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Abstract Modern reservoir engineering practices require accurate information on thermodynamic and transport fluid properties together with reservoir rock properties to perform material balance calculations. These calculations lead to the estimation if initial hydrocarbons, the future reservoir performance, optimum production schemes and ultimate hydrocarbon recovery. These fluid properties which are usually determined by laboratory experiments or using empirically derived correlations provide the information required to properly understand the phase behavior, evaluate various production scenarios, optimize reservoir production and IOR schemes, and to maximize ultimate recovery and optimize production economics. One of these properties is the petroleum reservoir fluid viscosity. Crude oil viscosity is an important physical property that controls and influences the flow of oil through porous media and pipes. This paper introduces a new implementation of the genetic algorithms technology in petroleum engineering. Intelligent techniques such as genetic algorithms for data analysis and interpretation are an increasingly powerful and reliable tool for making breakthroughs in the science and engineering. The introduced model in this paper can predict the reservoir fluid viscosity data with genetic algorithms technique. Prediction results of the proposed model have been tested against the measured reservoir fluid viscosity data. Results indicate that the proposed prediction model can successfully predict and model reservoir fluid viscosity. Introduction Modern reservoir engineering practices require accurate information on thermodynamic and transport fluid properties together with reservoir rock properties to perform material balance calculations. These calculations lead to the determination (estimation) of the initial hydrocarbons in place, the future reservoir performance, optimal exploration and production schemes, and the ultimate hydrocarbon recovery. Reservoir simulators are routinely used to predict and optimize oil recovery from different fields. These softwares require input properties of the reservoir fluids as a function of pressure, temperature and composition and the accuracy of these input parameters can affect the results of the simulation. One of these parameters is the petroleum reservoir fluid viscosity. Crude oil viscosity is an important physical property that controls and influences the flow of oil through porous media and pipes. The viscosity, in general, is defined as the internal resistance of the fluid to flow. The oil viscosity is a strong function of the temperature, pressure, oil gravity, gas gravity and gas solubility. Whenever possible, oil viscosity should be determined by laboratory measurements at reservoir temperature and pressure. The viscosity is usually reported in standard PVT analyses. If such laboratory data are not available, engineers may refer to published correlations, which usually vary in complexity and accuracy depending upon the available data on the crude oil. The viscosity of crude oils is a critical property in predicting oil recovery. Viscosity reduction and thermal expansion are the key properties to increase productivity of heavy oils. Reservoir simulators are routinely used to predict and optimize oil recovery from oil fields. These simulators require as input properties of the reservoir fluids as a function of pressure, temperature and composition. The accuracy of the fluid properties can decisively affect the results of the simulation. Among the required fluid properties are phase densities, phase viscosities, formation volume factors and dissolved gas-oil ratios. The physicochemical properties of the reservoir fluids are a function of the fluids' composition. These compositions can be determined by experimental analysis such as, true boiling point essays and gas chromatography. In many practical cases no compositional information is present. A practical method to predict reservoir fluids' viscosities should be able to calculate viscosity of compositional and black oils. Numerous viscosity-correlation methods have been proposed. None, however, has been used as a standard method in the oil industry. Since the crude oil composition is complex and often undefined, many viscosity estimation methods are geographically dependent. Most correlation methods can be categorized either a black oil or as compositional.
- Geology > Geological Subdiscipline (1.00)
- Geology > Petroleum Play Type > Unconventional Play > Heavy Oil Play (0.54)
- Reservoir Description and Dynamics > Reservoir Simulation (1.00)
- Reservoir Description and Dynamics > Fluid Characterization > Phase behavior and PVT measurements (1.00)
- Reservoir Description and Dynamics > Fluid Characterization > Fluid modeling, equations of state (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)
Abstract Successful design and implementation of a miscible gas injection project depends upon the minimum miscibility pressure (MMP) and other factors such as reservoir and fluid characterization. The experimental methods available for determining MMP are both costly and time consuming. Therefore, the use of correlations that prove to be reliable for a wide range of fluid types would likely be considered acceptable for preliminary screening studies. This work includes a comparative evaluation of MMP correlations and thermodynamic models using an equation of state by PVTsim 1 software. We observed that none of the evaluated MMP correlations studied in this investigation is sufficiently reliable. EOS-based analytical methods seemed to be more conservative in predicting MMP values. Following an acceptable estimate of MMP, several compositional simulation runs were conducted to determine the sensitivity of the oil recovery to variations in injection pressure (at pressures above, equal to and below the estimated MMP), stratification and mobility ratio parameters in miscible and immiscible gas injection projects. Simulation results indicated that injection pressure was a key parameter that affects oil recovery to a high degree. MMP determined to be the optimum injection pressure. Stratification and mobility ratio could also affect the recovery efficiency of the reservoir in a variety of ways. Introduction Through the past decades, miscible displacement processes have been developed as a successful oil recovery method in many reservoirs. The successful design and implementation of a gas injection project depends on the favorable fluid and rock properties. The case studies using Eclipse 2 compositional simulator considered the effect of key parameters, such as injection pressure, stratification and mobility ratio on the performance recovery in miscible and immiscible flooding of the reservoir. However, accurate estimation of the minimum miscibility pressure is important in conducting numerous simulation runs. MMP is the minimum miscibility pressure which defines whether the displacement mechanism in the reservoir is miscible or immiscible. Thermodynamic models using an equation of state and appropriate MMP correlations were used in determining the MMP. Compositional simulation runs determined the sensitivity of the oil recovery to the variations in above mentioned parameters. Significant increase in oil recovery was observed when interfacial tension dependent relative permeability curves were used. These relative permeability curves provide an additional accounting for miscibility by using a weighted average between fully miscible and immiscible relative permeability curves. The local interfacial tension determines the interpolation factor which is used in obtaining a weighted average of immiscible and miscible (straight line) relative permeabilities. Simulation runs were performed at pressures below, equal to, and greater than estimated MMP for reservoir fluid/ injection gas system. Oil recovery was greatest when miscibility achieved. To investigate the effect of stratification on the performance recovery of the reservoir, the base relative permeability of two layers changed. Location of the high permeable layer (up or bottom layer) in the stratified reservoir greatly influenced the efficiency of the reservoir. Understanding the effect of interfacial tension and adverse mobility ratio on the efficiency of the gas injection project was the last case study. Injection gas and reservoir fluid compositions differed in such a way to have interfacial tension and mobility dominated mechanism. To investigate the effect of interfacial tension water was considered as a fluid with much higher surface tension values with the oil. Lower surface tension values between rich gas and reservoir fluid (interfacial tension dominated) made gas injection project a more competitive recovery method than waterflooding. In mobility dominated displacement mechanism (lean gas/reservoir fluid system) the viscous instabilities were more important than the interfacial tension effect. For this case, waterflooding with favorable mobility ratio resulted in higher oil recoveries.
- Africa > Middle East > Libya > Wadi al Hayat District > Murzuq Basin > Block NC 186 > I&R Fields > R Field > Mamouniyat Formation (0.99)
- Africa > Middle East > Libya > Wadi al Hayat District > Murzuq Basin > Block NC 115 > I&R Fields > R Field > Mamouniyat Formation (0.99)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Gas-injection methods (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
- Reservoir Description and Dynamics > Fluid Characterization > Fluid modeling, equations of state (1.00)