Microbial enhanced oil recovery (MEOR) is a biotechnology-based oil recovery method which involves the use of microorganisms and their metabolic products (metabolites) to enhance oil production from the screened mature oil reservoirs. One of the work packages of the technology project “MEOR studies” being conducted by Wintershall is the numerical predictions of the planned pilots and potential field applications. Field simulation model must be developed for launching the MEOR field pilot and plan next steps. Meanwhile, multi-well test (MWT) was planned to implement in the last part of this integrated project, and a tracer injection was designed and conducted to investigate the reservoir characterization and the connectivity between injection and production wells due to water breakthrough time. According to the old reservoir simulation model, the tracer predictions results could not match the actual tracer results in producers potentially due to the flow barriers and unpredicted heterogeneity. The issue revealed the necessity of seismic re-interpretation to improve the knowledge of the reservoir. The primary objective of this thesis is to reestablish the reservoir simulation model according to the revised seismic interpretation serving the acceptable reservoir description. This thesis work focuses mainly on manual history matching carried out on the full field model improved with new geologic interpretations. The implementation of this reservoir simulation model has encountered the inevitable challenges which are described in the context including data collection and data accuracy regarding the high number of wells in this field and nearby field; high uncertainty in production and injection data and surveillance data; reservoir simulator issue; QC of the exported data file form the static model, and the structural model uncertainty. After a global match succeeded, the utilization of assisted history matching which aids in accelerating the history matching process can provide an algorithmic framework to minimize the mismatch and improve the simulated results. Sensitivity analysis was carried out to determine the most critical dynamic parameters that affect the adjustment between the simulated model and the known performance of the field. The new reservoir model obtained with the preliminary history matching is used then for the improved predictions in MWT location of the ongoing project. A sector model representing the MWT location was created. The tracer operation was modelled, and the results were compared with the results of the previous model. The last focus of this thesis is on the sensitivity analysis of the tracer simulation to provide the realistic interpretation of inter-well connectivity and optimize the flood parameters in the proposed well-sidetrack.