51st U.S. Rock Mechanics/Geomechanics Symposium,
San Francisco, California, USA
2017. American Rock Mechanics Association
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138 since 2007
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ABSTRACT: Unconfined compressive strength (UCS) is the key parameter to; estimate the in situ stresses of the rock, alleviate drilling problems, design optimal fracture geometry and to predict optimum mud weight. Retrieving reservoir rock samples throughout the depth of the reservoir section and performing laboratory tests on them are extremely expensive as well as time consuming. Therefore, mostly UCS predicted from empirical correlations. Most of the empirical correlations for UCS prediction are based on elastic parameters or on compressional wave velocity. These correlations were developed using linear or non-linear regression techniques. This paper presents a rigorous empirical correlation based on the weights and biases of Artificial Neural Network to predict UCS. The testing of new correlation on real field data gave a less error between actual and predicted data, suggesting that the proposed correlation is very robust and accurate. Therefore, the developed correlation can serve as handy tool to help geo-mechanical engineers in order to determine the UCS.
UCS defines the strength of the rock when subjected to uniaxial loading. Under unconfined conditions, it is the maximum axial compressive stress that a perfectly right-cylindrical sample of material can withstand. UCS has been used widely in petroleum industry to estimate the in-situ stresses of the rock, to make geo-mechanical earth model, to optimize of rate of penetration in drilling and to design optimal hydraulic fracture parameters in production (Gatens et al., 1990). Accurate prediction of UCS can avoid severe drilling problems which includes well bore collapse, hole pack off, sand production and tight holes (Khaksar et al., 2009).
UCS can be determined by means of static methods. These methods are uniaxial and tri-axial compressional tests, which are conducted on a right cylindrical cores retrieved from the depth of the interest. These tests measure the deformation of rock sample by the application of known force (Barree et al., 2009). The stress-strain deformation curves are generated from these tests. These curves are traced and analyzed to obtain UCS as well as elastic parameters (Jaegar et al., 2007).
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