TITLE:
A Computational Comparison between Optimization Techniques for Wells Placement Problem: Mathematical Formulations, Genetic Algorithms and Very Fast Simulated Annealing
AUTHORS:
Ghazi D. AlQahtani, Ahmed Alzahabi, Timothy Spinner, Mohamed Y. Soliman
KEYWORDS:
Wells Placement Optimization Integer Programming Simulated Annealing Genetic Algorithm
JOURNAL NAME:
Journal of Materials Science and Chemical Engineering,
Vol.2 No.10,
October
28,
2014
ABSTRACT:
This study considers several
computational techniques for solving one formulation of the wells placement
problem (WPP). Usually the wells placement problem is tackled through the
combined efforts of many teams using conventional approaches, which include
gathering seismic data, conducting real-time surveys, and performing production
interpretations in order to define the sweet spots. This work considers one
formulation of the wells placement problem in heterogeneous reservoirs with
constraints on inter-well spacing. The performance of three different types of
algorithms for optimizing the well placement problem is compared. These three
techniques are: genetic algorithm, simulated annealing, and mixed integer
programming (IP). Example case studies show that integer programming is the
best approach in terms of reaching the global optimum. However, in many cases,
the other approaches can often reach a close to optimal solution with much more
computational efficiency.