Kooperativer Bibliotheksverbund

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Umfang: xiii, 538 pages : , illustrations ; , 24 cm

ISBN: 9780323902311

Anmerkung: Includes index. , Front Cover -- Methods for Petroleum Well Optimization -- Methods for Petroleum Well Optimization: Automation and Data Solutions -- Copyright -- Contents -- Preface -- Acknowledgment I -- Acknowledgment II -- One - Introduction to digital twin, automation and real-time centers -- 1.1 Digital twin technology -- 1.1.1 Digital twins -- 1.1.1.1 Data-related technologies -- 1.1.1.2 High-fidelity modeling technologies -- 1.1.1.3 Model-based simulation technologies -- 1.1.2 Five-dimension digital twin model -- 1.1.2.1 Physical entities in digital twin -- 1.1.2.2 Virtual models in digital twin -- 1.1.2.3 Digital twin data -- 1.1.2.4 Services in digital twin -- 1.1.2.5 Connections in digital twin -- 1.1.3 Value of digital twin -- 1.1.4 Modeling basis used in digital twin development -- 1.1.5 Monitoring of the drilling wells using digital twin -- 1.1.6 The concept of digital twinning for well construction -- 1.2 Drilling automation -- 1.2.1 Automation levels -- 1.2.2 Modeling -- 1.2.3 Data communication -- 1.2.4 Modes of automation -- 1.2.4.1 Envelope protection automation -- 1.2.4.2 Closed-loop automation -- 1.2.4.3 Multilevel control structure -- 1.3 Real-time centers -- 1.3.1 Collaborative well planning -- 1.3.2 Well engineering and planning -- 1.3.3 Real-time data aggregation and visualization -- 1.3.4 Real-time monitoring and interventions -- 1.3.5 Predictive modeling -- 1.3.6 Drilling optimization and detailed technical analysis -- 1.3.7 Training and mentoring -- 1.3.8 Data management and archiving -- 1.4 Summary -- 1.5 Problems -- Problem 1: Drilling systems automation -- Problem 2: Real-time centers (drilling operation centers or onshore collaboration centers) -- Problem 3: Digital drilling ecosystem -- Problem 4: Drillbotics competition -- Problem 5: Microservices -- References -- Further reading -- Open-source code. , Two - Petroleum well optimization -- 2.1 Mathematical optimization -- 2.1.1 Fundamentals of optimization -- 2.1.2 Geometric programming -- 2.1.3 Multiobjective optimization -- 2.1.4 Stochastic optimization -- 2.1.5 Robust optimization -- 2.2 Petroleum well optimization -- 2.2.1 Drilling problem formulation -- 2.2.1.1 Rate of penetration optimization -- 2.2.1.1.1 Rate of penetration objective function -- 2.2.1.1.2 Rate of penetration constraints -- 2.2.1.2 Minimum mechanical specific energy -- 2.2.1.3 Bottomhole assembly configuration -- 2.2.1.4 Path optimization framework -- 2.2.1.4.1 Well path optimization problem formulation -- 2.2.1.5 Wellbore profile energy -- 2.2.1.5.1 Wellbore trajectory -- 2.2.1.5.2 Wellbore trajectory constraints -- 2.2.1.6 Hole cleaning optimization -- 2.2.1.6.1 Hole cleaning objective function -- 2.2.1.6.2 Hole cleaning variables and constraints -- 2.2.2 Production problem formulation -- 2.2.2.1 The quality map approach -- 2.2.2.1.1 The quality concept -- 2.2.2.2 Well placement problem -- 2.2.2.2.1 Sequential well placement problem -- 2.2.2.2.2 Multiplacement approach -- 2.2.2.3 Closed-loop reservoir management -- 2.2.3 Well control optimization -- 2.3 Summary -- 2.4 Problems -- Problem 1: Deterministic and stochastic mathematical formulation -- Problem 2: ROP model with GP format -- Problem 3: Multiobjective mathematical formulation -- Problem 4: Well placement optimization -- Problem 5: Shortcomings of well placement -- Problem 6: Nonlinear optimization -- Problem 7: Nonlinear optimization -- Problem 8: Well placement and number of wells optimization -- Problem 9: ROP Optimization by SA -- Problem 10: ROP model for reamers by GA -- Nomenclature -- References -- Further reading -- Open-source code -- Three - Wellbore friction optimization -- 3.1 Elementary models for wellbore friction. , 3.1.1 Friction in straight wellbore sections -- 3.1.1.1 Torque -- 3.1.2 Friction in curved wellbore sections -- 3.1.3 Two-dimensional friction modeling -- 3.1.4 Three-dimensional friction modeling -- 3.1.5 Combined axial motion and rotation -- 3.2 Advanced models for wellbore friction -- 3.2.1 The Johancsik model -- 3.3 Application of friction models to wells -- 3.3.1 Radius of curvature well path model -- 3.3.1.1 Positions for straight well sections -- 3.3.2 The dogleg severity -- 3.3.3 The catenary well path -- 3.4 Design of oil wells using analytical friction models -- 3.4.1 Well with build-and-hold profile -- 3.4.2 Constructing a modified catenary well profile -- 3.4.3 Comparing trajectories for a long-reach well -- 3.4.4 Ultralong-reach well design -- 3.4.5 2D well path optimization -- 3.5 Summary -- 3.6 Problems -- Problem 1: Weight in air, weight in suspension, and hook load