Exploring Uncertainty: 2014 Reservoir Research Highlights

1. Annual Meeting 2014 Stanford Center for Reservoir Forecasting SCRF 27th Annual Meeting May 8-9 2014

2. SCRF 27th Annual Meeting • SCRF Overview • 2014 Research Highlights

3. SCRF Overview SCRF Mission Leading research in quantitative reservoir modeling with a focus on data integration and assessing uncertainty

4. SCRF: Overview • Quantitative modeling of geological heterogeneity • Modeling uncertainty • Building 3D/4D models accounting for scale and accuracy of geological, geophysical and reservoir engineering data

5. SCRF: Students, Staff, and Faculty Graduate students (~17) Post-docs Pejman Tahmasebi, Ankur Roy Research Staff Celine Scheidt Staff Thuy Nguyen, Eiko Rutherford Faculty Jef Caers Tapan Mukerji Alexandre Boucher Work closely with other research groups in the School of Earth Sciences

6. SCRF: Stanford Collaborations • SRB • Rock Physics • SUPRI/Smart Fields • Flow simulation • SEP • Seismic Imaging • SPODDS • Deep Water Systems • BPSM • Basin Modeling

7. SCRF: Research topics • Modeling uncertainty • Modeling integrated uncertainty in metric space • Distance-Kernel Method • Quantifying geological scenario uncertainty • Multiple-point geostatistics • Stochastic simulation of (geo)patterns • Design of fast and robust geostatistical algorithms • Application to actual reservoirs, carbonate and clastic • Hybridization with surface and object-based methods

8. SCRF: Research topics • Seismic reservoir characterization • Statistical Rock physics • Interpretation of facies from seismic data • Dealing with sub-seismic scale • Integrating different types of geophysical data • Seismic constraints for Basin Modeling • Time-lapse seismic and history matching • Geologically consistent HM • Workflows for integrating 4D seismic • Streamline-based HM • Value of Information • Decision driven modeling of uncertainty

9. SCRF: Affiliate Members Long-term research goals are made possible through continuous funding of most major oil, service and software companies ~20 affiliate members

10. SCRF: Membership Benefits • Graduates • Facilitated access to research • Reports • Theses • Software • Annual Meeting • Visits • Research collaborations

11. SCRF 27th Annual Meeting 2014 Research and Results: Highlights

12. 1. Modeling Uncertainty

13. 1. Modeling Uncertainty • Distance Kernel Methods • Geological scenario uncertainty • Generalized Sensitivity Analysis

14. 1. Modeling Uncertainty Multidimensional Scaling (MDS) Caers et al., 2009 Map a set of N earth models using a pair wise distance between them.

15. 1. Modeling Uncertainty Celine Scheidt Uncertainty in depositional scenarios

16. 1. Modeling Uncertainty Celine Scheidt Uncertainty in depositional scenarios + Uncertainty in trends

17. 1. Modeling Uncertainty Geological Scenario Uncertainty: Field case study Field seismic data Cheolkyun Jeong, Celine Scheidt Pattern distance? Multiple geological scenarios Offshore W. Africa Use pattern distance to update multiple scenarios

18. 1. Modeling Uncertainty Distance Based Modeling of Uncertainty Distance between shapes and patterns

19. 1. Modeling Uncertainty Distance based modeling of uncertain geologic scenarios MDS space O Scenario 1 OScenario 2 P( geologic scenario | data) Updating geologic scenario * data 19

20. 1. Modeling Uncertainty Well Logs Cheolkyun Jeong, Celine Scheidt Core information Core Well logs Seismic data Data Integration

21. 1. Modeling Uncertainty Yongduk Shin Post-deformational Syn-depositional Deformation and restoration of reservoir properties Deformation Scenario Uncertainty deformation style accommodation style deformation-diagenesis interaction

22. 1. Modeling Uncertainty Orhun Aydin Structural Uncertainty Surfaces to regions Efficient workflow without re-gridding

23. 1. Modeling Uncertainty Lewis Li, Paul Sava SEG SEAM model Seismic Imaging Uncertainty velocity model uncertainty interpretation uncertainty

