Skip to main content

Turning Rocks into Knowledge

  • Chapter
  • First Online:
Simula Research Laboratory
  • 813 Accesses

Abstract

Since early 2005, Simula Research Laboratory and StatoilHydro have built a strong and long-term research collaboration in computational geosciences. The main goal for this collaboration is to strengthen the procedures used in oil and gas exploration through new and improved computer-based models of geological and geophysical processes. So far, the 4D Lithosphere Model and a new generation of the Compound Modelling technology have been successfully established, and the collaboration has become strategically important for both organisations. More contributions to the field are progressing rapidly and potentially will lead to improved reliability of depositional models, better insight into the physics of underwater gravity flows of sediments, and more accurate descriptions of deformations in sedimentary basins.

This chapter describes the background for the research collaboration as well as ongoing scientific activities. Using the results obtained from academic and industrial pursuits as a backdrop, we also summarise the key factors responsible for the successful implementation of a close link between the basic research community and industry. The coupling of research tasks of an academic nature with technology development has proven to be bidirectional, in that development-oriented activities lead to new PhD and postdoctoral research projects and vice versa. The intimate connection between the axes of research and development is a particular strength in the StatoilHydro-Simula collaboration. This feature is a consequence of both companies being committed to long-term research and the flexibility offered by Simula’s organisation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. M. A. Tatang, W. Pan, R. G. Prinn, and G. J. McRae. An efficient method for parametric uncertainty analysis of numerical geophysical models. J. Geophysical Research, 102:21925–21932, 1997.

    Article  Google Scholar 

  2. P. M. C. Leod, S. Carey, and R. S. J. Sparks. Behaviour of particle-laden flows into the ocean: Experimental simulation and geological implications. Sedimentation, 46:523–536, 1999.

    Google Scholar 

  3. H. Li and D. Zhang. Probabilistic collocation method for flow in porous media: Comparisons with other stochastic methods. Water Resources Research, 43:523–536, 2007.

    Google Scholar 

  4. A. K. Thurmond, J. Skogseid, C. Heine, T. V. Stensby, C. Tarrou, and A. M. Bruaset. Development of the 4D lithosphere model (4DLM): How exploration research has contributed to 4-dimensional visualization and interpretation of geological and geophysical data. Eos Trans., 89:53, 2008.

    Article  Google Scholar 

  5. R. Walker. The origin and significance of the internal sedimentary structures of turbidites. Proceedings of the Yorkshire Geological Society, 35:1–32, 1965.

    Article  Google Scholar 

  6. J. Shirolkar, C. Coimbra, and M. Queroz McQuay. Fundemental aspects of modeling turbulent particle dispersion in dilute flows. Progress In Energy Combustion Science, 22:363–399, 1996.

    Article  Google Scholar 

  7. H. Li, H. Fang, Z. Lin, S. Xu, and S. Chen. Lattice Boltzmann simulation on particle suspensions in a two-dimensional symmetric stenotic artery. Physical Review E, 69(3):031919–+, Mar. 2004.

    Article  Google Scholar 

  8. Z. Fan, F. Qiu, A. Kaufman, and S. Yoakum-Stover. GPU cluster for high performance computing. SuperComputing Conference, 2004.

    Google Scholar 

  9. A. Masselot and B. Chopard. A Lattice Boltzmann model for particle transport and deposition. Europhys. Lett, 42:264, 1998.

    Article  Google Scholar 

  10. S. Huang, S. Mahadevan, and R. Rebba. Collocation-based stochastic finite element analysis for random field problems. Probabilistic Engineering Mechanics, 22:194–205, 2007.

    Article  Google Scholar 

  11. Ø. Hjelle and M. Dæhlen. Multilevel least squares approximation of scattered data over binary triangulations. Computing and Visualization in Science, 8(2):83–91, 2005.

    Article  MathSciNet  Google Scholar 

  12. J. P. M. Syvitski and E. W. H. Hutton. 2D SEDFLUX 1.0C: an advanced process-response numerical model for the fill of marine sedimentary basins. Computers & Geosciences, 27(6):731–753, 2001.