calculation -- Problem 2: Compute the torque and tension along the string -- Problem 3: Compute the tension, hook load and torque -- Nomenclature -- References -- Further reading -- Open-source code -- Four - Wellbore trajectory optimization -- 4.1 Introduction -- 4.2 Constraints potentially affecting the optimal well trajectory -- 4.2.1 Geomechanical constraints -- 4.2.2 Anticollision constraints -- 4.2.3 Offset well constraints -- 4.2.4 Well control constraints -- 4.3 Well path optimization -- 4.3.1 Three-dimensional well path design by single-objective optimization -- 4.3.2 Three-dimensional well path design by two-objective optimization -- 4.4 Well trajectory optimization for preventing wellbore instability -- 4.4.1 Constraint range of the inclination and azimuth angle -- 4.4.1.1 The Mohr-Coulomb criterion -- 4.4.1.2 The Mogi-Coulomb failure criterion -- 4.4.2 Algorithm to achieve the optimum well trajectory -- 4.4.3 Well trajectory optimization -- 4.5 Summary. , 4.6 Problems -- Problem 1: New mathematical modeling -- Problem 2: Probabilistic constraints -- Problem 3: Uncertainty anti-collision analysis of cylindrically shaped wells (volumetric safety factor) -- Nomenclature -- References -- Open-source code -- Examples include: -- Five - Wellbore hydraulics and hole cleaning: optimization and digitalization -- 5.1 Hydraulic optimization -- 5.1.1 Introduction -- 5.1.2 The hydraulic system -- 5.1.2.1 Pressure losses -- 5.1.2.2 Classical optimization criteria -- 5.1.2.3 Example of shortcomings of the classical approach -- 5.1.3 Hydraulic optimization -- 5.1.3.1 A new method for hydraulic optimization -- 5.1.4 Optimum nozzle and flow rate selection -- 5.1.5 Proposed optimization criteria for various well types -- 5.2 Hole cleaning -- 5.2.1 Effect of parameters on hole cleaning -- 5.2.2 Cuttings transport mechanisms -- 5.2.3 Hole cleaning model -- 5.2.4 Cuttings transport and settling -- 5.3 Real-time assessment of the hole cleaning efficiency -- 5.3.1 Hole cleaning strategy -- 5.3.1.1 Angles of 0-35 degrees -- 5.3.1.2 Angles of 35-60 degrees -- 5.3.1.3 Angles of 60-90 degrees -- 5.3.2 Real-time modeling -- 5.3.3 Carrying capacity index -- 5.3.3.1 Carrying capacity index curve generation -- 5.3.3.2 Integration of the model -- 5.4 New methods for drilling hydraulics -- 5.4.1 Reelwell drilling method -- 5.4.1.1 Principal description of system -- 5.4.1.2 The single pump system and the multiple pump system -- 5.4.1.3 Frictional pressure loss calculation method -- 5.4.1.4 Example pressure distribution single-pump system -- 5.4.1.5 The multiple pump system pressure distribution -- 5.4.2 Hole cleaning and wellbore risk reduction service -- 5.5 Summary -- 5.6 Problems -- Problem 1: Nozzle size design -- Problem 2: Pressure distribution in the multiple-pump system -- Problem 3: Hydraulics and hole cleaning digitalization. , Problem 4: Reelwell drilling method (RDM) -- Nomenclature -- Examples include: -- References -- Further reading -- Open-source code -- Six - Mechanical specific energy and drilling efficiency -- 6.1 Introduction to mechanical specific energy -- 6.1.1 Drilling efficiency -- 6.1.2 Causes of inefficiency -- 6.1.2.1 Bit balling -- 6.1.2.2 Bottomhole balling -- 6.1.2.3 Vibrations -- 6.1.3 Regions of drilling efficiency -- 6.1.4 Analyzing trends in mechanical specific energy -- 6.2 Mechanical specific energy: next-generation digital drilling optimization -- 6.2.1 Maximizing drill rates with real-time surveillance of mechanical specific energy -- 6.2.1.1 Friction losses in the drill string -- 6.2.1.2 Bit balling -- 6.2.1.3 Bottomhole balling -- 6.2.1.3.1 Vibrations -- 6.2.1.4 Bit dulling -- 6.2.2 Hydromechanical specific energy -- 6.2.3 Hydromechanical specific energy for lithology prediction -- 6.2.3.1 Field example -- 6.2.4 Hydromechanical specific energy for pore pressure prediction -- 6.2.4.1 Methodology of pore pressure prediction -- 6.2.4.2 Field example of pore pressure prediction -- 6.3 Rock drillability assessments -- 6.3.1 Drillability d-exponent -- 6.3.2 Formation drillability prediction -- 6.4 Drilling system energy beyond mechanical specific energy -- 6.4.1 Assessing the energy loss -- 6.4.2 Energy flow in the drill string -- 6.4.3 Theory of drilling energy -- 6.5 Summary -- 6.6 Problems -- Problem 1: MSE simulation and drilling efficiency -- Problem 2: MSE optimization and drilling efficiency -- Problem 3: Operating parameters optimization -- Nomenclature -- References -- Open-source code -- Seven - Data-driven machine learning solutions to real-time ROP prediction -- 7.1 Introduction -- 7.1.1 Types of machine learning -- 7.2 Data piping in real time -- 7.3 Drilling rate of penetration optimization workflow -- 7.3.1 Sensor. , 7.3.2 Machine learning model.

Sprache: Englisch