{"product_id":"unconventional-hydrocarbon-resources-9781119389361","title":"Unconventional Hydrocarbon Resources","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eUnconventional Hydrocarbon Resources\u003c\/b\u003e \u003cp\u003e\u003cb\u003eEnables readers to save time and effort in exploring and exploiting shale gas and other unconventional fossil fuels by making use of advanced predictive tools\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eUnconventional Hydrocarbon Resources\u003c\/i\u003e highlights novel concepts and techniques for the geophysical exploration of shale and other tight hydrocarbon reservoirs, focusing on artificial intelligence approaches for modeling and predicting key reservoir properties such as pore pressure, water saturation, and wellbore stability. Numerous application examples and case studies present real-life data from different unconventional hydrocarbon fields such as the Barnett Shale (USA), the Williston Basin (USA), and the Berkine Basin (Algeria). \u003c\/p\u003e\u003cp\u003e\u003ci\u003eUnconventional Hydrocarbon Resources\u003c\/i\u003e explores a wide range of reservoir properties, including  modeling of the geomechanics of shale gas reservoirs, petrophysics analysis of shale and tight sand gas reservoirs, and prediction of hy\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Predrill Pore Pressure Estimation in Shale Gas Reservoirs Using Seismic Genetic Inversion with an Example from the Barnett Shale 1\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSid-Ali Ouadfeul, Mohamed Zinelabidine Doghmane, and Leila Aliouane\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 1\u003c\/p\u003e \u003cp\u003e1.2 Methods and Application to Barnett Shale 2\u003c\/p\u003e \u003cp\u003e1.2.1 Geological Setting 2\u003c\/p\u003e \u003cp\u003e1.2.2 Methods 3\u003c\/p\u003e \u003cp\u003e1.3 Data Processing 6\u003c\/p\u003e \u003cp\u003e1.4 Results Interpretation and Conclusions 7\u003c\/p\u003e \u003cp\u003eReferences 9\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 An Analysis of the Barnett Shale’s Seismic Anisotropy’s Role in the Exploration of Shale Gas Reservoirs (United States) 11\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSid-Ali Ouadfeul, Leila Aliouane, Mohamed Zinelabidine Doghmane, and Amar Boudella\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 11\u003c\/p\u003e \u003cp\u003e2.2 Seismic Anisotropy 12\u003c\/p\u003e \u003cp\u003e2.3 Application to Barnett Shale 14\u003c\/p\u003e \u003cp\u003e2.3.1 Geological Setting 14\u003c\/p\u003e \u003cp\u003e2.3.2 Data Analysis 15\u003c\/p\u003e \u003cp\u003e2.4 Conclusions 18\u003c\/p\u003e \u003cp\u003eReferences 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Wellbore Stability in Shale Gas Reservoirs with a Case Study from the Barnett Shale 21\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSid-Ali Ouadfeul, Mohamed Zinelabidine Doghmane, and Leila Aliouane\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 21\u003c\/p\u003e \u003cp\u003e3.2 Wellbore Stability 22\u003c\/p\u003e \u003cp\u003e3.2.1 Mechanical Stress 22\u003c\/p\u003e \u003cp\u003e3.2.2 Chemical Interactions with the Drilling Fluid 22\u003c\/p\u003e \u003cp\u003e3.2.3 Physical Interactions with the Drilling Fluid 22\u003c\/p\u003e \u003cp\u003e3.3 Pore Pressure Estimation Using the Eaton’s Model 23\u003c\/p\u003e \u003cp\u003e3.4 Shale Play Geomechanics and Wellbore Stability 24\u003c\/p\u003e \u003cp\u003e3.5 Application to Barnett Shale 26\u003c\/p\u003e \u003cp\u003e3.5.1 Geological