    Article  Google Scholar 

  13. K. Borovkov. Elements of Stochastic Modelling. World Scientific Publishing, 2003.

    Google Scholar 

  14. B. J. T. Morgan. Applied Stochastic Modelling. Chapmann & Hall, 2nd edition, 2008.

    Google Scholar 

  15. B. D. Ripley. Stochastic Simulation. Wiley Series in Probability and Statistics. Wiley, 2006.

    Google Scholar 

  16. W. Gautschi. Algorithm 726: ORTHPOL–a package of routines for generating orthogonal polynomials and Gauss-type quadrature rules. ACM Trans. Math. Softw., 20(1):21–62, 1994.

    Article  MATH  Google Scholar 

  17. R. Ghanem and P. D. Spanos. Polynomial chaos in stochastic finite elements. Journal of Applied Mechanics, 57(1):197–202, 1990.

    Article  MATH  Google Scholar 

  18. L. Rainald. Applied Computational Fluid Dynamics Techniques: An Introduction Based on Finite Element Methods. Wiley, 2008.

    Google Scholar 

  19. G. Hämmerlin and K.-H. Hoffmann. Numerical Mathematics. Springer, 1991.

    Google Scholar 

  20. T. Løseth. Submarine Massflow Sedimentation. Number 82 in Lecture Notes in Earth Sciences. Springer, 1999.

    Google Scholar 

  21. P. Keary and F. J. Vine. Global tectonics. Blackwell Publishing, 2nd edition, 1996.

    Google Scholar 

  22. P. A. Allen and J. R. Allen. Basin Analysis: Principles and Applications. Blackwell Publishing, 2nd edition, 2005.

    Google Scholar 

  23. L. M. Hwa, M. A. Duchaineau, and K. I. Joy. Adaptive 4-8 texture hierarchies. Visualization Conference, IEEE, 0:219–226, 2004.

    Google Scholar 

  24. L. M. Hwa, M. A. Duchaineau, and K. I. Joy. Real-time optimal adaptation for planetary geometry and texture: 4-8 tile hierarchies. IEEE Transactions on Visualization and Computer Graphics, pages 355–368, 2005.

    Google Scholar 

  25. K. Sahr, D. White, and A. J. Kimerling. Geodesic discrete global grid systems. Cartography and Geographic Information Science, 30(2):121–134, 2003.

    Article  Google Scholar 

  26. J. Rivenæs. Application of a dual–lithology, depth–dependent diffusion equation in stratigraphic simulation. Basin Research, 4:133–146, 1992.

    Article  Google Scholar 

  27. J. Rivenæs. A Computer Simulation Model for Siliciclastic Basin Stratigraphy. PhD thesis, NTH, 1993.

    Google Scholar 

  28. B. Doligez, D. Granjeon, P. Joseph, R. Eschard, and H. Beucher. How can stratigraphic modeling help to constrain geoststistical reservoir simulations? Numerical Experiments in Stratigraphy: Recent Advances in Stratigraphic and Sedimentologic Computer Simulations, volume 62 of SEPM Society for Sedimentary Geology Special Publications, pages 239–244. Geological Society Publishing House, 1999.

    Google Scholar 

  29. D. M. Tetzlaff and J. W. Harbaugh. Simulating Clastic Sedimentation. Van Nostrand Reinhold, 1989.

    Google Scholar 

  30. L. Landweber. An iteration formula for Fredholm integral equations of the first kind. Amer. J. Math., 73:615–624, 1951.

    Article  MATH  MathSciNet  Google Scholar 

  31. H.-J. Schroll. Automatic calibration of depositional models. Automated Solution of Differential Equations. Springer, 2009. Submitted by invitation.

    Google Scholar 

  32. A. R. Conn, K. Scheinberg, and L. N. Vicente. Introduction to Derivative-Free Optimization. MPS-SIAM Book Series on Optimization. SIAM, 2009.

