메뉴 건너뛰기




Volumn 53, Issue 1, 2005, Pages 103-120

Inversion of nuclear well-logging data using neural networks

Author keywords

[No Author keywords available]

Indexed keywords

DATA ACQUISITION; GAMMA RAYS; NEURAL NETWORKS; NEUTRONS; PARTICLE DETECTORS; POROSITY; SALINITY MEASUREMENT; SATURATION (MATERIALS COMPOSITION);

EID: 12844272223     PISSN: 00168025     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1365-2478.2005.00432.x     Document Type: Article
Times cited : (32)

References (36)
  • 1
    • 0034162355 scopus 로고    scopus 로고
    • Automatic detection of buried utilities and solid objects with GPR using neural networks and pattern recognition
    • Al-Nuaimy W., Huang Y., Nakhash M., Fang M.T.C., Nguyen V.T. and Erikse A. 2000. Automatic detection of buried utilities and solid objects with GPR using neural networks and pattern recognition. Journal of Applied Geophysics 43, 157-165.
    • (2000) Journal of Applied Geophysics , vol.43 , pp. 157-165
    • Al-Nuaimy, W.1    Huang, Y.2    Nakhash, M.3    Fang, M.T.C.4    Nguyen, V.T.5    Erikse, A.6
  • 2
    • 0034233231 scopus 로고    scopus 로고
    • Neural networks in geophysical applications
    • van der Baan M. and Jutten C. 2000. Neural networks in geophysical applications. Geophysics 65, 1032-1047.
    • (2000) Geophysics , vol.65 , pp. 1032-1047
    • van der Baan, M.1    Jutten, C.2
  • 4
    • 0034254418 scopus 로고    scopus 로고
    • Quantitative 2D VLF data interpretation
    • Beamish D. 2000. Quantitative 2D VLF data interpretation. Journal of Applied Geophysics 45, 33-47.
    • (2000) Journal of Applied Geophysics , vol.45 , pp. 33-47
    • Beamish, D.1
  • 5
    • 0032925830 scopus 로고    scopus 로고
    • Inferring the lithology of borehole rocks by applying neural network classifiers to downhole logs: An example from the Ocean Drilling Program
    • Benaouda W.G., Whitmarsh R.B., Rothwell R.G. and MacLeod C. 1999. Inferring the lithology of borehole rocks by applying neural network classifiers to downhole logs: an example from the Ocean Drilling Program. Geophysical Journal International 136, 477-491.
    • (1999) Geophysical Journal International , vol.136 , pp. 477-491
    • Benaouda, W.G.1    Whitmarsh, R.B.2    Rothwell, R.G.3    MacLeod, C.4
  • 7
    • 0032172620 scopus 로고    scopus 로고
    • Automatic NMO correction and velocity estimation by a feed-forward neural network
    • Calderon-Macias C., Sen M.K. and Stoffa P.L. 1998. Automatic NMO correction and velocity estimation by a feed-forward neural network. Geophysics 63, 1696-1707.
    • (1998) Geophysics , vol.63 , pp. 1696-1707
    • Calderon-Macias, C.1    Sen, M.K.2    Stoffa, P.L.3
  • 8
    • 0342264727 scopus 로고    scopus 로고
    • Artificial neural networks for parameter estimation in geophysics
    • Calderon-Macias C., Sen M.K. and Stoffa P.L. 2000. Artificial neural networks for parameter estimation in geophysics. Geophysical Prospecting 48, 21-47.
    • (2000) Geophysical Prospecting , vol.48 , pp. 21-47
    • Calderon-Macias, C.1    Sen, M.K.2    Stoffa, P.L.3
  • 12
    • 0035394457 scopus 로고    scopus 로고
    • Inversion of DC resistivity data using neural networks
    • El-Qady G. and Ushijima K. 2001. Inversion of DC resistivity data using neural networks. Geophysical Prospecting 49, 417-430.
    • (2001) Geophysical Prospecting , vol.49 , pp. 417-430
    • El-Qady, G.1    Ushijima, K.2
  • 14
    • 0025573942 scopus 로고
    • Occam's inversion to generate smooth, two-dimensional models from magnetotelluric data
    • de Groot-Hedlin C. and Constable S. 1990. Occam's inversion to generate smooth, two-dimensional models from magnetotelluric data. Geophysics 55, 1613-1624.
    • (1990) Geophysics , vol.55 , pp. 1613-1624
    • de Groot-Hedlin, C.1    Constable, S.2
  • 15
