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Finite-Element Modeling of Borehole Breakouts for In Situ Stress Determination
Borehole breakouts appear in drilling and production operations when rock subjected to in situ stress experience shear failure. By finite-element modeling of borehole breakouts, the authors obtained the stress state close to the borehole wall, the shape of borehole breakouts, and the mechanism of borehole breakouts in terms of initiation, propagation, and stability. It is desirable that this information on borehole breakouts be used to determine in situ stress by inverse analysis. Artificial neural network provides such a tool to establish the relationship between in situ stress and information on borehole breakouts. Determination of in situ stress by inverse analysis consisted of two steps. First, finite-element modeling provided sets of data on in situ stress and borehole breakout measures, which were used to train an artificial neural network that could eventually represent the relationship between the in situ stress and borehole breakout measures. Second, for a given measure of borehole breakouts, the trained artificial neural network was used to predict the corresponding in situ stress. Verification of the modeling of borehole breakouts was conducted, and numerical experiments were carried out. The results showed that the inverse analysis based on finite-element modeling of borehole breakouts and artificial neural network can effectively determine the in situ stress.
Finite-Element Modeling of Borehole Breakouts for In Situ Stress Determination
Borehole breakouts appear in drilling and production operations when rock subjected to in situ stress experience shear failure. By finite-element modeling of borehole breakouts, the authors obtained the stress state close to the borehole wall, the shape of borehole breakouts, and the mechanism of borehole breakouts in terms of initiation, propagation, and stability. It is desirable that this information on borehole breakouts be used to determine in situ stress by inverse analysis. Artificial neural network provides such a tool to establish the relationship between in situ stress and information on borehole breakouts. Determination of in situ stress by inverse analysis consisted of two steps. First, finite-element modeling provided sets of data on in situ stress and borehole breakout measures, which were used to train an artificial neural network that could eventually represent the relationship between the in situ stress and borehole breakout measures. Second, for a given measure of borehole breakouts, the trained artificial neural network was used to predict the corresponding in situ stress. Verification of the modeling of borehole breakouts was conducted, and numerical experiments were carried out. The results showed that the inverse analysis based on finite-element modeling of borehole breakouts and artificial neural network can effectively determine the in situ stress.
Finite-Element Modeling of Borehole Breakouts for In Situ Stress Determination
Zhang, Hua (Autor:in) / Yin, Shunde (Autor:in) / Aadnoy, Bernt S. (Autor:in)
04.10.2018
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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