    Google Scholar 

  33. D. Zhang. Stochastic Methods for Flow in Porous Media. Coping with Uncertainties. Academic Press, 2002.

    Google Scholar 

  34. K. Bitzer and R. Salas. SIMSAFADIM: 3D simulation of stratigraphic architecture and facies distribution modeling of carbonate sediments. Computers & Geosciences, 28:1177–1192, 2002.

    Article  Google Scholar 

  35. J. Strobel, R. Cannon, C. Kendall, G. Biswas, and J. Bezdek. Interactive (SEDPAK) simulation of clastic and carbonate sediments in shelf to basin settings. Computers and Geoscience, 15:1279–1290, 1989.

    Article  Google Scholar 

  36. J.-L. Mallet. Space-time mathematical framework for sedimentary geology. Mathematical Geology, 36(1), 2004.

    Google Scholar 

  37. S. A. Petersen. Compound Modelling - a geological approach to the construction of shared earth models. EAGE 61th Conference & Exhibition, Extended Abstracts, 1999.

    Google Scholar 

  38. S. A. Petersen. Optimization strategy for shared earth modeling. EAGE 66th Conference & Exhibition, Extended Abstracts, 2004.

    Google Scholar 

  39. S. A. Petersen, Ø. Hjelle, and S. L. Jensen. Earth modelling using distance fields derived by Fast Marching. EAGE 69th Conference & exhibition, Extended Abstracts, 2007.

    Google Scholar 

  40. S. A. Petersen and Ø. Hjelle. Earth recursion, an important component in sheared earth model builders. EAGE 70th Conference & exhibition, Extended Abstracts, 2008.

    Google Scholar 

  41. M. G. Imhof and A. K. Sharma. Seismostratigraphic inversion: Appraisal, ambiguity, and uncertainty. Geophysics, 72(4):Rr51–R66, 2007.

    Article  Google Scholar 

  42. J. B. Haga, A. M. Bruaset, X. Cai, H. P. Langtangen, H. Osnes, and J. Skogseid. Parallelisation and numerical performance of a 3D model for coupled deformation, fluid flow and heat transfer in sedimentary basins. MekIT’07, pages 151–162. Tapir Academic Press, 2007.

    Google Scholar 

  43. O. Al-Khayat, A. M. Bruaset, and H. P. Langtangen. Lattice Boltzmann method and turbidity flow modeling. MekIT’07, pages 213–228. Tapir Academic Press, 2007.

    Google Scholar 

  44. M. W. Gee, C. M. Siefert, J. J. Hu, R. S. Tuminaro, and M. G. Sala. ML 5.0 Smoothed Aggregation User’s Guide. Technical Report SAND2006-2649, Sandia National Laboratories, 2006.

    Google Scholar 

  45. T. V. Stensby, C. Tarrou, A. M. Bruaset, J. Skogseid, A. K. Thurmond, and C. Heine. Multi-resolution visualization of time-dependent horizons on the globe. Presentation at the 33rd International Geological Congress, Oslo, 2008.

    Google Scholar 

  46. Ø. Hjelle and S. Petersen. Mathematics of folding in structural geology. Working notes, 2009.

    Google Scholar 

  47. StatoilHydro and Simula. Interactive rendering of physical entities. UK Patent Application No. 0814474.3, filed August 6, 2008, 2008.

    Google Scholar 

  48. O. Al-Khayat, A. M. Bruaset, and H. P. Langtangen. A lumped particle model for the simulation of suspended flows. Journal paper in writing, 2009.

    Google Scholar 

  49. J. B. Haga, H. Osnes, and H. P. Langtangen. Parallelisation and numerical performance of a large-scale porothermoelastic basin model. Journal paper in writing, 2009.

    Google Scholar 

  50. S. Clark, A. M. Bruaset, T. Sømme, and T. Løseth. Probabilistic handling of uncertainty in diffusion-based stratigraphic models. Journal paper in writing, 2009.

