Conditional Spectral Simulation with Phase Identification

Journal of the International Association for Mathematical Geology - Tập 30 Số 3 - Trang 285-308 - 1998
Yao, Tingting1
1Department of Geological & Environmental Science, Stanford University, Stanford

Tóm tắt

Spectral simulation is used widely in electrical engineering to generate random fields with a given covariance spectrum. The algorithms used are fast particularly when based on Fast Fourier Transform (FFT). However, because of lack of phase identification, spectral simulation only generates unconditional realizations. Local data conditioning is obtained typically by adding a simulated kriging residual. This conditioning process requires an additional kriging at each simulated node thus forfeiting the speed advantage of FFT. A new algorithm for conditioning is proposed whereby the phase values are determined iteratively to ensure approximative data reproduction while reproducing the frequency spectrum, that is, the covariance model. A case study is presented to demonstrate the algorithm.

Từ khóa


Tài liệu tham khảo

citation_title=Three-dimensional frequency-domain simulations of geological variables; citation_inbook_title=Geostatistics for natural resources characterization; citation_publication_date=1984; citation_pages=517-541; citation_id=CR1; citation_author=L. Borgman; citation_author=M. Taheri; citation_author=R. Hagan; citation_publisher=Reidel Publ.

citation_title=The Fourier Transform and its application; citation_publication_date=1986; citation_id=CR2; citation_author=R. Bracewell; citation_publisher=McGraw Hill, Inc.

citation_journal_title=IEEE Transaction on Circuits and Systems, Part II: Analog and Digital Signal Processing; citation_title=Implementation of the FFT butterfly with redundant arithmetic; citation_author=J. Bruguera; citation_volume=43; citation_issue=10; citation_publication_date=1996; citation_pages=717-723; citation_id=CR3

citation_title=Conditional fBm simulation with dual kriging; citation_inbook_title=Geostatistics for the next century; citation_publication_date=1994; citation_pages=407-421; citation_id=CR4; citation_author=J. Chu; citation_author=A. Journel; citation_publisher=Kluwer Publ.

citation_title=Direct assessment of accuracy and precision; citation_inbook_title=Geostatistics Wollongang '96; citation_publication_date=1996; citation_pages=115-125; citation_id=CR5; citation_author=C. Deutsch; citation_publisher=Kluwer Publ.

citation_title=GSLIB: Geostatistical Software Library and User's Guide; citation_publication_date=1992; citation_id=CR6; citation_author=C. Deutsch; citation_author=A. Journel; citation_publisher=Oxford Univ. Press

Gutjahr, A., Kallay, P., and Wilson, J., 1987, Stochastic models for two-phase flow: A spectral-perturbation approach: Eos, Transaction, American Geophysical Union, v. 68,no. 44, p. 1266–1267.

citation_title=Mining geostatistics; citation_publication_date=1978; citation_id=CR8; citation_author=A. Journel; citation_author=C. Huijbregts; citation_publisher=Academic Press

McKay, D., 1988, A fast Fourier transform method for generation of random fields: Unpubl. master's thesis, New Mexico Institute of Mining and Technology, 92 p.

citation_journal_title=Math. Geology; citation_title=The Fourier integral method: An efficient spectral method for simulation of random fields; citation_author=E. Pardo-Iguzquiza, M. Chica-Olmo; citation_volume=25; citation_issue=4; citation_publication_date=1993; citation_pages=177-217; citation_id=CR10

Thông tin
Thông tin xuất bản

Journal of the International Association for Mathematical Geology

Tập 30 Số 3

285-308

Thông tin tác giả