Artificial Intelligent Approaches in Petroleum Geosciences

Artificial Intelligent Approaches in Petroleum Geosciences

Cranganu, Constantin

Springer International Publishing AG





15 a 20 dias

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Preface 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.
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Artificial Intelligent Methods;Machine Learning Modeling;Big Data, Data Mining, and Data Analysis;Well Logging;Petroleum Geosciences