Type of Document Dissertation Author Al-Mudhafar, Watheq Jasim Mohammed Author's Email Address email@example.com URN etd-04072016-165145 Title Statistical Reservoir Characterization, Simulation, and Optimization Of Field Scale-Gas Assisted Gravity Drainage (GAGD) Process with Uncertainty Assessments Degree Doctor of Philosophy (Ph.D.) Department Petroleum Engineering Advisory Committee
Advisor Name Title Rao, Dandina Committee Chair Dutrow, Barbara Committee Member Marx, Brian Committee Member Sears, Stephen Committee Member Srinivasan, Sanjay Committee Member Tyagi, Mayank Committee Member D'Sa, Eurico Dean's Representative Keywords
- Geostatistical Reservoir Characterization
- Field-Scale Reservoir Simulation
- Oil Recovery Optimization
- Bayesian Statistics
- Uncertainty Quantification
- Gas Assisted Gravity Drainage Process
Date of Defense 2016-02-15 Availability unrestricted AbstractUnlike the Continuous Gas Injection (CGI) and Water-Alternative Gas (WAG), the Gas Assisted Gravity Drainage (GAGD) process takes advantage of the natural segregation of reservoir fluids to provide gravity-stable oil displacement. The gas is injected through existing vertical wells to formulate a gas cap to allow oil and water drain down to the horizontal producer (s). Therefore, the GAGD process was implemented through immiscible and miscible injection modes to improve oil recovery in a sector of the main pay/upper sandstone member in the South Rumaila oil field, located in Iraq.
A high-resolution geostatistical reservoir characterization model was constructed to model the lithofacies and petrophysical properties in order to provide the most realistic geological environment for the GAGD process evaluation. After upscaling the geostatistical model, a compositional reservoir simulation was built to evaluate the GAGD process and test its effectiveness to improve oil recovery.
Next, sensitivity analysis was performed to determine the most influential reservoir parameters that impact the GAGD process. With no effect of reservoir porosity, it was also investigated that reservoir permeability and anisotropy ratio have the most impact on the reservoir flow response through the GAGD process.
Then, several GAGD optimization and uncertainty assessment approaches were conducted to determine the optimal future reservoir scenario of the largest improvement in oil recovery. These optimal cases include operational decision parameters, injection pressure, and cycling injection. It was concluded that the cycling GAGD process has better performance to improve oil recovery than the continuous injection mode. In addition, all the successive approaches of the optimization and uncertainty assessments led to in- crease oil production by more than 500 million barrels over the base-case GAGD process of default operational decision parameters. Finally, both heterogeneity and anisotropy effects have been identified by showing a significant impact on the reservoir flow responses. Specifically, the effect of permeability anisotropy is higher than reservoir heterogeneity be cause the main concept of the GAGD process considers vertical fluid movements towards the horizontal producers.
Consequently, the overall reservoir characterization, compositional simulation, and optimization of the immiscible GAGD process have shown its effectiveness to improve oil recovery in a real field-scale evaluation.
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