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Transcript
Geotechnical Properties of the Rodessa Formation in East Texas:
A Compressive and Tensile Strength Analysis
Using Artificial Neural Network Methodology
Pawan Kakarla and Wesley A. Brown
Department of Geology, Stephen F. Austin State University, 1936 North St., Nacogdoches, Texas 75962
GCAGS Explore & Discover Article #00132*
http://www.gcags.org/exploreanddiscover/2016/00132_kakarla_and_brown.pdf
Posted September 13, 2016.
*
Abstract published in the GCAGS Transactions (see footnote reference below) and delivered as a poster presentation at
the 66th Annual GCAGS Convention and 63rd Annual GCSSEPM Meeting in Corpus Christi, Texas, September 18–
20, 2016.
ABSTRACT
The estimation of rock mass strength is becoming more and more important because this is a key parameter in rock mechanics and geotechnics which are used in the
design of geotechnical structures like tunnels, dams, and slopes. The main focus of this
study is to calculate the shear strength of certain rocks and to correlate their stability
when they are injected with fluids. The parameters which will be used are the unconfined (uniaxial) compression test (UCS) and tensile strength. In this study, a soft computing approach which is known as Artificial Neural Networks (ANN) will be used to predict the strength of rocks from the Rodessa Formation of the East Texas region. Core
samples from the Rodessa Formation will be taken from the Stephen F. Austin State
University Core Lab Repository and tested at the University of Texas at El Paso. Parameters such as water absorption, dry density, saturation density, and bulk density will
be experimentally determined using procedures given by the International Society of
Rock Mechanics . These procedures can predict the uniaxial compressive strength and
tensile strength of the rocks from the Rodessa Formation. Based on previous studies, it
is found out that artificial neural networks are quite accurate in providing the strength
of the rocks. Therefore, results obtained will be useful in characterizing the rocks of the
Rodessa Formation for practical applications.
Originally published as: Kakarla, P., and W. A. Brown, 2016, Geotechnical properties of the Rodessa Formation in East
Texas: A compressive and tensile strength analysis using artificial neural network methodology: Gulf Coast Association
of Geological Societies Transactions, v. 66, p. 983.
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