Assessment of Chemical Injection to Mitigate Wax Deposition in Unconventional Wells

2021 ◽  
Author(s):  
Rafael M. D. Rosa ◽  
Arthur B. Soprana ◽  
Vinicius Girardi ◽  
Fernando M. Villagra

Abstract This work presents a numerical assessment of chemical inhibitor injection to mitigate wax deposition in unconventional wells. The goal of this study is to simulate the deposition of wax under several operational conditions and later optimize the chemical inhibitor injection position, using two different types of numerical simulations. A transient one-dimensional multiphase flow simulator - ALFAsim, with a dedicated wax model, was used to predict flow conditions such pressure, temperature, holdup and flow pattern profiles, as well the position and rates that wax accumulates. The results from the 1D simulation were then used as boundary conditions in a 3D CFD simulator, which aimed to assess how long it would take to a satisfactory homogenization of the inhibitor with the flow and what would be the minimum depth for the injector should be installed. In this work, a 1D multiphase flow simulator with wax deposition model was used to identify on which operational conditions (flow rates and environmental temperatures) an unconventional well would start to present wax deposition on its tubing walls. After defining the susceptible region where the paraffin could deposit, it was important to verify if the inhibitor would be well homogenized with the stream when reaching this region. For that, a 3D CFD simulation was performed, using information obtained directly from the 1D simulator as boundary conditions. The CFD model was capable to show the mixing evolution of the inhibitor with the stream and it was possible to determine the minimum distance where the injector should be placed to guarantee such homogeneity. A real well was selected to provide comparisons between field observations and simulated data, in order to validate the model assumptions and accuracy.

Author(s):  
C. Klein ◽  
S. Reitenbach ◽  
D. Schoenweitz ◽  
F. Wolters

Due to a high degree of complexity and computational effort, overall system simulations of jet engines are typically performed as 0-dimensional thermodynamic performance analysis. Within these simulations and especially in the early cycle design phase, the usage of generic component characteristics is common practice. Of course these characteristics often cannot account for true engine component geometries and operating characteristics which may cause serious deviations between simulated and actual component and overall system performance. This leads to the approach of multi-fidelity simulation, often referred to as zooming, where single components of the thermodynamic cycle model are replaced by higher-order procedures. Hereby the consideration of actual component geometries and performance in an overall system context is enabled and global optimization goals may be considered in the engine design process. The purpose of this study is to present a fully automated approach for the integration of a 3D-CFD component simulation into a thermodynamic overall system simulation. As a use case, a 0D-performance model of the IAE-V2527 engine is combined with a CFD model of the appropriate fan component. The methodology is based on the DLR in-house performance synthesis and preliminary design environment GTlab combined with the DLR in-house CFD solver TRACE. Both, the performance calculation as well as the CFD simulation are part of a fully automated process chain within the GTlab environment. The exchange of boundary conditions between the different fidelity levels is accomplished by operating both simulation procedures on a central data model which is one of the essential parts of GTlab. Furthermore iteration management, progress monitoring as well as error handling are part of the GTlab process control environment. Based on the CFD results comprising fan efficiency, pressure ratio and mass flow, a map scaling methodology as it is commonly used for engine condition monitoring purposes is applied within the performance simulation. Hereby the operating behavior of the CFD fan model can be easily transferred into the overall system simulation which consequently leads to a divergent operating characteristic of the fan module. For this reason, all other engine components will see a shift in their operating conditions even in case of otherwise constant boundary conditions. The described simulation procedure is carried out for characteristic operating conditions of the engine.


2018 ◽  
Author(s):  
Kanat Karatayev ◽  
Beibit Bissakayev ◽  
Tamer Saada ◽  
Benjamin Madeley ◽  
Alberto Brancolini ◽  
...  

2018 ◽  
Author(s):  
Kanat Karatayev ◽  
Beibit Bissakayev ◽  
Tamer Saada ◽  
Benjamin Madeley ◽  
Alberto Brancolini ◽  
...  

Author(s):  
Andreas Kyprianou ◽  
Andreas Tjirkallis

An important task in structural health monitoring (SHM) is that of damage detection under varying environmental and operational conditions. Structures, under varying environmental conditions, change their mass, elasticity and damping properties whereas changing operational conditions cause changes to excitations. A damage detection methodology implemented in these circumstances faces serious challenges since changes to structural behaviour imparted by environmental or operational conditions could be wrongly attributed to damage. The part of a damage detection decision algorithm that removes environmental and operational effects is called normalization. In this chapter a normalization methodology that is based on the similarity between continuous wavelet transform maxima decay lines is presented. This methodology is implemented on both simulated and experimental data. Simulated data were obtained from a three degree of freedom system. Varying environmental conditions were simulated by temperature dependent stiffness parameters and operating conditions by changing the colour of random excitation. Experimental data were obtained from damaged cantilever beams that were subjected to random excitations of different colour and varying temperatures.


2018 ◽  
Vol 17 (6) ◽  
pp. 1581-1597 ◽  
Author(s):  
Pengcheng Xu ◽  
Xin Liu ◽  
Heye Zhang ◽  
Dhanjoo Ghista ◽  
Dong Zhang ◽  
...  

2020 ◽  
Vol 192 ◽  
pp. 107288 ◽  
Author(s):  
Laio Oriel Seman ◽  
Luis Kin Miyatake ◽  
Eduardo Camponogara ◽  
Caio Merlini Giuliani ◽  
Bruno Ferreira Vieira

Wear ◽  
2017 ◽  
Vol 376-377 ◽  
pp. 1176-1184 ◽  
Author(s):  
Mazdak Parsi ◽  
Mustafa Kara ◽  
Madhusuden Agrawal ◽  
Netaji Kesana ◽  
Anchal Jatale ◽  
...  

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