The Prediction of the Tensile Strength of Sandstones from their petrographical properties using regression analysis and artificial neural network

Document Type : Research Paper

Authors

1 Geology Department, Bu-Ali Sina University, Hamedan, Iran

2 Geology Department, Shahid Chamran University, Ahvaz, Iran

Abstract

This study investigates the correlations among the tensile strength, mineral composition, and textural features of twenty-nine
sandstones from Kouzestan province. The regression analyses as well as artificial neural network (ANN) are also applied to evaluate
the correlations. The results of simple regression analyses show no correlation between mineralogical features and tensile strength.
However, the tensile strength of the sandstone was decreased by cement content reduction. Among the textural features, the packing
proximity, packing density, and floating contact as well as sutured contact are the most effective indices. Meanwhile, the stepwise
regression analyses reveal that the tensile strength of the sandstones strongly depends on packing density, sutured contact, and cement
content. However, in artificial neural network, the key petrographical parameters influencing the tensile strength of the sandstones are
packing proximity, packing density, sutured contact and floating contact, concave-convex contact, grain contact percentage, and
cement content. Also, the R-square obtained ANN is higher than that observed for the stepwise regression analyses. Based on the
results, ANN were more precise than the conventional statistical approaches for predicting the tensile strength of these sandstones from
their petrographical characteristics.

Keywords


Article Title [Persian]

پیش بینی مقاومت کششی ماسه سنگها از خصوصیات سنگ شناسی با استفاده از آنالیز رگرسیون و شبکه عصبی مصنوعی

Authors [Persian]

  • محمدحسین قبادی 1
  • ساجدین موسوی 2
  • مجتبی حیدری 1
  • بهروز رفیعی 1
1
2
Bell, F.G., Culshaw, M.G., 1978. Petrographic and engineering properties of sandstones from the Sneinton Formation,
Nottinghamshire, England. Quarterly Journal of Engineering Geology. 31: 5–21.
Bell, F.G., Lindsay, P., 1999. The petrographical and geomechanical properties of some sandstones from the Newspaper
Member of the Natal Group near Durban, South Africa. Engineering Geology. 53: 57–81.
Canakci, H., Pala, M., 2007. Tensile strength of basalt from a neural network. Engineering Geology. 93: 10–18.
Dobereiner, L., De Freitas, M.H., 1986. Geotechnical properties of weak sandstone. Geotechnique. 36 (1): 79–94.
Ersoy, A., Waller, M.D., 1995. Textural characterisation of rocks. Engineering Geology.39: 123 – 136.
Folk, R.L., 1974. Petrology of sedimentary rocks. Hemphill Publication Company, Austin.
Gurocak, Z., Solanki, P., Alemdag, S., Zaman, M.M., 2012. New considerations for empirical estimation of tensile
strength of rocks. Engineering Geology. 145-146: 1–8.
Howarth, D.F., Rowlands, J.C., 1986. Development of an index to quantify rock texture for qualitative assessment of
intact rock properties. Geotechnical Testing Journal. 9: 169-179.
International society for rock mechanics, 1981. Rock characterization, testing and monitoring, ISRM Suggested Methods.
Pergamon Press, Oxford.
James, G.A., Wynd, J.G., 1965. Stratigraphic nomenclature of Iranian Oil Consortium Agreement Area. Bulletin of
American Association of Petroleum Geology. 49(12): 2182-2245.
Kahn, J.S., 1956. The analysis and distribution of the properties of packing in sand size sediments. Journal of Geology.
64:385–395.
Kasabov, N.K., 1996. Foundations of Neural Networks, Fuzzy Systems and Knowledge. the MIT press, Cambridge.
Kamruzzaman, J., Begg, R.K., Sarker, R.A., 2006. Neural Networks in Finance and Manufacturing. Idea Group
Publishing, Hershey.
Merriam, R., Rieke III, H.H, Kim, Y.C., 1970. Tensile strength related to mineralogy and texture of some granitic rocks.
Engineering Geology. 4: 155 – 160.
Nova, A., Zaninetti, R., 1990. An investigation into the tensile behavior of a schistose rock. International Journal of Rock
Mechanics and Mining Sciences& Geomechanics Abstracts. 27(1): 231-242.
Ozcelik, Y., Bayram, F., Yasitli, N.E., 2012. Prediction of engineering properties of rock from microscopic data.Arabian
Journal of Geosciences.
Prikryl, R., 2001. Some microstructural aspects of strength variation in rocks. International Journal of Rock Mechanics
and Mining Sciences. 38: 671– 682.
Tugrul, A., Zarif, I.H., 1999. Correlation of mineralogical and textural characteristics with engineering properties of
selected granitic rocks from Turkey. Engineering Geology. 51: 303 – 317.
Tavallali, A., and Vervoort, A., 2010. Failure of layered sandstone under Brazilian test conditions: effect of micro-scale
parameters on macro-scale behavior. Rock Mechanics and Rock Engineering. 43(5):641-653.