate the Magnitude of Abnormally Pressured Fluid Zones: A Case Study from the Anadarko Basin, Oklahoma -- 7. Active Learning Method for Estimating Missing Logs in Hydrocarbon Reservoirs -- 8. Improving the Accuracy of Active Learning Method via Noise Injection for Estimating Hydraulic Flow Units: An Example from a Heterogeneous Carbonate Reservoir -- 9. Well Log Analysis by Global Optimization-based Interval Inversion Method -- 10. Permeability Estimation in Petroleum Reservoir by Meta-heuristics: An Overview -- Index. 330 $aThis book presents cutting-edge approaches to solving practical problems faced by professionals in the petroleum industry and geosciences. With various state-of-the-art working examples from experienced academics, the book offers an exposure to the latest developments in intelligent methods for oil and gas research, exploration, and production. This second edition is updated with new chapters on machine learning approaches, data-driven modelling techniques, and neural networks. The book delves into machine learning approaches, including evolutionary algorithms, swarm intelligence, fuzzy logic, deep artificial neural networks, KNN, decision tree, random forest, XGBoost, and LightGBM. it also analyzes the strengths and weaknesses of each method and emphasizes essential parameters like robustness, accuracy, speed of convergence, computer time, overlearning, and normalization. Integration, data handling, risk management, and uncertainty management are all crucial issues in petroleum geosciences. The complexities of these problems require a multidisciplinary approach that fuses petroleum engineering, geology, geophysics, and geochemistry. Essentially, this book presents an approach for integrating various disciplines such as data fusion, risk reduction, and uncertainty management. Whether you are a professional or a student, you can greatly benefit from the latest advancements in intelligent methods applied to oil and gas research. This comprehensive and updated book presents cutting-edge approaches and real-world examples that can help you in solving the intricate challenges of the petroleum industry and geosciences. 606 $aCogeneration of electric power and heat 606 $aFossil fuels 606 $aArtificial intelligence 606 $aGeotechnical engineering 606 $aMathematical models 606 $aMineralogy 606 $aFossil Fuel 606 $aArtificial Intelligence 606 $aGeotechnical Engineering and Applied Earth Sciences 606 $aMathematical Modeling and Industrial Mathematics 606 $aMineralogy 615 0$aCogeneration of electric power and heat. 615 0$aFossil fuels. 615 0$aArtificial intelligence. 615 0$aGeotechnical engineering. 615 0$aMathematical models. 615 0$aMineralogy. 615 14$aFossil Fuel. 615 24$aArtificial Intelligence. 615 24$aGeotechnical Engineering and Applied Earth Sciences. 615 24$aMathematical Modeling and Industrial Mathematics. 615 24$aMineralogy. 676 $a665.5028563 700 $aCranganu$b Constantin$01749426 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910874668803321 996 $aArtificial Intelligent Approaches in Petroleum Geosciences$94183667 997 $aUNINA LEADER 06142nam 22004811 450 001 9910956372103321 005 20251019235712.0 010 $a9789004447851 010 $a9004447857 024 7 $a10.1163/9789004447851 035 $a(CKB)5490000000008751 035 $a(MiAaPQ)EBC6631742 035 $a(Au-PeEL)EBL6631742 035 $a(OCoLC)1233219011 035 $a(nllekb)BRILL9789004447851 035 $a(EXLCZ)995490000000008751 100 $a20201130d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMorphology and Bionomics of Dorylaims (Nematoda, Dorylaimida) /$fReyes Pen?a Santiago 210 1$aLeiden; $aBoston :$cBRILL, $d2021. 215 $a1 online resource (298 pages) 225 1 $aNematology Monographs and Perspectives ;$v13 311 08$a9789004439993 311 08$a9004439994 320 $aIncludes bibliographical references and index. 