    Google Scholar 

  51. T. Salles, S. Lopez, R. Eschard, O. Lerat, T. Mulder, and M. C. Cacas. Turbidity current modelling on geological time scales. Marine Geology, 248:127–150, 2008.

    Article  Google Scholar 

  52. A. Kjeldstad, H. P. Langtangen, J. Skogseid, and K. Bjørlykke. Simulation of sedimentary basins. Advanced Topics in Computational Partial Differential Equations, pages 611–658. Springer, 2003.

    Google Scholar 

  53. H. P. Langtangen. Computational Partial Differential Equations: Numerical Methods and Diffpack Programming. Springer, 2nd edition, 2003.

    Google Scholar 

  54. M. J. D. Powell. UOBYQA: unconstrained optimization by quadratic approximation. Math. Program., Ser. B, 92:555–582, 2002.

    Article  MATH  Google Scholar 

  55. DK Images. http://www.dkimages.com/.

  56. Jerome Neufeld. Photo from a tank experiment showing a turbidity current.The experimental nonlinear physics group, University of Toronto, Canada. See http://www.physics.utoronto.ca/ nonlin/turbidity/turbidity.html.

  57. Kevin Walsh. Photo of a stack of turbidites in Cornwall, UK. See http://www. everystockphoto.com/photo.php?imageId=8672.

  58. A. B. Watts. Isostasy and Flexure of the Lithosphere. Cambridge University Press, 2001.

    Google Scholar 

  59. J.-L. Mallet. Numerical Earth Models. EAGE, 2008.

    Google Scholar 

  60. J.-L. Mallet. Geomodeling. Oxford University Press, 2002.

    Google Scholar 

  61. U. M. Yang. Parallel algebraic multigrid methods — High performance preconditioners. Numerical Solution of Partial Differential Equations on Parallel Computers, pages 209–236. Springer, 2006.

    Google Scholar 

  62. M. Rumpf and R. Strzodka. Graphics processor units: New prospects for parallel computing. Numerical Solution of Partial Differential Equations on Parallel Computers, pages 89–132. Springer, 2006.

    Google Scholar 

  63. G. Karypis, K. Schloegel, and V. Kumar. Parmetis parallel graph partitioning and sparse matrix ordering library, version 3.1. Technical report, University of Minnesota, 2003.

    Google Scholar 

  64. W. Joubert and J. Cullum. Scalable algebraic multigrid on 3500 processors. Electronic Transactions on Numerical Analysis, 23:105–226, 2006.

    MATH  MathSciNet  Google Scholar 

  65. H. A. van der Vorst. Bi-CGSTAB: A fast and smoothly converging variant of Bi-CG for the solution of nonsymmetric linear systems. SIAM J. Sci. Stat. Comput., 13:631–644, 1992.

    Article  MATH  Google Scholar 

  66. R. A. Olea. Geostatistics for Engineers and Earth Scientists. Kluwer Academic Publishers, 1999.

    Google Scholar 

  67. M. Perrin, B. Zhu, J.-F. Rainaud, and S. Schneider. Knowledge-driven applications for geological modeling. Journal of Petroleum Science and Engineering, 47(1):89–104, 2005.

    Article  Google Scholar 

  68. J. A. Sethian. Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science. Cambridge University Press, 1999.

    Google Scholar 

  69. J. G. Ramsay and M. I. Hubert. The Techniques of Modern Structural Geology: Folds and Fractures. Academic Press, 1987.

    Google Scholar 

  70. C. M. R. Fowler. The Solid Earth: An Introduction to Global Geophysics. Cambridge University Press, 2nd edition, 2004.

    Google Scholar 

  71. E. Rouy and A. Tourin. A viscosity solutions approach to shape-from-shading. SIAM J. Num. Anal, 29(3):867–884, 1992.

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Bruaset, A.M. (2010). Turning Rocks into Knowledge. In: Tveito, A., Bruaset, A., Lysne, O. (eds) Simula Research Laboratory. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01156-6_40

Download citation

Publish with us

Policies and ethics