Context 26\u003c\/p\u003e \u003cp\u003e3.5.2 Data Processing 28\u003c\/p\u003e \u003cp\u003e3.6 Conclusion 28\u003c\/p\u003e \u003cp\u003eReferences 30\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 A Comparison of the Levenberg-Marquardt and Conjugate Gradient Learning Methods for Total Organic Carbon Prediction in the Barnett Shale Gas Reservoir 31\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSid-Ali Ouadfeul, Mohamed Zinelabidine Doghmane, and Leila Aliouane\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 31\u003c\/p\u003e \u003cp\u003e4.2 Levenberg-Marquardt Learning Algorithm 32\u003c\/p\u003e \u003cp\u003e4.3 Application to Barnett Shale 33\u003c\/p\u003e \u003cp\u003e4.3.1 Geological Setting 33\u003c\/p\u003e \u003cp\u003e4.3.2 Data Processing 33\u003c\/p\u003e \u003cp\u003e4.3.3 Results Interpretation 36\u003c\/p\u003e \u003cp\u003e4.4 Conclusions 39\u003c\/p\u003e \u003cp\u003eReferences 40\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Identifying Sweet Spots in Shale Reservoirs 41\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSusan Smith Nash\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 41\u003c\/p\u003e \u003cp\u003e5.2 Materials and Methods 41\u003c\/p\u003e \u003cp\u003e5.3 Data for Two Distinct Types of Sweet Spot Identification Workflows 42\u003c\/p\u003e \u003cp\u003e5.3.1 Workflow 5.1: Early-Phase Workflow Elements: Total Petroleum System Approach 42\u003c\/p\u003e \u003cp\u003e5.3.2 Workflow 5.2: Smaller-Scale Field-Level Tools and Techniques 43\u003c\/p\u003e \u003cp\u003e5.4 Results: Two Integrative Workflows 45\u003c\/p\u003e \u003cp\u003e5.4.1 Early-Phase Exploration Workflow 45\u003c\/p\u003e \u003cp\u003e5.4.2 Later Phase Developmental, Including Refracing Workflow 45\u003c\/p\u003e \u003cp\u003e5.5 Case Studies 46\u003c\/p\u003e \u003cp\u003e5.5.1 Woodford Shale: Emphasis on Chemostratigraphy 46\u003c\/p\u003e \u003cp\u003e5.5.2 Barnett Shale: Emphasis on Seismic Attributes 46\u003c\/p\u003e \u003cp\u003e5.5.3 Eagle Ford Shale: Pattern Recognition\/Deep Learning 47\u003c\/p\u003e \u003cp\u003e5.6 Conclusion 47\u003c\/p\u003e \u003cp\u003eReferences 47\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Surfactants in Shale Reservoirs 49\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSusan Smith Nash\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 49\u003c\/p\u003e \u003cp\u003e6.2 Function of Surfactants 49\u003c\/p\u003e \u003cp\u003e6.2.1 Drilling 50\u003c\/p\u003e \u003cp\u003e6.2.2 Completion (Hydraulic Fracturing) 50\u003c\/p\u003e \u003cp\u003e6.3 Materials and Methods 50\u003c\/p\u003e \u003cp\u003e6.4 Characteristics of Shale Reservoirs 50\u003c\/p\u003e \u003cp\u003e6.4.1 High Clay Mineral Content 51\u003c\/p\u003e \u003cp\u003e6.4.2 Nano-Sized Pores 51\u003c\/p\u003e \u003cp\u003e6.4.3 Mixed-Wettability Behavior 51\u003c\/p\u003e \u003cp\u003e6.4.4 High Capillary Pressures 51\u003c\/p\u003e \u003cp\u003e6.5 The Klinkenberg Correction 51\u003c\/p\u003e \u003cp\u003e6.5.1 Klinkenberg Gas Slippage Measurement 52\u003c\/p\u003e \u003cp\u003e6.6 Completion Chemicals to Consider in Addition to the Surfactant 52\u003c\/p\u003e \u003cp\u003e6.6.1 Enhanced Oil Recovery (EOR) 52\u003c\/p\u003e \u003cp\u003e6.6.2 Liquids-Rich Shale Plays After Initial Decline 53\u003c\/p\u003e \u003cp\u003e6.7 Mono-Coating Proppant 53\u003c\/p\u003e \u003cp\u003e6.7.1 Zwitterionic Coating 53\u003c\/p\u003e \u003cp\u003e6.8 Dual-Coating Proppant 54\u003c\/p\u003e \u003cp\u003e6.8.1 Outside Coating 54\u003c\/p\u003e \u003cp\u003e6.8.2 