Implementation of Tikhonov Regularization in Oil Well Liquid Level Reading Data


  •  Nurdi Irianto    
  •  Sudjati Rachmat    
  •  Leksono Mucharam    
  •  Sapto Indratno    

Abstract

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.

 



This work is licensed under a Creative Commons Attribution 4.0 License.
  • Issn(Print): 1913-1844
  • Issn(Onlne): 1913-1852
  • Started: 2007
  • Frequency: monthly

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Google-based Impact Factor (2018): 6.49

h-index (January 2018): 30

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