The Fourier Integral Method: An efficient spectral method for simulation of random fields

The Fourier Integral Method (FIM) of spectral simulation, adapted to generate realizations of a random function in one, two, or three dimensions, is shown to be an efficient technique of non-conditional geostatistical simulation. The main contribution is the use of the fast Fourier transform for both numerical calculus of the density spectral function and as generator of random finite multidimensional sequences with imposed covariance. Results obtained with the FIM are compared with those obtained by other classic methods: Shinozuka and Jan Method in 1D and Turning Bands Method in 2D and 3D, the points for and against different methodologies are discussed. Moreover, with the FIM the simulation of nested structures, one of which can be a nugget effect and the simulation of both zonal and geometric anisotropy is straightforward. All steps taken to implement the FIM methodology are discussed.

[1]  R. Bracewell The Fourier Transform and Its Applications , 1966 .

[2]  C. G. Fox An inverse Fourier transform algorithm for generating random signals of a specified spectral form , 1987 .

[3]  P. Brooker Two-dimensional simulation by turning bands , 1985 .

[4]  George Christakos,et al.  Stochastic simulation of spatially correlated geo-processes , 1987 .

[5]  David L. Freyberg,et al.  Simulation of one-dimensional correlated fields using a matrix-factorization moving average approach , 1990 .

[6]  A. Journel Geostatistics for Conditional Simulation of Ore Bodies , 1974 .

[7]  Richard W. Kulp,et al.  The Analysis of Time Series, 4th Ed. , 1991 .

[8]  M. Shinozuka,et al.  Digital simulation of random processes and its applications , 1972 .

[9]  Aristotelis Mantoglou,et al.  Digital simulation of multivariate two- and three-dimensional stochastic processes with a spectral turning bands method , 1987, Mathematical Geology.

[10]  Francisco Javier Duoandikoetxea Zuazo Análisis de Fourier , 1991 .

[11]  Leon E. Borgman,et al.  Three-Dimensional, Frequency-Domain Simulations of Geological Variables , 1984 .

[12]  H. Weaver Theory of Discrete and Continuous Fourier Analysis , 1989 .

[13]  Linus Schrage,et al.  A More Portable Fortran Random Number Generator , 1979, TOMS.

[14]  Peter A. Dowd,et al.  A review of recent developments in geostatistics , 1991 .

[15]  E. Brigham,et al.  The fast Fourier transform , 2016, IEEE Spectrum.

[16]  Chris Chatfield,et al.  The Analysis of Time Series , 1990 .

[17]  E. Brigham,et al.  The fast Fourier transform and its applications , 1988 .

[18]  David R. Cox,et al.  The Theory of Stochastic Processes , 1967, The Mathematical Gazette.

[19]  G. Matheron The intrinsic random functions and their applications , 1973, Advances in Applied Probability.

[20]  A. Mantoglou,et al.  The Turning Bands Method for simulation of random fields using line generation by a spectral method , 1982 .