327 $aPreface -- Acknowledgements -- 1. Concept -- Morphological characterisation: distinctive features -- Biology -- Distribution -- Diversity -- 2. General aspect -- Size -- Shape -- Habitus -- Colour -- 3. Body wall and pseudocoel -- Cuticle -- Structure (layers) -- Surface ornamentation -- Specialisations -- Body pores -- Epidermis and lateral chords -- Somatic musculature -- Pseudocoel and its components -- 4. Lip region and amphids -- Lip region shape -- Profile (contour) -- Anterior margin -- Tapering -- Differentiation (separation from the adjoining body) -- Lips and their papillae -- General pattern -- Lips -- Papillae -- Oral aperture (mouth) -- Oral field -- Amphids -- Basic structure -- Position -- Aperture -- Fovea -- 5. Stoma and feeding apparatus -- Cheilostom -- Detailed structure -- General morphology -- Guiding ring -- Guiding sheath -- Mural tooth -- Axial odontostyle -- Odontophore -- Musculature associated with stoma -- 6. Digestive tract -- Pharynx -- General morphology -- Sections -- Ultrastructure -- Anterior section -- Enlargement -- Basal expansion and pharyngeal glands -- Basic patterns -- Pharyngo-intestinal junction -- Intestine proper -- Prerectum -- Rectum -- 7. Female genital system -- General concept and terminology -- Ovary -- Oviduct -- Sphincter -- Uterus -- Basic types -- Uterine special differentiations -- Vagina -- Vulva -- Malformations. 327 $a8. Male genital system -- General concept -- Testes -- Genital tract -- Spicules -- Lateral guiding pieces -- Gubernaculum -- Genital papillae (supplements) and other papillae -- Specialised musculature -- Glands associated with male genital system -- 9. Nervous system and receptors -- Central nervous system -- Nerves -- Cephalic nervous system -- Pharyngeal nervous system -- Recto-sympathetic nervous system -- Sensory structures -- Chemoreceptors -- Amphids -- Other chemoreceptive elements -- Mechanoreceptors -- Labial and cephalic papillae -- Other mechanoreceptive elements -- 10. Caudal region -- General concept -- Tail shape -- Tail sexual dimorphism -- Postembryonic changes in tail shape -- Functional and evolutionary aspects of tail shape -- 11. Feeding habits and feeding behaviour -- Methodological constraints -- Feeding spectrum -- Feeding behaviour -- Food suitability and selection -- Feeding functional morphology -- Excretion and osmo-regulation in dorylaims -- 12. Reproduction and development -- Bisexual vs monosexual species -- Gatemetogenesis and egg production -- Embryonic development and hatching -- Postnatal development - general aspects -- Moulting process -- Genital system development -- Other (minor) postnatal changes -- Life cycle and life span -- 13. Ecology and Biogeography -- Rationale - dorylaims as K-strategists -- Dorylaims as components of nematode communities -- Local distribution -- Vertical (depth) distribution -- Temporal (seasonal) distribution -- Regional distribution -- Global distribution -- . The distribution of particular taxa - some examples -- Historic biogeography -- Phylogeography -- Dispersal and transport -- Chorological relationships -- Biotic interactions -- Dorylaims as bioindicators in a global change scenario -- Notes on survival -- 14. Diversity -- Historical outline -- The origins (1845-1920) -- The prodigious 1930s decade -- The order Dorylaimida setting -- The golden age of the exploration of dorylaimid diversity (1960-1990) -- A new era for an integrative approach -- The internal phylogeny of Dorylaimida -- Evolutionary relationships of Dorylaimida with other nematode taxa -- Dorylaims - members of the subclass Dorylaimia -- Mononchs - the closest relatives of dorylaims? -- Dorylaims and other animal-parasitic Dorylaimia -- Dorylaimida and other non-Dorylaimia -- Updated inventory of dorylaimid taxa -- Subject Index -- Cited Taxa Index. 330 $aDorylaims are probably the most diverse order of nematodes and are often an abundant component of the fauna in soils and freshwater habitats. As a result of their widespread distribution and many different feeding habits, they are considered as good bio-indicators of environmental quality and soil health. Their usefulness in this regard is only impeded by practical difficulties related to the accurate identification of the members of such a large and complex group. In this volume, Professor Reyes Pen?a-Santiago gives a detailed morphology of the dorylaims and provides a thorough overview of their feeding behaviour, reproduction, ecology, and diversity. You will learn what dorylaims are like and how they live, making this book an invaluable tool for nematologists, ecologists and other scientists who wish to embark on an in-depth study of the members of this fascinating group. 410 0$aNematology Monographs and Perspectives ;$v13. 606 $aMorphology 615 0$aMorphology. 676 $a571.31 700 $aSantiago$b Reyes Pen?a$01786220 801 0$bNL-LeKB 801 1$bNL-LeKB 906 $aBOOK 912 $a9910956372103321 996 $aMorphology and Bionomics of Dorylaims (Nematoda, Dorylaimida)$94317619 997 $aUNINA