... Abstract Optimizing bottom hole pressure is crucial for successful nitrogen lifting during clean-out phases after well interventions. Precisely predicting bottom hole pressure is vital for evaluating Inflow performance relationship (IPR) and optimizing operational parameters (e.g., nitrogen...

... for CTD. The proposed AI model leverages custom regression models for each MWD sensor, using various machine learning techniques such as Random Forest, Gradient Boosted Trees, and more to predict sensor values when a sensor fails. The model is continuously updated with new data and uses predefined...

... production control conveyance configuration azimuth friction production monitoring tractor bopd wellbore simulation presented prediction well intervention conference compartment category Introduction Historical records of the international oil industry abound with details...

..., as wellbore geometry becomes more complicated, it gets more difficult to predict the cleaning performance of fluids. As a result, optimization is often challenging. Therefore, this study aims to develop a data-driven model for predicting hole cleaning in deviated wells to optimize drilling performance. More...

... Abstract For many years, tubing force models (TFMs) have been used to predict coiled tubing (CT) reach in the wellbore, de-risk interventions, and track CT pipe life. Several input parameters, for example, the friction coefficient, the stripper friction, and the fluid viscosity, are difficult...

... prediction coefficient test fluid hole cleaning fibrous fluid test section Introduction Cleanout using coiled tubing (CT) is widely used in wellbore cleaning operations to remove material such as frac proppant, formation fines, drill cuttings, scales, and milling debris out of the wellbore...

.... The study is aimed to establish an accurate mechanistic model for optimizing wellbore cleanout in horizontal and inclined wells. The new CTV model is established to predict the initiation of bed particle movement during cleanout operations. The model is formulated considering the impact of fiber using...

... of identical material, with software modelling predictions providing an additional basis for comparison. Samples of 1.25" CT were situated concentrically within samples of 2.375" CT, and both were repeatedly bent and straightened on a standard CT fatigue testing system, with separate pressures in the inner...

... predicted the amount of diametrical growth. This ongoing work has already shown that rotation affects the fatigue life. Fatigue life calculations without rotation are usually conservative. It has also shown that rotation does not explain the over prediction of diametrical growth. It is currently believed...

... necessary to account for diameter growth when predicting CT life. When predicting CT longevity, low-cycle fatigue is determined using software to simulate planned operations. This helps minimize the risk of a specific CT string experiencing fatigue failure during the planned process. The software...

... Abstract A new process has been developed to track the life of coiled tubing (CT) strings. This paper documents the development of this process, including the material models and the software tools used by the process. The results of this process are a prediction of the CT life and diametrical...

... the influence of these parameters. coiled tubing operations gooseneck radius diameter stress distribution upstream oil & gas ksi straight configuration gooseneck completion installation and operations curvature prediction spool radius straightener internal pressure residual curvature...

... of the inner tubing to the inner diameter of the outer tubing) on axial friction pressure losses. The friction pressure gradients predicted by the CFD simulations were verified by comparing with the published studies and flow data from a field scale experimental set-up. At a constant flow rate...

.... Correlations based on curves through the middle of those bands can be considered estimates of "mean" life. Alternatively, such life estimates can be considered to exhibit "50%" survival. In other words, half the samples should fail before their predicted life and the other half should survive longer...

..., especially when scaled-up to a large-scale. production control production monitoring Reservoir Surveillance production logging Completion Installation and Operations concentration viscosity drag reduction characteristic shear rate Upstream Oil & Gas Flow property prediction surfactant...

... University to determine the fatigue de-rating factors for damaged CT produced an algorithm ("Flexor TU4") that can predict the remaining fatigue life of the CT based on specific damage geometry, tubing characteristics and operating parameters. However, the majority of the testing for this algorithm has been...

... Abstract Coiled tubing (CT) bending fatigue has been the subject of much research. Slickline (SL) fatigue is the subject of more recent, ongoing research. Fatigue life tracking and prediction systems are available for both CT and SL. However, these systems do not adequately include...

... exponent endurance limit fatigue data fatigue life residual stress Coiled tubing operations roughness surface roughness factor amplitude surface roughness conservatism society of petroleum engineers production enhancement eqn prediction material downhole intervention abrasion spe 100068...

... the combined loadings of axial compression and internal pressure. Previous analytical models to predict failure under such loading conditions have focused mostly on the buckling behavior of the short coiled-tubing section with minor modification of yield strength to account for the effect of internal pressure...

... force to the axial shortening of the tubing. The new model is consistent with experimental data from several previous studies. Moreover, through this new model, a simple technique is developed to predict the lockup length of the coiled tubing resulting from friction. This leads to an improved prediction...