Error handling strategies in multiphase inverse modeling

Computers and Geosciences

Volumn 37, Issue 6, 2011, Pages 724-730

  Finsterle, Stefan ^a   Zhang, Yingqi ^a  

^a LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

Author keywords

Inverse modeling; ITOUGH2; Multiphase flow; Residual analysis; Robust estimation

Indexed keywords

CALIBRATED MODEL; CONVERGENCE PROBLEMS; ERROR HANDLING; ERROR STRUCTURES; FLOW AND TRANSPORT; INVERSE MODELING; ITOUGH2; LEAST SQUARES METHODS; PARAMETER ESTIMATE; PREDICTIVE CAPABILITIES; RESIDUAL ANALYSIS; ROBUST ESTIMATION; UNCERTAINTY MEASURES;

ESTIMATION; INVERSE PROBLEMS; LEAST SQUARES APPROXIMATIONS; MAXIMUM LIKELIHOOD ESTIMATION; MULTIPHASE FLOW; RANDOM ERRORS; SYSTEMATIC ERRORS; UNCERTAINTY ANALYSIS;

PARAMETER ESTIMATION;

CALIBRATION; ERROR ANALYSIS; FLOW MODELING; GEOSTATISTICS; INVERSE ANALYSIS; LEAST SQUARES METHOD; MAXIMUM LIKELIHOOD ANALYSIS; MULTIPHASE FLOW; NUMERICAL MODEL; PARAMETERIZATION;

EID: 79953103536     PISSN: 00983004     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cageo.2010.11.009     Document Type: Article

References (17)

1. Andrews D.F., Bickel P.J., Hampel F.R., Huber P.J., Rogers W.H., Tukey J.W. Robust Estimates of Location: Survey and Advances 1972, Princeton University Press, Princeton, NJ, 374 pp.
2. Box G., Cox D. An analysis of transformations. Journal of the Royal Statistical Society, Series B 1964, 26(2):211-252.
3. Carrera J., Neuman S.P. Estimation of aquifer parameters under transient and steady state conditions: 1. Maximum likelihood method incorporating prior information. Water Resources Research 1986, 22:199-210.
4. Cooley R.L. A method of estimating parameters and\assessing reliability for models of steady state groundwater flow: 2. Application of statistical analysis. Water Resources Research 1979, 15(3):603-617.
5. Doherty J., Welter D. A short exploration of structural noise. Water Resources Research 2010, 46:W05525. 10.1029/2009WR008377.
6. Finsterle S. Multiphase inverse modeling: review and iTOUGH2 applications. Vadose Zone Journal 2004, 3:747-762.
7. Finsterle S., Kowalsky M.B. Joint hydrological-geophysical inversion for soil structure identification. Vadose Zone Journal 2008, 7:287-293. 10.2136/vzj2006.0078.
8. Finsterle, S., Kowalsky, M.B. A truncated Levenberg-Marquardt algorithm for the calibration of highly parameterized nonlinear models. Computers and Geosciences this issue, doi:. http://10.1016/j.cageo.2010.11.005.
9. Finsterle S., Persoff P. Determining permeability of tight rock samples using inverse modeling. Water Resources Research 1997, 33(8):1803-1811.
10. Finsterle S., Najita J. Robust estimation of hydrogeologic model parameters. Water Resources Research 1998, 34(11):2939-2947.
11. iTOUGH2, 2010. Lawrence Berkeley National Laboratory, Berkeley, CA, 〈〉 (Accessed October 1, 2010). http://esd.lbl.gov/iTOUGH2.
12. Kaipio J., Somersalo E. Statistical and Computational Inverse Problems. Applied Mathematical Sciences 2004, vol. 160. Springer-Verlag, Berlin, Germany, 344 pp.
13. Lehikoinen A., Huttunen J.M.J., Finsterle S., Kowalsky M.B., Kaipio J.P. Dynamic inversion for hydrological process monitoring under model uncertainty. Water Resources Research 2010, W04513. 10.1029/2009WR008470.
14. Moore C., Doherty J. The cost of uniqueness in groundwater model calibration. Advances in Water Resources 2006, 29(4):605-623.
15. Oreskes N., Shrader-Frechette K., Belitz K. Verification, validation, and confirmation of numerical models in the earth sciences. Science 1994, 264:641-646.
16. Vrugt J., Boutem W. Validity of first-order approximations to describe parameter uncertainty in soil hydraulic models. Soil Science Society of America Journal 2002, 66:1740-1751.
17. Weisberg S. Applied Linear Regression 1980, John Wiley & Sons, New York, NY, 283 pp.