Abstract
We present a back-propagation neural network with an input layer in the form of a tapped delay line wich can be trained effectively on one or several well logs to recognize a particular geological marker. Subsequently, the neural network proposes locations of this marker on other wells in the field. Another neural network, similar in architecture to the first one, performs the same task for secondary markers using, in addition to the well logs, a depth reference function to the first marker. This method is shown to have better performance and better discrimination than standard cross-correlation techniques. It lends itself well for an interactive implementation on a workstation.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Baldwin, J. L., Otte, D. N., and Bateman, R. M., 1989, Computer emulation of human mental processes: application of neural network simulators to problems in well log pattern recognition: Proc. Soc. Petroleum Engineers, 64th Ann. Fall Meeting, p. 481–493.
Bishop, C. M., 1995, Neural networks for pattern recognition: Clarendon Press, Oxford, 485 p.
Doveton, J. H., 1994, Geologic log analysis using computer methods: Am. Assoc. Petroleum Geologists, Computer Methods in Geology No. 2, 169 p.
Gamero de Villarroel, H., Higgs, R., Bryant, I., Baygun, B., and Herron, M., 1995, Application of sequence stratigraphie re-interpretation of Lower Lagunillas Member to further development of bloque IV, Lake Maracaibo, Venezuela. Am. Assoc. Petroleum Geologists, Ann. Conv. Abstracts (Houston, Texas), p. 31A.
Griffiths, C. M., and Bakke, S., 1990, Interwell matching using a combination of petrophysically derived numerical lithologies and gene-typing techniques,in Hurst, A., Lovell, M. A., and Morton, A. C, eds., Geological applications of wireline logs: Geol. Soc. London Spec. Publ., No. 48, p. 133–151.
Haykin, S., 1994, Neural networks: MacMillan College Publ. Co., New York, 696 p.
Hecht-Nielsen R., 1990, Neurocomputing: Addison-Wesley Publ. Co., Reading, Massachusetts, 433 p.
Kuo, T.-B., 1986, Well log correlation using artificial intelligence: unpubl. doctoral dissertation, Texas, A&M Univ., 138 p.
Lineman, D. J., Mendelson, J. D., and Toksoz, M. N., 1987, Well to well correlation using knowledge-based systems and dynamic depth warping: Trans. SPWLA 28th Ann. Logging Symp., Paper UU, 25 p.
McCormack, M., 1991, Neural computing in geophysics: The Leading Edge, v. 10, no. 1, p. 11–15.
Moran, J. H., Confleau, M. A., Miller, G. K., and Timmons, J. P., 1962, Automatic computation of dipmeter logs digitally recorded on magnetic tapes: Jour. Petroleum Technology, v. 16, no. 7, p. 771–782.
Olea, R. A., 1994, Expert systems for automated correlation and interpretation of wireline logs: Math. Geology, v. 26, no. 8, p. 879–897.
Parlos, A. G., Chong, K. T., and Atiya, A., 1994, Application of the recurrent multilayer perceptron in modeling complex process dynamics: IEEE Trans. Neural Networks, v. 5, no. 2, p. 255–266.
Press, W. H., Teulosky, S. A., Vetterling, W. T., and Flannery, B. P., 1992, Numerical Recipes: Cambridge, 963 p.
Rogers, S. J., Fang, J. H., Karr, C. L., and Stanley, D. A., 1992, Determination of lithology from well logs using a neural network: Am. Assoc. Petroleum Geologists Bull., v. 76, no. 5, p. 731–739.
Smith, M., Carmichael, N., Reid, I., and Bruce, C, 1991, Lithofacies determination from wireline log data using a distributed neural network: Edinburgh Parallel Computing Centre, Rept. TR91-10, unpaginated.
Van Wagoner, J. C, Mitchum, R. M., Campion, K. M., and Rahmanian, V. D. 1990, Siliciclastiic sequence stratigraphy in well logs, cores and outcrops: Concepts for High-Resolution Correlation of Time and Facies, Am. Assoc. Petroleum Geologists, Methods in Exploration Series 7, 55 p.
Wiener, J. M., Rogers, J. A., and Moll, R. F., 1995, Predict permeability from wireline logs using neural networks: Petroleum Engineer Intern., v. 67, no. 5, p. 18–24.
Wu, X., and Nyland, E., 1987, Automated stratigraphic interpretation of well logs data: Geophysics, v. 52, no. 12, p. 1665–1676.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Luthi, S.M., Bryant, I.D. Well-log correlation using a back-propagation neural network. Math Geol 29, 413–425 (1997). https://doi.org/10.1007/BF02769643
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF02769643