Conceptual Design of an In-Pipe Displacement System Applicable for Oil Well Production Column

2021 ◽  
Author(s):  
Juan Carlos Romero Albino ◽  
Saulo Figliuolo ◽  
Valert Beal ◽  
Luis Alberto Breda Mascarenhas ◽  
Hugo Francisco Lisboa Santos
Author(s):  
Saulo Queiroz Figliuolo ◽  
Valter Estevão Beal ◽  
Luis Alberto Breda Mascarenhas ◽  
Juan Carlos Romero Albino ◽  
Hugo Francisco Lisboa Santos

Abstract Oil well production rate should be maintained during its lifecycle and maintenance interventions are necessary to reach this goal. Production engineer teams work on different ways to make the production stable and to enhance the oil recovery from the reservoirs. However, interventions are necessary to maintain or recover the production rate. Some problems that cause maintenance are malfunctioning/wear of equipment, clogging/obstruction and operational mistakes. These maintenances are required using expensive equipment, especially on offshore operations. In order to reduce the overall cost of interventions, robotic systems have been proposed. In this work, a conceptual development for a robotic production column well intervention system is proposed. This equipment should be strong enough to resist oil well environmental characteristics. Nowadays, the challenge involves high pressure and high temperature wells, high flow rates, a long/deep well and other very hostile features. Even though, this device has to be very slim and lightweight because it will be responsible for carrying on other systems (measurement / inspection tools, completion tools, etc.) displacing into the oil well production column. On the other hand, it needs to have highly efficient power consumption since the power availability is usually limited in the actuation environment of this autonomous equipment. In order to guarantee the achievement of the desirable requirements, the design team followed the best practices of the product development process aided by a design for lifecycle guidelines.


2016 ◽  
Vol 9 (1) ◽  
pp. 21-32 ◽  
Author(s):  
Xin Ma ◽  
Zhi-bin Liu

Predicting the oil well production is very important and also quite a complex mission for the petroleum engineering. Due to its complexity, the previous empirical methods could not perform well for different kind of wells, and intelligent methods are applied to solve this problem. In this paper the multi expression programming (MEP) method has been employed to build the prediction model for oil well production, combined with the phase space reconstruction technique. The MEP has shown a better performance than the back propagation networks, gene expression programming method and the Arps decline model in the experiments, and it has also been shown that the optimal state of the MEP could be easily obtained, which could overcome the over-fitting.


Author(s):  
Zhi Ma ◽  
Changfeng Wang ◽  
Zhonghai Qin ◽  
Xiaolong Gao ◽  
Lili Wei ◽  
...  

2017 ◽  
Vol 11 (10) ◽  
pp. 81
Author(s):  
Nurdi Irianto ◽  
Sudjati Rachmat ◽  
Leksono Mucharam ◽  
Sapto Wahyu Indratno

In the petroleum industry, it is common practice to do survey well liquid level for monitoring well in the purpose of evaluation well production capacity, for setting performance of downhole pump. Here we proposed liquid level survey using acoustic well sounder (echosounder) equipment. The reading of liquid level in the oil well is contained noises due to some physical and mechanical condition. An idea to handle large scattered field data contains noises is smoothness method by Tikhonov regularization.Liquid level survey is set up under shunt in well condition, to clearly monitoring liquid level rises in the well column. So, we have acquired field data reading. Beside the field data reading using echosounder tool, we also need to calculate expected liquid level, because that noises factor in the field data. The equation is generated to define calculation of liquid level increases in the well column as a function of time. The initial condition of started liquid column height h0 and well production rate Q0 at t=0 is definite. We build the Volterra integral equation of the 1st kind for this calculation purpose.The ill-posed problem performs in the data, needs the solution for smoothness. Tikhonov regularization (Least Squared problem) has handling this problem. Some value of regularization parameter were employed to the calculation.This paper is an innovative idea to maximum utilization of fluid level data monitoring in the well, while the acquired data is scattered or contains error. After smoothness of the data, qualified model solution curve is fully advantage for well interpretation. 


2018 ◽  
Author(s):  
Camilo Andrés Guerrero-Martin ◽  
Erik Montes-Páez ◽  
Márcia Cristina Khalil de Oliveira ◽  
Jonathan Campos ◽  
Elizabete F. Lucas

2016 ◽  
Author(s):  
Guoqing Han ◽  
Chaodong Tan ◽  
Jun Li ◽  
Zhejun Pan ◽  
He Zhang ◽  
...  

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