OPTIMASI ALOKASI LAJU INJEKSI WATERFLOOD MENGGUNAKAN PARAMETER DYNAMIC LORENZ COEFFICIENT DENGAN MATLAB RESERVOIR SIMULATION TOOLBOX

The use of waterflood which is less effective on heterogeneous porosity and permeability becomes a challenge for optimization. Optimization in regulating the injection rate allocation is chosen because it is very effective considering the lower price compared to drilling sequences and well placeme...

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Bibliographic Details
Main Author: Rizky Tsaury, Mohammad
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/53767
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:The use of waterflood which is less effective on heterogeneous porosity and permeability becomes a challenge for optimization. Optimization in regulating the injection rate allocation is chosen because it is very effective considering the lower price compared to drilling sequences and well placement. The injection rate allocation is carried out by considering the Dynamic Lorenz Coefficient value using flow diagnostics. Dynamic Lorenz Coefficient is used because it can measure the distribution of water injection in the reservoir with very fast optimization times using the open-source simulator MRST (MATLAB Reservoir Simulation Toolbox). This study results in optimization by reducing the Dynamic Lorenz Coefficient value on the injection rate control for each injector well can increase the sweep efficiency. Change in size of grid is not very sensitive to changes in the Dynamic Lorenz Coefficient value. The magnitude of injection rate after optimization of the reservoir with the normal distribution of porosity and permeability is directly proportional to its magnitude of pore volume. Conversely, in a reservoir with a permeable streak, the magnitude of the injection rate is proportionally inverse by the magnitude of permeability. Optimization of injection rate allocation by reducing the Dynamic Lorenz Coefficient value is proven to be effective because it can increase oil recovery from increasing in cumulative oil production using the initials scenario and the after-optimization scenario. These results have been validated in the simulator commercial CMG.