Gibbs, Trevor Howard (2010-05). Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms. Master's Thesis. Thesis uri icon

abstract

  • Horizontal well placement determination within a reservoir is a significant and difficult step in the reservoir development process. Determining the optimal well location is a complex problem involving many factors including geological considerations, reservoir and fluid properties, economic costs, lateral direction, and technical ability. The most thorough approach to this problem is that of an exhaustive search, in which a simulation is run for every conceivable well position in the reservoir. Although thorough and accurate, this approach is typically not used in real world applications due to the time constraints from the excessive number of simulations. This project suggests the use of a genetic algorithm applied to the horizontal well placement problem in a gas reservoir to reduce the required number of simulations. This research aims to first determine if well placement optimization is even necessary in a gas reservoir, and if so, to determine the benefit of optimization. Performance of the genetic algorithm was analyzed through five different case scenarios, one involving a vertical well and four involving horizontal wells. The genetic algorithm approach is used to evaluate the effect of well placement in heterogeneous and anisotropic reservoirs on reservoir recovery. The wells are constrained by surface gas rate and bottom-hole pressure for each case. This project's main new contribution is its application of using genetic algorithms to study the effect of well placement optimization in gas reservoirs. Two fundamental questions have been answered in this research. First, does well placement in a gas reservoir affect the reservoir performance? If so, what is an efficient method to find the optimal well location based on reservoir performance? The research provides evidence that well placement optimization is an important criterion during the reservoir development phase of a horizontal-well project in gas reservoirs, but it is less significant to vertical wells in a homogeneous reservoir. It is also shown that genetic algorithms are an extremely efficient and robust tool to find the optimal location.
  • Horizontal well placement determination within a reservoir is a significant and difficult

    step in the reservoir development process. Determining the optimal well location is a

    complex problem involving many factors including geological considerations, reservoir

    and fluid properties, economic costs, lateral direction, and technical ability. The most

    thorough approach to this problem is that of an exhaustive search, in which a simulation

    is run for every conceivable well position in the reservoir. Although thorough and

    accurate, this approach is typically not used in real world applications due to the time

    constraints from the excessive number of simulations.

    This project suggests the use of a genetic algorithm applied to the horizontal well

    placement problem in a gas reservoir to reduce the required number of simulations. This

    research aims to first determine if well placement optimization is even necessary in a gas

    reservoir, and if so, to determine the benefit of optimization. Performance of the genetic

    algorithm was analyzed through five different case scenarios, one involving a vertical well and four involving horizontal wells. The genetic algorithm approach is used to

    evaluate the effect of well placement in heterogeneous and anisotropic reservoirs on

    reservoir recovery. The wells are constrained by surface gas rate and bottom-hole

    pressure for each case.

    This project's main new contribution is its application of using genetic algorithms to

    study the effect of well placement optimization in gas reservoirs. Two fundamental

    questions have been answered in this research. First, does well placement in a gas

    reservoir affect the reservoir performance? If so, what is an efficient method to find the

    optimal well location based on reservoir performance? The research provides evidence

    that well placement optimization is an important criterion during the reservoir

    development phase of a horizontal-well project in gas reservoirs, but it is less significant

    to vertical wells in a homogeneous reservoir. It is also shown that genetic algorithms are

    an extremely efficient and robust tool to find the optimal location.

publication date

  • May 2010