Inner Coating 54\u003c\/p\u003e \u003cp\u003e6.9 Dual Coating with Porous Proppant 54\u003c\/p\u003e \u003cp\u003e6.9.1 Zwitterionic Outer Coating; Inorganic Salt Inner Coating, Porous Core 54\u003c\/p\u003e \u003cp\u003e6.10 Data 55\u003c\/p\u003e \u003cp\u003e6.10.1 Types of Surfactants 55\u003c\/p\u003e \u003cp\u003e6.10.1.1 Anionic 55\u003c\/p\u003e \u003cp\u003e6.10.1.2 Cationic 56\u003c\/p\u003e \u003cp\u003e6.10.1.3 Nonionic 56\u003c\/p\u003e \u003cp\u003e6.10.1.4 Zwitterionic 56\u003c\/p\u003e \u003cp\u003e6.11 Examples of Surfactants in Shale Plays 56\u003c\/p\u003e \u003cp\u003e6.11.1 Bakken (Wang and Xu 2012) 56\u003c\/p\u003e \u003cp\u003e6.11.2 Eagle Ford (He and Xu 2017) 57\u003c\/p\u003e \u003cp\u003e6.11.3 Utica (Shuler et al. 2016) 57\u003c\/p\u003e \u003cp\u003e6.12 Results 57\u003c\/p\u003e \u003cp\u003e6.13 Shale Reservoirs, Gas, and Adsorption 57\u003c\/p\u003e \u003cp\u003e6.14 Operational Conditions 58\u003c\/p\u003e \u003cp\u003e6.15 Conclusions 59\u003c\/p\u003e \u003cp\u003eReferences 59\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Neuro-Fuzzy Algorithm Classification of Ordovician Tight Reservoir Facies in Algeria 61\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMohamed Zinelabidine Doghmane, Sid-Ali Ouadfeul, and Leila Aliouane\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 61\u003c\/p\u003e \u003cp\u003e7.2 Neuro-Fuzzy Classification 61\u003c\/p\u003e \u003cp\u003e7.3 Results Discussion 63\u003c\/p\u003e \u003cp\u003e7.4 Conclusion 67\u003c\/p\u003e \u003cp\u003eReferences 67\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Recognition of Lithology Automatically Utilizing a New Artificial Neural Network Algorithm 69\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMohamed Zinelabidine Doghmane, Sid-Ali Ouadfeul, and Leila Aliouane\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 69\u003c\/p\u003e \u003cp\u003e8.2 Well-Logging Methods 70\u003c\/p\u003e \u003cp\u003e8.2.1 Nuclear Well Logging 70\u003c\/p\u003e \u003cp\u003e8.2.2 Neutron Well Logging 70\u003c\/p\u003e \u003cp\u003e8.2.3 Sonic Well Logging 70\u003c\/p\u003e \u003cp\u003e8.3 Use of ANN in the Oil Industry 71\u003c\/p\u003e \u003cp\u003e8.4 Lithofacies Recognition 71\u003c\/p\u003e \u003cp\u003e8.5 Log Interpretation 72\u003c\/p\u003e \u003cp\u003e8.5.1 Methodology of Manual Interpretation 72\u003c\/p\u003e \u003cp\u003e8.5.2 Results of Manual\/Automatic Interpretation 73\u003c\/p\u003e \u003cp\u003e8.6 Conclusion 78\u003c\/p\u003e \u003cp\u003eReferences 79\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Construction of a New Model (ANNSVM) Compensator for the Low Resistivity Phenomena Saturation Computation Based on Logging Curves 81\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMohamed Zinelabidine Doghmane, Sid-Ali Ouadfeul, and Leila Aliouane\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 81\u003c\/p\u003e \u003cp\u003e9.2 Field Geological Description 82\u003c\/p\u003e \u003cp\u003e9.2.1 Conventional Interpretation 82\u003c\/p\u003e \u003cp\u003e9.2.2 Reservoir Mineralogy 84\u003c\/p\u003e \u003cp\u003e9.3 Low-Resistivity Phenomenon 84\u003c\/p\u003e \u003cp\u003e9.3.1 Cross Plots Interpretation 84\u003c\/p\u003e \u003cp\u003e9.3.2 NMR Logs Interpretation 85\u003c\/p\u003e \u003cp\u003e9.3.3 Comparison Between Well-1 and Well- 2 85\u003c\/p\u003e \u003cp\u003e9.3.4 Developed Logging Tools 85\u003c\/p\u003e \u003cp\u003e9.3.5 Proposed ANNSVM Algorithm 85\u003c\/p\u003e \u003cp\u003e9.4 Conclusions 91\u003c\/p\u003e \u003cp\u003eReferences 