International Petroleum Technology Conference · 2015 · 12 citations · 2 references
ArchitecturePetroleum EngineeringDesign OptimizationOptimizationReservoir EngineeringCombinatorial OptimizationGenetic AlgorithmsPipeline SystemsProduction OptimizationTopology OptimizationConvergence CriteriaEnergy ConsumptionGenetic Algorithm Based DesignGenetic Algorithm OptimizationGenetic Algorithm Variable SelectionHash Table ImplementationsPipe Network TopologyPipeline Network Design
Abstract Coalbed methane has attracting much attention as a kind of the new energy source, with ever increasing demand in energy consumption. Pipeline networks of CBM fields are characterized by their complex topological structures and high investment costs. Therefore, the optimization of the pipeline network topology structure will be very helpful in lowering the production costs. The paper discusses four main structures: (1) the well gathering connection, (2) the nearby insertion connection,(3) the valve gathering connection and (4) the combination of well gathering and valve gathering connection. The optimal models which aim at minimizing total investment are solved by genetic algorithm with hybrid encoding by Hash table. The models have taken factors such as flow rate balance at nodes, constraints of the flow velocity, the minimum inlet pressure, maximum operating pressure, maximum number of wells connecting the valve block and the geographic condition into consideration. The paper comes up with a sort of regionally surviving convergence criterion which focuses on models that are strongly discontinuous and prone to be trapped in a local optimum. Taking 46 wells in a CBM field as an example, the paper works out the optimal topological connection for each structure. The result shows that the investment costs, calculated by the regionally surviving convergence criteria, are reduced by a maximum of 11.94% as compared to the traditional one. Also computing time is sharply saved. This study provides a guide line for reducing the cost of producing pipeline networks in CBM fields.
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