The Microemulsion phase behavior model based on oleic-aqueous-surfactant pseudo-phase equilibrium, commonly used in chemical flooding simulators, is coupled to Gas-Oil-Water phase equilibrium in our new four-fluid-phase, fully implicit In-House Research Reservoir Simulator (IHRRS). The method consists in splitting the equilibrium in two stages, where all the components other than surfactant are equilibrated first (e.g. using a black-oil, K-value or equation of state model), and the resulting Gas, Oil and Water phases are then lumped into pseudo-phases to be equilibrated using the Microemulsion model. This subdivision in stages is conceptual, and at each converged time-step the four phases (Gas, Oil, Water and Microemulsion, when simultaneously present) will be in equilibrium with each other.The fluid properties (such as densities, viscosities and interfacial tensions) and rock-fluid properties (such as relative permeabilities), required in the transport equations, are evaluated with models from well-known industrial or academic simulators. Surfactant flooding being usually implemented as a tertiary recovery mechanism, on fields for which complete models that we do not wish to modify already exist, particular care is devoted to ensuring continuity of the physics at the onset of surfactant injection.Our code is validated against a reference academic chemical flooding simulator, on 1D corefloods where the original hydrocarbons in place form a dead-Oil phase, possibly with free dry-Gas. Some numerical aspects of our implementation such as numerical dispersion versus time-step size and nonlinear convergence performance are also discussed. As an application example of our code where it is necessary to account for four phases in equilibrium, we consider a scenario where the chemical flood is preceded by a vaporizing Gas drive.
Numerical modeling of advanced recovery mechanisms at the reservoir scale (e.g. miscible or immiscible Gas 1 flood, chemical flood, steam injection…), typically implemented in a tertiary phase, is essential to reasonably estimate their potential benefit and to rank the various field development options. In this perspective, using a unique advanced-physics simulator for the entire life of an asset is a desirable objective, because in addition to saving engineering time spent in data conversion, it ensures continuity of the models at all times. In our view such a tool, expected to be flexible and allow reactivity for testing new models, should come as a complement to optimized and robust industrial-grade simulators used for prediction and history matching during primary and secondary recovery.In this paper we present the prototyping framework implemented in our In-House Research Reservoir Simulator (IHRRS), enabling easy integration of new physics for improved recovery processes with the well-known Black-Oil and Kvalue or Equation of State compositional models. As a demonstration example, we choose Surfactant-Polymer (SP) flooding, possibly requiring an additional Microemulsion phase. The framework is based on a natural variables formulation, solving a coupled system of conservation equations for the hydrocarbon and aqueous components (and optionally for the energy), simultaneously with a set of local thermodynamic constraints. These constraints enforce the equilibrium of hydrocarbon and aqueous components across the different fluid phases, including the equilibrium of Water and Oil with Microemulsion.To ensure compatibility between the different recovery mechanisms handled by our system, as well as to facilitate their development and benchmarking, special attention has been paid to developing physical options as plug-in functionalities. For this purpose, instead of relying on complex software engineering tools we prefer the approach of using low-level interfaces to communicate between the core and the modules (such as the fluid, the petrophysical, or the surface facility modules). Most of our modules are entirely independent from each other, and can be compiled as stand-alone programs to be called by MATLAB® or Python scripts for instance; symmetrically, they could be replaced by external software in order to test third party functionalities.As a first benchmark of our IHRRS, we consider a surfactant-polymer flood scenario in a 2D anisotropic quarter five-spot setting, and compare our solutions against those of a reference academic chemical flooding simulator (UTCHEM). The potentialities of our framework will then be demonstrated on a simplified model of a real Middle-Eastern field.
Summary The Microemulsion phase behavior model based on oleic/aqueous/surfactant pseudophase equilibrium, commonly used in chemical-flooding simulators, is coupled to Gas/Oil/Water phase equilibrium in our new four-fluid-phase, fully implicit in-house research reservoir simulator (IHRRS) (Moncorgé et al. 2012). The method consists of splitting the equilibrium into two stages, in which all the components other than surfactant are equilibrated first—by use of a black-oil, K-value, or equation of state (EOS) model—and the resulting Gas, Oil, and Water phases are then lumped into pseudophases to be equilibrated by use of the Microemulsion model. This subdivision in stages is conceptual, and at each converged timestep the four phases (Gas, Oil, Water, and Microemulsion, when simultaneously present) will be in equilibrium with each other. The fluid properties (such as densities, viscosities, and interfacial tensions) and rock/fluid properties (such as relative permeabilities) required in the transport equations are evaluated with models from well-known industrial or academic simulators. Surfactant flooding being usually implemented as a tertiary recovery mechanism, on fields for which complete models that we do not wish to modify already exist, particular care is devoted to ensuring continuity of the physics at the onset of surfactant injection. Our code is first validated against a reference academic chemical-flooding simulator, on a 1D, three-fluid-phase (Oil/Water/Microemulsion) coreflood. Second, as application examples where it is necessary to account for four phases in equilibrium, we consider a scenario where the chemical flood is preceded by a vaporizing Gas drive, as well as a scenario where dissolved gas is released by the Oil during the flooding process. Some aspects of our implementation, such as numerical dispersion vs. timestep length and nonlinear convergence, are also discussed; in particular, we show that numerical performance is not degraded by the four-phase equilibrium.
The dynamic effect of pressure and Oil composition on Microemulsion phase behavior, complementing the key effect of variable salinity, has been implemented in our four-fluid-phase, fully implicit in-house research reservoir simulator. This has been achieved through self-consistent coupling of a traditional Gas/Oil/Water phase equilibrium model, either compositional or generalized black-oil,-providing phase fractions, oleic composition, and aqueous salinity-with a Microemulsion model based on oleic/aqueous/chemical pseudophase equilibrium.As an application example and validation test case, we consider a hypothetical surfactant/polymer (SP) coreflood of a saturated Oil, interrupted by a progressive depressurization, during which dissolved gas is released, which shifts the Microemulsion phase state from Winsor Type III to Type II -. This proves the good functioning of our new option, and shows, yet on a simple case, that it does not degrade numerical performance, despite the introduction of additional nonlinear dependencies.
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