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The results from this research indicate that implication of GA LSSVM and GA FL in prediction can lead to more reliable porosity/permeability predictions, which can lead to the design of more efficient reservoir simulation schemes.
In the study of oil reservoirs, the prediction of absolute permeability is a fundamental key in reservoir descriptions and has a direct impact, in particular, on effective completion designs, successful water injection programs and more efficient reservoir management.
Thus, the flow of injected water diverts to unswept regions, leading to more efficient reservoir sweep and higher recovery factor (Thomas and Ali 1989; Seright and Liang 1995; Babadagli 2005).
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The injection flow rate is found to be more efficient, concerning reservoir productivity, than the other two parameters.
Understanding the extent to which theses parameters might affect the SWCT test profiles could help us to manage and design the SWCT test more efficient at different reservoir conditions.
Inflow control devices have been used to delay water or gas breakthrough, making possible a more efficient drainage of the reservoir while maximizing recovery.
However, these nanoparticles are more efficient in light oil reservoirs [11].
In this study, we established a more efficient approach for fractured shale reservoir modeling with an emphasis on simplifying and automating the workflow for assisted history matching and uncertainty quantification.
These studies are logistically complicated and expensive, so more efficient methods of determining the reservoir of infection are required in order to target interventions optimally.
Thus, it is concluded that the application of CWI to virgin light oil reservoirs, i.e., secondary CWI, is more efficient compared to CWI applied to the reservoir after WF, i.e., tertiary CWI.
The presented model can be used to interpret pressure data more accurately for shale gas reservoirs and provide more accurate dynamic parameters which are important for efficient reservoir development.
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