Optimization of Horizontal Well Direction and Length Considering Geomechanics Properties and Drainage Area Using Genetic Algorithm in A Gas Field


  •  Prasandi Aziz    
  •  Tutuka Ariadji    

Abstract

To maximize a horizontal well production, we need to determine the optimum direction and horizontal well length that maximizes the gas field recovery for a certain constant flow rate called by plateau rate. This problem is conventionally solved by using a reservoir simulation model and trial and error procedure that consumes considerably a lot of time and efforts. This study uses a random search method, i.e., Genetic Algorithm (GA), to solve this optimization problem and it very much eases to find the best well location with less time and efforts consumed.

Along the general technique in directing a horizontal well towards the least principal stress of rocks, this study considers the geomechanics effects that influence the gas production performance. And also, the drainage area of horizontal well will be considered in this study to obtain the optimum horizontal well direction and length. In order to do this, a new proposed objective function for the GA has been constructed based on basic reservoir properties (i.e., porosity, permeability and gas saturation) and geomechanics properties (i.e., Young’s modulus and Poisson’s ratio). The results of the proposed method are validated using a reservoir model and economics evaluation.

It may be concluded that the applying GA, with the appropriate objective function, can give accurate and faster results compared with the trial and error method using reservoir simulator, technically and economically, and also the proposed method is able to reduce the amount of works considerably time.



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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(The data was calculated based on Google Scholar Citations)

Google-based Impact Factor (2018): 6.49

h-index (January 2018): 30

i10-index (January 2018): 163

h5-index (January 2018): 19

h5-median(January 2018): 25

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