91\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 A Practical Workflow for Improving the Correlation of Sub-Seismic Geological Structures and Natural Fractures using Seismic Attributes 93\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMohamed Zinelabidine Doghmane, Sid-Ali Ouadfeul, and Leila Aliouane\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 93\u003c\/p\u003e \u003cp\u003e10.2 Description of the Developed Workflow 94\u003c\/p\u003e \u003cp\u003e10.3 Discussion 94\u003c\/p\u003e \u003cp\u003e10.4 Conclusions 95\u003c\/p\u003e \u003cp\u003eReferences 96\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Calculation of Petrophysical Parameter Curves for Nonconventional Reservoir Modeling and Characterization 99\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMohamed Zinelabidine Doghmane, Sid-Ali Ouadfeul, and Leila Aliouane\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 99\u003c\/p\u003e \u003cp\u003e11.2 Proposed Methods 99\u003c\/p\u003e \u003cp\u003e11.3 Results and Discussion 101\u003c\/p\u003e \u003cp\u003e11.4 Conclusions 101\u003c\/p\u003e \u003cp\u003eReferences 102\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Fuzzy Logic for Predicting Pore Pressure in Shale Gas Reservoirs With a Barnett Shale Application 105\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eLeila Aliouane, Sid-Ali Ouadfeul, Mohamed Zinelabidine Doghmane, and Amar Boudella\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 105\u003c\/p\u003e \u003cp\u003e12.2 The Fuzzy Logic 106\u003c\/p\u003e \u003cp\u003e12.3 Application to Barnett Shale 106\u003c\/p\u003e \u003cp\u003e12.3.1 Geological Context 106\u003c\/p\u003e \u003cp\u003e12.3.2 Data Processing 107\u003c\/p\u003e \u003cp\u003e12.4 Results Interpretation and Conclusions 110\u003c\/p\u003e \u003cp\u003eReferences 111\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Using Well-Log Data, a Hidden Weight Optimization Method Neural Network Can Classify the Lithofacies of a Shale Gas Reservoir: Barnett Shale Application 113\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eLeila Aliouane, Sid-Ali Ouadfeul, Mohamed Z. Doghmane, and Ammar Boudella\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 113\u003c\/p\u003e \u003cp\u003e13.2 Artificial Neural Network 114\u003c\/p\u003e \u003cp\u003e13.3 Hidden Weight Optimization Algorithm Neural 114\u003c\/p\u003e \u003cp\u003e13.4 Geological Context of the Barnett Shale 115\u003c\/p\u003e \u003cp\u003e13.5 Results Interpretation and Conclusions 117\u003c\/p\u003e \u003cp\u003eBibliography 124\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 The Use of Pore Effective Compressibility for Quantitative Evaluation of Low Resistive Pays 127\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMohamed Zinelabidine Doghmane, Sid-Ali Ouadfeul, and Leila Aliouane\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 127\u003c\/p\u003e \u003cp\u003e14.2 Low-Resistivity Pays in the Studied Basin 127\u003c\/p\u003e \u003cp\u003e14.3 Water Saturation from Effective Pore Compressibility 128\u003c\/p\u003e \u003cp\u003e14.4 Discussion 128\u003c\/p\u003e \u003cp\u003e14.5 Conclusions 130\u003c\/p\u003e \u003cp\u003eBibliography 130\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 The Influence of Pore Levels on Reservoir Quality Based on Rock Typing: A Case Study of Quartzite El Hamra, Algeria 133\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eNettari Ferhat, Mohamed Z. Doghmane, Sid-Ali Ouadfeul, and Leila Aliouane\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 