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Optimization of Well Placement and Number of Wells in one of Iranian oil reservoirs using Streamline Simulation

Afshari, Saeed | 2010

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 41440 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Pishvaie, Mahmoud Reza; Amin Shahidy, Babak
  7. Abstract:
  8. Determining the optimized number and best locations for new wells is a challenging problem due to the nonlinearly correlation and uncertainty associated with engineering, geological and economical variables affecting reservoir performance. The proposed location and configuration for new producers and injectors is usually nontrivial because of the complexity of the fluid flow in highly heterogeneous reservoirs. It depends on reservoir and fluid properties, well and surface equipment specifications and economic criteria. Various approaches have been proposed for this problem. Among those, direct optimization using the numerical simulator as the evaluation function is the most common solution.This study proposes an optimization technique based on a numerical simulator in combination with a stochastic optimization algorithm to solve the placement problem. In order to reduce the time required for numerical simulations, a streamline based simulator has been used. These simulators, in contrast with conventional finite deference simulators, are very fast and their accuracy is the same as the finite difference simulators. Different types of optimization algorithms (Simulated Annealing, Genetic Algorithm, Differential Evolution, Particle Swarm Optimization and Harmony Search) were used to find the optimum number and locations of the new wells and their performances have been compared in order to determine the suitable ones for this optimization problem.Performance of the technique was investigated by optimizing placement of injection or production wells in some synthetic reservoir models. It was observed from controlled experiments that the Harmony Search algorithm produced better results compared to other optimization algorithms with Particle Swarm Optimization algorithm stands in the second place after Harmony Search.In the next stage, the proposed technique using Harmony Search as the optimization algorithm were used to optimize the number and locations of new injection wells in a real west Iranian reservoir already having five production wells. The study also implemented well pattern optimization as a solution to the well placement problem. We used a general framework for constraining wells to exist within patterns and then optimized the parameters associated with the pattern type and geometry. Different types of optimization algorithms have been employed to find the optimum number and locations of production and injection wells in a synthetic reservoir model. Their results have been compared and it is found that Particle Swarm Optimization Algorithm has better performance in the well pattern optimization problem compared to the others
  9. Keywords:
  10. Streamline Simulation ; Genetic Algorithm ; Simulated Annealing Method ; Differential Evolution Algorithm ; Harmony Search Algorithm ; Particles Swarm Optimization (PSO) ; Well Placement ; Wellpattern Optimization

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