Reservoir Characterization. Группа авторов

19.1 Introduction 19.2 Simulation Framework 19.3 Coupling of Mathematical Models 19.4 Verification Cases 19.5 Results 19.6 Discussions 19.7 Conclusions and Future Work References

      31  20 3D Seismic-Assisted CO₂-EOR Flow Simulation for the Tensleep Formation at Teapot Dome, USA 20.1 Presentation Sequence 20.2 Introduction 20.3 Geological Background 20.4 Discrete Fracture Network (DFN) 20.5 Petrophysical Modeling 20.6 PVT Analysis 20.7 Streamline Analysis 20.8 CO₂-EOR 20.9 Conclusions Acknowledgement References

      32  Part 7: New Advances in Reservoir Characterization-Machine Learning Applications

      33  21 Application of Machine Learning in Reservoir Characterization 21.1 Brief Introduction to Reservoir Characterization 21.2 Artificial Intelligence and Machine (Deep) Learning Review 21.3 Artificial Intelligence and Machine (Deep) Learning Applications to Reservoir Characterization 21.4 Machine (Deep) Learning and Enhanced Oil Recovery (EOR) 21.5 Conclusion Acknowledgement References

      34  Index

      35  End User License Agreement

      List of Illustrations

      1 Chapter 1Figure 1.1 Different components of reservoir characterization, from Fornel and E...Figure 1.2 Wide range of physical scale for different data types associated with...Figure 1.3 SURE Challenge: Having to deal with the wide ranges of Scale, Uncerta...Figure 1.4 Areal coverage of well data is complemented by the larger areal sampl...Figure 1.5 Vertical and spatial resolution of various geophysical, well logs and...Figure 1.6 Time-lapse seismic response changes caused by different positions of ...Figure 1.7 Use of conventional seismic, well log data and MEQ data to create a 3...Figure 1.8 The entire process of reservoir model updating through 4D seismic mod...Figure 1.9 Reservoir modeling process workflow. The process takes control of the...Figure 1.10 Integrated reservoir modeling, fluid simulation update and reiterati...

      2 Chapter 2Figure 2.1 Common methods for estimating the shear wave velocity.Figure 2.2 The placement of the test device is shown in schemati.Figure 2.3 Schematic, placement of sample with transducer and the top cap.Figure 2.4 (a) The core flooding system, (b) Image of the holder connected to th...Figure 2.5 Compressional and shear wave velocity vs different effective pressure...Figure 2.6 P-wave velocity (experimental and estimated) at different effective p...Figure 2.7 S-wave velocity (experimental and estimated) at different effective p...Figure 2.8 Cross plot of estimated P-wave velocities vs. laboratory measurements...Figure 2.9 Cross plot of the estimated S-wave velocities vs. laboratory measurem...Figure 2.10 Plot of experimental shear wave velocity against compressional wave ...Figure 2.11 Plot of estimated shear wave velocity against compressional wave vel...Figure 2.12 Rate of variability of experimental/estimated velocities with increa...Figure 2.13 Plot of Laboratory vs. estimated Bulk modulus (K) of rock sample.Figure 2.14 Plot of laboratory vs. estimated shear modulus.Figure 2.15 Plot of laboratory vs. estimated Young’s modulus.

      3 Chapter 3Figure 3.1 Divergence values for records in training and test set. The horizonta...Figure 3.2 Expected versus posterior false discovery rate for two sizes of the t...Figure 3.3 Histograms of area under posterior ROC Curve (AUC) for three anomaly ...Figure 3.4 AUC histograms and quantile regions calculated from 1000 pairs of tra...Figure 3.5 Median of posterior AUC for three AD classifiers as a function of the...Figure 3.6 Quantile width of AUC distribution calculated on anomaly detection re...Figure 3.7 Sparsity