Estimating oil spill characteristics from oil heads in scattered monitoring wells
Article
Received:
Revised:
- 45 Downloads
- 3 Citations
Abstract
The results are presented of a comparison of four different methods of interpolating observed hydrocarbon depths in monitoring wells, as well as a comparison of different methods of selecting sampling points for interpolation. The results provide criteria for selecting one interpolation method over another, under different scenarios. The methods analyzed are: (1) inverse-distance weighting; (2) punctual kriging; (3) minimum surface curvature; and (4) Akima's quintic polynomial.
Keywords
Hydrocarbon Environmental Management Sampling Point Kriging Minimum Surface
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Preview
Unable to display preview. Download preview PDF.
References
- Akima, H.: 1986, ‘A Method of Bivariate Interpolation and Smooth Surface Fitting for Irregularly Distributed Data Points’, ACM Trans. on Math. Software 4, 148–159.Google Scholar
- Braile, L.W.: 1978, ‘Comparison of Four Random to Grid Methods’, Computers and Geosciences 4, 341–349.Google Scholar
- Briggs, I.C.: 1974, ‘Machine Contouring Using Minimum Curvature’, Geophysics 39, 39–48.Google Scholar
- Campbell, J.B.: 1987, Introduction to Remote Sensing, Guilford Press, New York.Google Scholar
- Cooke, R.A. and Mostaghimi, S.: 1992, ‘A Microcomputer Based Routine for Obtaining Mean Watershed Precipitation from Point Values’, Computers and Geosciences 7, 823–837.Google Scholar
- Cooke, R.A., Mostaghimi, S., and Heatwole, C.D.: 1991, ‘Statistical/Geostatistical Analysis of Field Data’, ASAE paper 912576, ASAE, St. Joseph, Michigan.Google Scholar
- Davis, J.C.: 1986, Statistics and Data Analysis in Geology (2nd ed.): John Wiley % Sons, New York.Google Scholar
- Golden Software, Inc.: 1988, Surfer, Golden Software, Inc., Golden, Colorado.Google Scholar
- Gutjahr, A.: 1988, ‘Problem Definition, Variability, Geostatistics and Sampling in Ground Water Contamination’, Proceedings of a National Workshop on Ground Water Quality, Arlington, Virginia.Google Scholar
- Hollander, M. and Wolfe, D.A.: 1973, Nonparametric Statistical Methods, John Wiley & Sons, New York.Google Scholar
- IMSL: 1987, International Mathematical and Statistical Libraries, IMSL, Houston, Texas.Google Scholar
- Jury, W.A.: 1986, ‘Spatial Variability of Soil Properties’, In: Hern, S.C. and S.M. Melancon (Eds.), Vadose Zone Modelling of Organic Pollutants, Lewis Publishers Inc., Chelsea, Michigan, pp. 245–269.Google Scholar
- Kelway, P.S.: 1974, ‘A Scheme for Assessing the Reliability of Interpolated Rainfall Estimates’, J. Hydrology 21, 247–269.Google Scholar
- Kaluarachchi, J.J., Parker, J.C., and Lenhard, R.J.: 1990, ‘A Numerical Model for Areal Migration of Water and Light Hydrocarbon in Unconfined Aquifers’, Adv. Water Resour. 13, 29–40.Google Scholar
- Lam, N.S.: 1983, ‘Spatial Interpolation Methods: Review’, American Cartographer 10, 129–149.Google Scholar
- Lawson, C.L.: 1972, ‘Generation of a Triangular Grid with Application to Contour Plotting’, Tech. Memo. 299, Sect. 914, Jet Propulsion Lab., Caltech, Pasadena, California.Google Scholar
- Loague, K. and Gander, G.A.: 1990, ‘R-5 Revisited. 1. Spatial Variability of Infiltration on a Small Rangeland Catchment’, Water Resources Research 26, 957–971.Google Scholar
- McBratney, A.B. and Webster, R.: 1986, ‘Choosing Functions for Semi-Variograms of Soil Properties and Fitting Them to Estimates’, J. Soil Science 37, 617–639.Google Scholar
- Marcus, D.L.: 1992, ‘A Week of Anguish in Mexico’, Dallas Morning News, April 26.Google Scholar
- Montefusco, L.B. and Casciola, G.: 1989, ‘C1 Surface Interpolation’, ACM Transactions on Mathematical Software 15, 365–374.Google Scholar
- N.O.A.A.: 1972, ‘National Weather Service River Forecast System Forecast Procedures’, TM NWS HYDRO-14, US Department of Commerce, Washington DC.Google Scholar
- Philip, G.M. and Watson, D.F.: 1986, ‘Matheronian Geostatistics — Quo Vadis?’, Math. Geol. 18, 93–117.Google Scholar
- Preusser, A.: 1990, ‘C1- and C2-Interpolation on Triangles with Quintic and Nonic Bivariate Polynomials’, ACM Transactions on Mathematical Software 16, 253–257.Google Scholar
- Srivastava, R.M.: 1986, ‘Philip and Watson — Quo Vadunt?’, Math. Geol. 18, 141–149.Google Scholar
- Trevis, J.W., Whittaker, A.D., and McCauley, D.J.: 1991, ‘Efficient Use of Data in the Kriging of Soil pH’, ASAE paper 917074, ASAE, St. Joseph, Michigan.Google Scholar
- Watson, D.F. and Philip, G.M.: 1985, ‘A Refinement of Inverse Distance Weighted Interpolation’, Geo-Processing 2, 315–327.Google Scholar
Copyright information
© Kluwer Academic Publishers 1993