133\u003c\/p\u003e \u003cp\u003e15.2 Quick Scan Method 133\u003c\/p\u003e \u003cp\u003e15.3 Results 135\u003c\/p\u003e \u003cp\u003e15.4 Discussion 135\u003c\/p\u003e \u003cp\u003e15.5 Conclusions 137\u003c\/p\u003e \u003cp\u003eBibliography 137\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 An Example from the Algerian Sahara Illustrates the Use of the Hydraulic Flow Unit Technique to Discriminate Fluid Flow Routes in Confined Sand Reservoirs 139\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAbdellah Sokhal, Sid-Ali Ouadfeul, Mohamed Zinelabidine Doghmane, and Leila Aliouane\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 139\u003c\/p\u003e \u003cp\u003e16.2 Regional Geologic Setting 140\u003c\/p\u003e \u003cp\u003e16.3 Statement of the Problem 142\u003c\/p\u003e \u003cp\u003e16.3.1 Concept of HFU 142\u003c\/p\u003e \u003cp\u003e16.3.2 HFU Zonation Process 142\u003c\/p\u003e \u003cp\u003e16.4 Results and Discussion 143\u003c\/p\u003e \u003cp\u003e16.4.1 FZI Method 143\u003c\/p\u003e \u003cp\u003e16.4.2 FZI Method 144\u003c\/p\u003e \u003cp\u003e16.5 Conclusions 146\u003c\/p\u003e \u003cp\u003eReferences 146\u003c\/p\u003e \u003cp\u003e0005546230.indd 9 07-18-2023 21:09:25\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Integration of Rock Types and Hydraulic Flow Units for Reservoir Characterization. Application to Three Forks Formation, Williston Basin, North Dakota, USA 147\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAldjia Boualam and Sofiane Djezzar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 147\u003c\/p\u003e \u003cp\u003e17.2 Petrophysical Rock-Type Prediction 148\u003c\/p\u003e \u003cp\u003e17.3\u003c\/p\u003e \u003cp\u003eRock Types’ Classification Based on R 35 Pore Throat Radius 150\u003c\/p\u003e \u003cp\u003e17.3.1 Upper Three Forks 153\u003c\/p\u003e \u003cp\u003e17.3.2 Middle Three Forks 155\u003c\/p\u003e \u003cp\u003e17.3.3 Lower Three Forks 157\u003c\/p\u003e \u003cp\u003e17.4 Determination of Hydraulic Flow Units 157\u003c\/p\u003e \u003cp\u003e17.4.1 Upper Three Forks 159\u003c\/p\u003e \u003cp\u003e17.4.2 Middle Three Forks 160\u003c\/p\u003e \u003cp\u003e17.4.3 Lower Three Forks 160\u003c\/p\u003e \u003cp\u003e17.5 Conclusion 160\u003c\/p\u003e \u003cp\u003eReferences 162\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Stress-Dependent Permeability and Porosity and Hysteresis. Application to the Three Forks Formation, Williston Basin, North Dakota, USA 163\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAldjia Boualam and Sofiane Djezzar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 163\u003c\/p\u003e \u003cp\u003e18.2 Database 165\u003c\/p\u003e \u003cp\u003e18.3 Testing Procedure 166\u003c\/p\u003e \u003cp\u003e18.3.1 Core Samples Cleaning and Drying 167\u003c\/p\u003e \u003cp\u003e18.3.2 Permeability and Porosity Measurements 169\u003c\/p\u003e \u003cp\u003e18.3.3 Mineral Composition Analysis 170\u003c\/p\u003e \u003cp\u003e18.3.4 Scanning Electron Microscope 171\u003c\/p\u003e \u003cp\u003e18.4 Results and Discussions 174\u003c\/p\u003e \u003cp\u003e18.4.1 Stress-Dependent Permeability and Hysteresis 175\u003c\/p\u003e \u003cp\u003e18.4.1.1 Upper Three Forks 175\u003c\/p\u003e \u003cp\u003e18.4.1.2 Middle Three Forks 181\u003c\/p\u003e \u003cp\u003e18.4.2 Permeability Evolution with Net Stress 183\u003c\/p\u003e \u003cp\u003e18.4.3 Stress-Dependent Porosity and Hysteresis 186\u003c\/p\u003e \u003cp\u003e18.4.3.1 Upper Three Forks 186\u003c\/p\u003e \u003cp\u003e18.4.3.2 Middle Three