Chemical EOR is one of the promising methods to improve the oil recovery. However, due to high cost of the process, there are challenges to minimize the cost and maximize the oil recovery. Some influencing parameters should be taken into account in a systematic approach to find their impact on oil recovery and accordingly optimizing the process.In this study, we present a robust optimization workflow of alkaline-surfactant (AS) flooding into a thin clastic reservoir of a field in the Malay Basin. There are coreflood experiments and pilot tests on this field that can be quite helpful to provide a basis to find out the appropriate range of input parameters. Optimization work is based on response surface methodology (RSM) and particle swarm optimization (PSO) technique that aid us to indicate the optimum oil recovery from chemical flooding. In order to get the utmost advantage of this workflow, the waterflooding should be optimized prior to the chemical flooding optimization to maximize the sweep efficiency and oil recovery from the chemical flood.Evaluation of coreflood and pilot tests indicated that some parameters need supplementary evaluation to investigate their effect on reservoir performance and flow dynamics. These parameters include residual oil reduction by chemical, relative permeability curves, chemicals adsorption, chemical concentration, slug size, injection rate, and initiation time of chemical injection. Based on the result of tornado chart, residual oil reduction and injection rate exhibited highest and lowest impact on oil recovery. RSM was used to explore the relationship between input variables and objective function. Some design parameters such as chemical concentration, slug size and initiation time were examined in this stage. Afterwards, proxy models have been built using polynomial regression and neural network methods. The results showed that the proxy model by neural network method revealed better performance for prediction of the simulation results. The proxy model was used to calculate the oil recovery for any combination of input parameters. Besides, it was used to assess the parameter sensitivity and identify the impact of any input parameter on oil recovery. At the next stage, PSO method was utilized to optimize the oil recovery by chemical flooding. It was found that the optimized water injection rate and pattern for water flooding scenario need further optimization to improve the sweep efficiency and thereby oil recovery by AS flooding at later stage. Running numerous simulation cases is normally expected to optimize the process by conventional methods and the proposed PSO approach can be used to reduce the number of runs significantly. Sensitivity analysis provided a very good understanding about reserve ranges for the different influential parameters. Optimizing the cost of chemical flooding and improving oil recovery are other outcomes of this study.
With the increasing demand in domestic energy requirement and with declining production rates from mature fields of offshore Malaysia, PETRONAS has embarked on an aggressive campaign to address the decline in rates as well as increase the reserves through proven Enhanced Oil Recovery (EOR) application. An immiscible Water Alternating Gas (WAG) process is found to be the most favorable EOR method due to gas supply availability, proven world-wide application, and promising results in improving injection fluid sweep efficiency and reducing residual oil saturation.
To reduce the uncertainty of EOR technical studies under low oil price, a comprehensive integrated procedure is required to study WAG performance and define key factors that impact flow efficiency under three-phase flow conditions for a more representative full-field reservoir simulation study results.
This procedure involves a detailed comprehensive parametric study of the cycle dependent hysteresis starting from extensive literature review, followed by laboratory experiments and extracting pertinent WAG parameters from coreflood history matching and finally applying these parameters in full-field reservoir simulation study. This study demonstrated that the WAG cycle dependency of relative permeability during WAG process is one of the key factors that has significant impact on WAG performance and recovery factor. This feature cannot be captured by conventional three-phase flow models used by reservoir simulators. The study indicates additional recovery factor of about 1%-2% compared to the base-case WAG model without WAG hysteresis.
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