Geological sequestration of carbon dioxide through enhanced oil recovery operation has been recognized as one of the more viable means of reducing emissions of anthropogenic CO2 into the atmosphere. The objective of this paper is to find the best EOR scenario for a compositional grading Iranian oil reservoir to be fed by a giant power plant which produces huge amount of CO2 emission, through simulation study. For this purpose a three-dimensional simplified yet realistic model of the reservoir considering compositional grading was built based on long term production data. Various simulation cases to combine different injection schemes and examining the effect of injection rate were conducted to propose an injection-production strategy that can optimize the oil recovery along with CO2 storage. This study is the first attempt to investigate technical and economic aspects of simultaneous CO2-EOR and sequestration for the nominated reservoir. Besides, this approach could be used for any gas cycling and natural gas storage process into this reservoir.
The results presented in the study clearly demonstrated that continuous CO2 injection scheme through one injection and one production well, is the best scenario for simultaneous EOR and sequestration/gas storage which lead to higher CO2 storage and oil recovery efficiency. Through continuous CO2 injection, this reservoir has potential for large scale CO2-EOR and storage projects (injection of more than 240 thousand metric tons of CO2 per year with only one injection well without any field development plan). Finally an economic study is performed to confirm the best scenario.
In compositional simulation of oil and gas reservoirs, equation-of-state (EOS) methods are seeing increasing usage for phase equilibrium calculations. EOS compositional reservoir simulation is an accurate and powerful means to model complicated phase and flow behavior when the displacement process depends on pressure and fluid composition. Many field development projects have strong composition dependence, such as miscible gas injection for oil reservoirs or liquid recovery under lean gas injection for condensate reservoirs or water-alternating-gas injection.
This paper presents characterization of some crude oil samples from an Iranian reservoir using the Peng-Robinson Equation of State (PR-EOS) to arrive at one EOS model that accurately describes the PVT behavior of crude oil produced from the different wells in the reservoir. The multi-sample characterization method is used to arrive at one consistent model for crude oil for the whole reservoir.
However, uncertainties still exist that are associated with the use of an EOS to model petroleum reservoir fluids because of the complicated nature of such fluids and limitations of the most commonly used EOS's. Tuning the adjustable EOS parameters to match experimental fluid PVT data is a common practice. The tuning procedure for the EOS is done systematically by matching the volumetric and phase behavior results with laboratory results. Also, a consistent C7+ pseudo component split using the Whitson splitting method is used for all samples to arrive at a consistent model for crude oil for the whole reservoir.
Results showed a good agreement between model predictions and laboratory data. Also the results demonstrate that multisample method has high ability to provide one EOS model for the crude oil using PVT test results from different wells. The EOS model developed for this particular field may be used in reservoir simulation studies to optimize hydrocarbon recovery.
Asphaltenes precipitation is one of the major operational problems affecting oil production in the Bangestan reservoir in south of Iranian fields. Precipitation of asphaltenes in reservoirs, wells and production facilities can have severe detrimental impact on the economics of oil production because of a reduction of well productivity and/ or clogging of production facilities. A field methodology based in the influence of pressure in asphaltenes precipitation has been designed and implemented to estimate the zone of maximum probability of asphaltenes precipitation. Nodal analysis is applied to determine pressure versus depth behavior at the well for different operational conditions. Knowing the saturation pressure and the flocculation onset pressure, the methodology allows the determination of the most probable range of depth at which asphaltenes precipitation will occur. The purpose of this methodology is determine the optimum operational conditions that maximize production at minimum risk of asphaltenes precipitation, as well as to select the better preventive measure for each particular case, thus maintaining overall control of the asphaltenes plugging problem. In this paper, field applications of the methodology are shown. Depending on the depth range of asphaltenes precipitation occurrence, reperforation of the producing interval, hydraulic fracture is recommended.