Forks 192\u003c\/p\u003e \u003cp\u003e18.4.4 Porosity Evolution with Net Stress 194\u003c\/p\u003e \u003cp\u003e18.4.5 Permeability Evolution with Porosity 195\u003c\/p\u003e \u003cp\u003e18.5 Conclusion 196\u003c\/p\u003e \u003cp\u003eReferences 198\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Petrophysical Analysis of Three Forks Formation in Williston Basin, North Dakota, USA 207\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAldjia Boualam and Sofiane Djezzar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19.1 Introduction 207\u003c\/p\u003e \u003cp\u003e19.2 Petrophysical Database 208\u003c\/p\u003e \u003cp\u003e19.2.1 Curve Editing and Environmental Correction 209\u003c\/p\u003e \u003cp\u003e19.2.2 Preanalysis Processing 211\u003c\/p\u003e \u003cp\u003e19.3 Methods and Background 211\u003c\/p\u003e \u003cp\u003e19.3.1 Wireline Logs 211\u003c\/p\u003e \u003cp\u003e19.3.1.1 Caliper Tool 211\u003c\/p\u003e \u003cp\u003e19.3.1.2 Total and Spectral Gamma-Ray Logs 212\u003c\/p\u003e \u003cp\u003e19.3.1.3 Electrical Properties (Resistivity) 212\u003c\/p\u003e \u003cp\u003e19.3.1.4 Neutron Logs 213\u003c\/p\u003e \u003cp\u003e19.3.1.5 Bulk Density Log 213\u003c\/p\u003e \u003cp\u003e19.3.1.6 Acoustic Logs 213\u003c\/p\u003e \u003cp\u003e19.3.1.7 Elemental Capture Spectroscopy 214\u003c\/p\u003e \u003cp\u003e19.3.1.8 Nuclear Magnetic Resonance 215\u003c\/p\u003e \u003cp\u003e19.3.1.9 Multifrequency Array Dielectric Measurements 215\u003c\/p\u003e \u003cp\u003e19.3.2 Petrophysical Analysis Challenges 216\u003c\/p\u003e \u003cp\u003e19.3.2.1 Formation Components and Volumes 217\u003c\/p\u003e \u003cp\u003e19.3.2.2 Water Saturation Model 221\u003c\/p\u003e \u003cp\u003e19.3.2.3 Nuclear Magnetic Resonance 224\u003c\/p\u003e \u003cp\u003e19.4 Petrophysical Analysis Results and Discussion 224\u003c\/p\u003e \u003cp\u003e19.4.1 Upper Three Forks 231\u003c\/p\u003e \u003cp\u003e19.4.2 Middle Three Forks 236\u003c\/p\u003e \u003cp\u003e19.4.3 Lower Three Forks 237\u003c\/p\u003e \u003cp\u003e19.5 Conclusion 240\u003c\/p\u003e \u003cp\u003eReferences 241\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 Water Saturation Prediction Using Machine Learning and Deep Learning. Application to Three Forks Formation in Williston Basin, North Dakota, USA 251\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAldjia Boualam and Sofiane Djezzar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20.1 Introduction 251\u003c\/p\u003e \u003cp\u003e20.2 Experimental Procedure and Methodology 253\u003c\/p\u003e \u003cp\u003e20.2.1 Support Vector Machine Concepts 253\u003c\/p\u003e \u003cp\u003e20.2.2 Preprocessing of the Dataset 255\u003c\/p\u003e \u003cp\u003e20.2.3 Building SVR Model 258\u003c\/p\u003e \u003cp\u003e20.2.4 Building Random Forest Regression Model 261\u003c\/p\u003e \u003cp\u003e20.2.5 Building Deep Learning Model 262\u003c\/p\u003e \u003cp\u003e20.2.6 Curve Reconstruction Using K.Mod 264\u003c\/p\u003e \u003cp\u003e20.3 Results and Discussion 264\u003c\/p\u003e \u003cp\u003e20.4 Conclusion 275\u003c\/p\u003e \u003cp\u003eReferences 276\u003c\/p\u003e \u003cp\u003eAppendix Hysteresis Testing and Mineralogy 285\u003c\/p\u003e \u003cp\u003eIndex 297\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49407044354391,"sku":"9781119389361","price":142.16,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119389361.jpg?v=1730497985","url":"https:\/\/bookcurl.com\/products\/unconventional-hydrocarbon-resources-9781119389361","provider":"Book Curl","version":"1.0","type":"link"}