In the same way that laboratory measurements require representative samples to be meaningful, reservoir fluid samples themselves must be supported by accurate data to provide a unique identification and to record all important production and sampling parameters that will be used in checking the sample and (in many cases) in determining the exact measurements that will be performed. This article reviews the importance of data measurement and provides guidelines for recording and validating the necessary data. Provided that flowmeters and pressure gauges are properly sized for a measurement, so that readings are not made at the low end of the measurement range, random errors are generally small. Although systematic errors are comparatively rare, their magnitude can be significant. In fact, on some occasions, errors are identified only when measured values are so large that the values become ridiculous.
An equation of state (EOS) is a simplified mathematical model that calculates thermodynamic properties and the equilibrium state. To develop the EOS, we need equations that relate thermodynamic quantities in terms of pressure, molar volume, and temperature data (PVT data), and we want to eliminate any path dependence by eliminating all properties that are not state functions. Substitution of Eq. 2 into Eq. 1 by elimination of dQ (a path dependent quantity) and selection of a reversible path (such that dSG 0) gives All of the properties in Eq. 3 are state functions; thus, Eq. 3 is independent of the path or process. After combining like terms, Eq. 3 becomes For a closed system (dn 0), Eq. 4 becomes Eqs. 4 and 5 are examples of fundamental property relations. Other fundamental property relations are possible.
The motivation for high-performance computing in reservoir simulation has always existed. From the earliest simulation models, computing resources have been severely taxed simply because the level of complexity desired by the engineer almost always exceeded the speed and memory of the hardware. The high-speed vector processors such as the Cray of the late 1970s and early 1980s led to orders-of-magnitude improvement in speed of computation and led to production models of several hundred thousand cells. The relief brought by these models, unfortunately, was short-lived. The desire for increased physics of compositional modeling and the introduction of geostatistically/structurally based geological models led to increases in computational complexity even beyond the large-scale models of the vector processors.
Enhanced oil recovery (EOR) is the technique or process where the physicochemical (physical and chemical) properties of the rock are changed to enhance the recovery of hydrocarbon. The properties of the reservoir fluid system which are affected by EOR process are chemical, biochemical, density, miscibility, interfacial tension (IFT)/surface tension (ST), viscosity and thermal. EOR often is called tertiary recovery if it is performed after waterflooding. Conformance is the application of processes to reservoirs and boreholes to reduce water production, enhance recovery efficiency, or satisfy a broad range of reservoir management and environmental objectives. Although the use of conformance processes may not result in increased production, such processes can often improve an operator's profitability as a result of the following benefits: Ideally, conformance control should be performed before a condition can result in serious damage.
Phase behavior calculations require that all components and their properties be specified. Crude oils, however, typically have hundreds of components, making the equation of state (EOS) procedure for the phase behavior of mixtures computationally intensive. Thus, components are often lumped into pseudocomponents to approximate the in-situ fluid characterization. The selection of pseudocomponents and their property values are likely not unique, as is often the case when numerous model parameters are estimated by fitting measured data with nonlinear regression. Care should be taken to avoid estimates in the pseudocomponent properties that are unphysical and to reduce the number of parameters.
Thermodynamic models for wax precipitation describes a number of models to calculate the amount of solid wax precipitated as a function of pressure, temperature, and fluid composition. Wax precipitation does not necessarily lead to solid deposition. The form of these models is discussed briefly in this section. For deposition to occur in pipelines, the following conditions must be fulfilled. Burger et al. investigated the significant physical processes leading to wax deposition in pipelines.
In a dynamic calculation, there are two effects not considered in steady flow: fluid inertia and fluid accumulation. In steady-state mass conservation, flow of fluid into a volume was matched by an equivalent flow out of the volume. In the dynamic calculation, there may not be equal inflow and outflow, but fluid may accumulate within the volume. For fluid accumulation to occur, either the fluid must compress, or the wellbore must expand. When considering the momentum equation, the fluid at rest must be accelerated to its final flow rate.