    • 0035394572 scopus 로고    scopus 로고
    • Porosity and permeability prediction from wireline logs using artificial neural networks: A North Sea case study
    • Helle H.B., Bhatt A. and Ursin B. 2001. Porosity and permeability prediction from wireline logs using artificial neural networks: A North Sea case study. Geophysical Prospecting 49, 431-444.
    • (2001) Geophysical Prospecting , vol.49 , pp. 431-444
    • Helle, H.B.1    Bhatt, A.2    Ursin, B.3
  • 16
    • 0016568437 scopus 로고
    • Resistivity inversion with ridge regression
    • Inman J.R. 1975. Resistivity inversion with ridge regression. Geophysics 40, 798-817.
    • (1975) Geophysics , vol.40 , pp. 798-817
    • Inman, J.R.1
  • 17
    • 0030438599 scopus 로고    scopus 로고
    • 3D Horizon tracking using artificial neural networks
    • Legget M., Sandham W.A. and Durrani T.S. 1996. 3D Horizon tracking using artificial neural networks. First Break 14, 413-418.
    • (1996) First Break , vol.14 , pp. 413-418
    • Legget, M.1    Sandham, W.A.2    Durrani, T.S.3
  • 19
    • 0028259705 scopus 로고
    • Inversion of 3D DC resistivity data using an approximate inverse mapping
    • Li Y.G. and Oldenburg D.W. 1994. Inversion of 3D DC resistivity data using an approximate inverse mapping. Geophysical Journal International 116, 527-537.
    • (1994) Geophysical Journal International , vol.116 , pp. 527-537
    • Li, Y.G.1    Oldenburg, D.W.2
  • 20
    • 0344029523 scopus 로고    scopus 로고
    • Rapid 2D resistivity and IP inversions using the least squares method
    • The RES2DINV manual
    • Loke M.H. 1998. Rapid 2D resistivity and IP inversions using the least squares method. The RES2DINV manual.
    • (1998)
    • Loke, M.H.1
  • 21
    • 0036509413 scopus 로고    scopus 로고
    • A comparison of the Gauss-Newton and quasi-Newton method in resistivity imaging inversion
    • Loke M.H. and Dahlin W. 2002. A comparison of the Gauss-Newton and quasi-Newton method in resistivity imaging inversion. Journal of Applied Geophysics 49, 149-162.
    • (2002) Journal of Applied Geophysics , vol.49 , pp. 149-162
    • Loke, M.H.1    Dahlin, W.2
  • 23
    • 0034036094 scopus 로고    scopus 로고
    • Evaluation of small-loop transient EM soundings to locate the Sherwood Sandstone aquifer and confining formations at well sites in the Vale of York, England
    • Meju M.A., Fenning P.J. and Hawkins T.R.W. 2000. Evaluation of small-loop transient EM soundings to locate the Sherwood Sandstone aquifer and confining formations at well sites in the Vale of York, England. Journal of Applied Geophysics 44, 217-236.
    • (2000) Journal of Applied Geophysics , vol.44 , pp. 217-236
    • Meju, M.A.1    Fenning, P.J.2    Hawkins, T.R.W.3
  • 24
    • 0027071123 scopus 로고
    • Automated first arrival picking: A neural network approach
    • Murat M.E. and Rudman A. 1992. Automated first arrival picking: A neural network approach. Geophysical Prospecting 40, 587-604.
    • (1992) Geophysical Prospecting , vol.40 , pp. 587-604
    • Murat, M.E.1    Rudman, A.2
  • 25
    • 0032826176 scopus 로고    scopus 로고
    • Velocity inversion in cross-hole seismic tomography by the counter-propagation neural network, genetic algorithm and evolutionary programming techniques
    • Nath S.K., Chakraborty S., Singh S.K. and Ganguly N. 1999. Velocity inversion in cross-hole seismic tomography by the counter-propagation neural network, genetic algorithm and evolutionary programming techniques. Geophysical Journal International 138, 108-124.
    • (1999) Geophysical Journal International , vol.138 , pp. 108-124
    • Nath, S.K.1    Chakraborty, S.2    Singh, S.K.3    Ganguly, N.4
  • 26
    • 0028557575 scopus 로고
    • Inversion of induced polarisation data
