Stick-slip is kind of vibration which associated with drilling operation in around the bottom hole assembly (BHA) due to the small clearance between drill string & the open hole and due to the eccentric rotating of string. This research presents results of specific experimental study that was run by using two types of drilling mud (Fresh water Bentonite & Polymer), with/without Nanoparticle size materials of MgO in various ratios and computes the rheological properties of mud for each concentration [Yield point, plastic viscosity, Av, PH, filter loss (30 min), filter cake, Mud Cake Friction, Friction Factor]. These results then were used to find a clear effects of Nanoparticle drilling mud rheology on stick - slip strength by several perspectives through a special “Torque and Drag” software which simulate the torque amount expected on BHA during drilling a vertical well in different conditions using real drilling string design that usually used in Iraqi oil fields. Thus to mitigate or to prevent stick–slip and cure the sequence events that could happen to both of drilling string and the well, i.e. Bit/BHA wear, pipe sticking, borehole instability and low Rate of penetration. Our study concluded that there are good reduction in the torque from (2031lb-ft) to (1823lb-ft) using polymer mud and torque reduction from (4000lb-ft) to (3450lb-ft) using Fresh Water Bentonite, these results do not include any breaking in the satisfactory range of other mud rheology.
KE Sharquie, AA Al-Nuaimy, FA Al-Shimary, Saudi medical journal, 2005 - Cited by 20
N, N′- bis[4-hydroxy phenyl] pyromillitdiimide [II] was prepared from the corresponding diamic acid , which was transfered to its new ester by the reaction with chloroethyl acetate [III ], [III] was used to prepare the novel hydrazide derivative [IV] , which was allowed to react with several aldehydes to yield the hydrazones [V – IX]. All the new compounds were synthesized , and characterized by their melting points .HNMR for some of them1FTIR,C,H,N analysis and ,
The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.
Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai
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