Improvement of Cement Placement in Horizontal Wells by Liner Rotation Using CFD

Nowadays, efficient cementing job is a vital operation in the life of a well. Appropriate cement displacement can extend the life of the wellbore by providing long-term zonal isolation. However, cement displacement is challenging issue in horizontal wells, but achieving maximum isolation is possible by using different techniques like proper mud properties, velocity and displacement rate, centralization of casing. There are several studies has done in this filed for improving cement displacement. Practices and laboratory experiments has revealed that the casing movement can bring improvement in cement displacement; either reciprocation or rotation motion. In this research focused mainly on seven inch (7) liner rotation by using ANSYS CFX14 software. The software implement computational Fluid Dynamic (CFD) model for simulating and ensure the improvements in horizontal wells. Moreover, affect of pressure drop (P) and Equivalent Circulation Density (ECD) on pipe rotation were investigated. According to simulation result, pressure drop will increase by raising rotation speed. Further, equivalent circulation density will increase as well. Increase in this two factor leads to high efficiency in cement placemen

Prediction of Earnings Management by Use of Multilayer Perceptron Neural Networks with Two Hidden Layers in Various Industries

Over the last few years, increase in the number of financial crisis cases has attracted the attention of a great number of investors and creditors to the prediction of these cases by using the data available from financial statements of the corporations in order to prevent losses which are caused by them. Many of the studies about the earning management only focus on identifying the factors which affect the earnings management and relation between earnings management and these factors and not on using these factors in order to predict the earnings management. On the other hand, in the present study, 12 influential factors, which are introduced by former studies, are used to evaluate the predicting ability of the neural networks for prediction of earnings management and its different levels. Multilayer perceptron neural network with 2 hidden layers is used for prediction. Moreover, the required data is obtained from the financial statements of the listed companies of Tehran Stock Exchange (TSE). The results show that the applied neural network method has an acceptable ability for the prediction of earnings management and its different levels in all different studies industries. Research paper Keywords: Earnings management, Neural network, Multilayer perceptron, Accrual items Reference to this paper should be made as follows: Mahmoudi, S., Mahmoudi, S., & Mahmoudi, A. (2017). “Prediction of Earnings Management by Use of Multilayer Perceptron Neural Networks with Two Hidden Layers in Various Industries”, Journal of Entrepreneurship, Business and Economics, Vol. 5, No. 1, pp. 216–236

Phase-controlled atom-photon entanglement in a three-level V-type atomic system via spontaneously generated coherence

We investigate the dynamical behavior of the atom-photon entanglement in a V-type three-level quantum system using the atomic reduced entropy. It is shown that an atom and photons are entangled at the steady-state; however disentanglement can also be achieved in an especial condition. It is demonstrated that in the presence of quantum interference induced by spontaneous emission, the reduced entropy and the atom-photon entanglement are phase-dependent. Non-stationary solution is also obtained when the quantum interference due to the spontaneous emission is completely included.Comment: 16 pages, 7 figure