    • Oldenburg D.W. and Li Y. 1994. Inversion of induced polarisation data. Geophysics 59, 1327-1341.
    • (1994) Geophysics , vol.59 , pp. 1327-1341
    • Oldenburg, D.W.1    Li, Y.2
  • 27
    • 0022905994 scopus 로고
    • An arbitrary geometry finite element method for multigroup neutron transport with anisotropic scattering
    • de Oliveira C.R.E. 1986. An arbitrary geometry finite element method for multigroup neutron transport with anisotropic scattering. Progress in Nuclear Energy 18, 227-236.
    • (1986) Progress in Nuclear Energy , vol.18 , pp. 227-236
    • de Oliveira, C.R.E.1
  • 29
    • 0027009209 scopus 로고
    • Location of subsurface targets in geophysical data using neural networks
    • Poulton M.M., Stenberg B.K. and Glass C.E. 1992. Location of subsurface targets in geophysical data using neural networks. Geophysics 57, 1534-1544.
    • (1992) Geophysics , vol.57 , pp. 1534-1544
    • Poulton, M.M.1    Stenberg, B.K.2    Glass, C.E.3
  • 30
    • 0028262573 scopus 로고
    • Neural networks and inversion of seismic data
    • Roth G. and Tarantola A. 1994. Neural networks and inversion of seismic data. Journal of Geophysical Research 99, 6753-6768.
    • (1994) Journal of Geophysical Research , vol.99 , pp. 6753-6768
    • Roth, G.1    Tarantola, A.2
  • 31
    • 0034745969 scopus 로고    scopus 로고
    • Full 3D inversion of electromagnetic data on PC
    • Sasaki Y. 2001. Full 3D inversion of electromagnetic data on PC. Journal of Applied Geophysics 46, 45-54.
    • (2001) Journal of Applied Geophysics , vol.46 , pp. 45-54
    • Sasaki, Y.1
  • 33
    • 0033758042 scopus 로고    scopus 로고
    • Seismic amplitude inversion for interface geometry of multi-layered structures
    • Wang Y.H. and Pratt R.G. 2000. Seismic amplitude inversion for interface geometry of multi-layered structures. Pure and Applied Geophysics 157, 1601-1620.
    • (2000) Pure and Applied Geophysics , vol.157 , pp. 1601-1620
    • Wang, Y.H.1    Pratt, R.G.2
  • 34
    • 0003745154 scopus 로고    scopus 로고
    • Production and Testing of the VITAMIN-B6 Fine group and the BUGLE-96 Broad-Group Neutron/Photon Cross-section Libraries derived from ENDF/B-VI Nuclear data
    • NUREG/CR-6214/R1, ORNL-6795/R1, Oak Ridge National Laboratory, Oak Ridge, TN
    • White J.E., Ingersoll D.T., Wright R.Q., Hunter H.T., Slater C.O., Greene N.M., MacFarlane R.E. and Roussin R.W. 2000. Production and Testing of the VITAMIN-B6 Fine group and the BUGLE-96 Broad-Group Neutron/Photon Cross-section Libraries derived from ENDF/B-VI Nuclear data. NUREG/CR-6214/R1, ORNL-6795/R1, Oak Ridge National Laboratory, Oak Ridge, TN.
    • (2000)
    • White, J.E.1    Ingersoll, D.T.2    Wright, R.Q.3    Hunter, H.T.4    Slater, C.O.5    Greene, N.M.6    MacFarlane, R.E.7    Roussin, R.W.8
  • 35
    • 0003421109 scopus 로고
    • Institute for Parallel and Distributed High Performance Systems (IRVR), University of Stuttgart and Wilhelm-Schickard Institute for Computer Science, University of Tubingen, Germany, Report No. 6/95
    • Zell A. et al. 1995. Stuttgart Neural Network Simulator (SNNS) User manual, version 4.2. Institute for Parallel and Distributed High Performance Systems (IRVR), University of Stuttgart and Wilhelm-Schickard Institute for Computer Science, University of Tubingen, Germany, Report No. 6/95.
    • (1995) Stuttgart Neural Network Simulator (SNNS) User Manual, Version 4.2
    • Zell, A.1
  • 36
    • 0031225042 scopus 로고    scopus 로고
    • Magnetotelluric inversion using regularized Hopfield neural networks
    • Zhang Y. and Paulson K.V. 1997. Magnetotelluric inversion using regularized Hopfield neural networks. Geophysical Prospecting 45, 725-743.
    • (1997) Geophysical Prospecting , vol.45 , pp. 725-743
    • Zhang, Y.1    Paulson, K.V.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.