24. 1. Modeling Uncertainty Distance based sensitivity analysis - applications - reservoir modeling - basin and petroleum system modeling - seismic interpretation - 4-D seismic

25. 1. Modeling Uncertainty Yao Tong Sensitivity Analysis in Basin Modeling HI TOC Thickness Thermal history Source rock hydrocarbon generation Piceance Basin Model

26. 2. Fractured Reservoir

27. 2. Fractured Reservoir Benchmark synthetic dataset Shin, Aydin, Roy, Li Platform to test workflows, development strategies and uncertainty modeling in fractured reservoir

28. 2. Fractured Reservoir Shin, Aydin, Roy, Li Geology Faults Depositional facies Rock properties Flow Elastic

29. 2. Fractured Reservoir Shin, Aydin, Roy, Li Geomechanics Stress/Strain Fracture intensity Seismic attributes Anisotropic elasticity P and S-wave

30. 2. Fractured Reservoir Flow simulation Development strategies Modeling uncertainty Orhun Aydin

31. 3. Data Mining and Statistical Learning 31

32. 3.Data Mining and Learning What can we learn from data? Source: google.earth.com Utah Shale gas production wells 32

33. 3.Data Mining and Learning Functional Data Analysis (FDA) Data as a function of underlying process. FDA: Flexible functional fitting Robust extrapolation Ogy Grujic Basis functions rate time time 33

34. 3.Data Mining and Learning Functional Data Analysis (FDA) Applications: Forecasting for shale gas Direct forecasting using functional basis Model selection by functional PCA (Eigenfunctions) Ogy Grujic Addy Satija 34

35. 4. Hybrid Geomodeling

36. 4. Hybrid Geomodeling • Surface based models • Generalized cellular automata • Rule-based geologic models

37. 4. Hybrid Geomodeling Two points Multiple points Geological realism Object based Surface based Process based Conditioning capabilities Bertoncello et al.

38. Integration of geomorphic experiment data in surface-based modeling Siyao Xu, PhD Thesis 4. Hybrid Geomodeling Prof. Chris Paola St. Anthony Falls Lab (UMN) 38

39. 4. Hybrid Geomodeling Modeling sub-seismic lobes using spatial statistics Yinan Wang

40. 5. Algorithms and Software

41. 5.Algorithms and Software Multiple Point Pattern Simulation Algorithms Image Quilting and Conditioning Pejman Tahmasebi

42. 5.Algorithms and Software MS-CCSIM Pejman Tahmasebi Multi-scale cross-correlation simulation Multi-scale search in Fourier space accelerates simulations

43. 5.Algorithms and Software Jaehoon Lee Probabilistic Particle Swarm Optimization (Pro-PSO) PSO Probabilistic Prior

44. 5.Algorithms and Software Lewis Li SGEMS-MATLAB Plugin MATLAB How can we Integrate Existing MATLAB Code Into SGEMS? SGEMS Alex Boucher C++ library for algorithm design in Multiple point simulation

45. 2014 Research Highlights • Modeling Uncertainty • Geological Scenario uncertainty and updating, Field case study • Structural Uncertainty, Seismic Imaging Uncertainty • Geomechanical and Diagenetic scenarios • Fractured Reservoir Modeling • Benchmark dataset • Data Mining and Statistical Learning • Forecasting with Functional Data Analysis (FDA) • Hybrid geomodeling • Tank experiment analysis • Modeling lobe complexes • Algorithms and Software • Pattern simulation, MC-CCSIM, Pro-PSO • SGeMS and Matlab, C++ library

46. Research Report Online annual report with papers Ph.D. Theses Presentations http://scrf.stanford.edu

47. Guest Speaker Professor Paul Sava Colorado School of Mines

48. Annual Meeting 2014 Stanford Center for Reservoir Forecasting SCRF 27th Annual Meeting May 8-9 2014

49. One other thing….. Krumbein Medal – IAMG’s highest award • Distinction in application of mathematics • and informatics in the earth sciences • Service to IAMG • Support to earth sciences professions