Estimation Of Fluid Properties Research Articles

A screening model for predicting injection well pressure buildup and plume extent in CO2 geologic storage projects

We present a new screening model for predicting injection well pressure buildup and CO2 plume migration for CO2 geologic sequestration projects. The model requires only limited information and is quite accurate when compared to detailed simulation results. Such models can assist project developers during the early days of project planning (e.g., for 45Q related projects), and also help regulators perform simple checks against detailed numerical models. The screening model consists of two correlations: one for injectivity index in terms of the slope of the CO2 fractional flow curve, and the second for total storage efficiency within the footprint of plume as a function of gravity number and slope of the CO2 fractional flow curve. Using these two correlations, as well as a knowledge of some basic reservoir characteristics and estimates of fluid properties from standard correlations, the injection-well pressure buildup and CO2 plume extent in the formation can be readily estimated. The new correlations show a good match with the results of the underlying simulations, and also provide good agreement with independent calculations for two example problems.

C7+ Reservoir Fluid Characterisation: Modification of Lohrenz Splitting Correlation

Petroleum reservoir fluid is commonly classified as individual components of C1 – C6 and lumped-up component of C7+. C7+ are hydrocarbon components of C7-heptane and above, that is, heavy hydrocarbons that are minimal in natural gas. De-lumping or splitting of C7+ into individual components is vital for accurate and efficient estimation of fluid properties. A number of correlations exist in literature and pressure-volume-temperature software for this. The least accurate and simple model by Lohrenz, Bray & Clark (1984) was modified in this work. Efficiency of the new model is highly comparable with existing models in the rigorous PVT systems for computing intensive and extensive natural gas properties.

Linking fluid composition to black-oil properties

Field development studies require, among many other things, reliable estimates of fluid properties. In cases where experimental data is unavailable or incomplete, it is necessary to predict fluid properties using correlations, based on input variables such as temperature, API, saturation pressure, gas gravity, and flash GOR. However, there are situations when even these input variables are not known, and where the only information is the initial reservoir fluid composition.The scope of the present work is to develop a predictive method which links the reservoir fluid composition to the input variables needed for the black-oil property correlations. The method is based on analysis of several experimental data sets comprising in total several hundred fluid compositions with associated black-oil properties as well as on isothermal flash calculations on 500,000 synthetic, but realistic, fluid compositions spanning a large range in compositional space. The aim of this work is therefore not to develop new correlations for oil compressibility, formation volume factors, viscosities etc. Rather, the contribution should be regarded as a novel way to incorporate reservoir fluid compositional information into an already existing framework for predicting fluid properties used for field development studies.Results from the study show that it is possible to predict API, flash gas gravity, flash GOR and saturation pressure with reasonable accuracy for a large range of reservoir fluid compositions as long as the molecular weight of the plus fraction is known. The work sheds more light on the quantitative influence of individual component mole fractions on fluid properties.

Model-Based Estimation of Flow Characteristics Using an Ionic Polymer–Metal Composite Beam

An ionic polymer-metal composite (IPMC) beam is capable of producing an electric signal closely correlated with its mechanical movement, due to the redistribution of mobile ions inside the IPMC material. Motivated by the potential application of this intrinsic sensing characteristic to flow property measurements in automotive engines, this paper investigates the feasibility of detecting the start and end of a pulsating flow and its fluid characteristics using an IPMC-beam-based sensor. A dynamic model is developed for the IPMC beam under the flow. The model consists of multiple rigid elements connected by rotational springs and, under suitable conditions, has a closed-form solution that enables efficient estimation of fluid properties and flow parameters with the least-squares minimization approach. The proposed fluid estimation scheme is validated using experimental results with different fluid media, and it is found that the estimated fluid drag coefficients (highly correlated with fluid viscosity) have good agreement with their actual values. This is very important for automotive applications where the characteristics of the fuel blend (such as gasoline and ethanol) need to be identified in real time.

Was leistet die statistische Thermodynamik für den Verfahrens‐Ingenieur?

AbstractWhat does statistical thermodynamics do for the chemical engineer? Statistical thermodynamics introduces molecular properties of a particular system into model equations for the thermodynamic functions of fluid mixtures. It thus contributes to the prediction, extrapolation or estimation of fluid properties, in particular phase and reaction equilibria, which are fundamental to numerous processes in thermochemical engineering. For systems of small, rigid molecules, as frequently encountered in natural gas and refrigeration applications, this method has reached a high level that is beginning to be introduced into industrial practice. For systems of complicated organic molecules, models from molecular thermodynamics have firmly established themselves in industrial applications.

Analysis of Vertical Two-phase Flow Calculations: Crude Oil-gas Flow In Well Tubing

Abstract Pressure drops in oil-well tubing, calculated by five well-known models are compared with actual field data covering a wide range of conditions. A detailed explanation is provided for the observed result that significantly higher accuracy is generally obtained when calculations are based on known bottom-hole conditions rather than known wellhead conditions. It is demonstrated that greater accuracy may be obtained by using measured bubble-point data than by using calculated values. The results of this study suggest that either the Aziz, Govier and Fogarasi or the Orkiszewski model should generally be used in preference to other methods for calculating pressure drops in oil-well tubing. Introduction A reliable estimate of the pressure drop in well tubing is essential for the solution of a number of important production engineering and reservoir analysis problems. For example, inflow performance calculations require a knowledge of pressure drop in the producing string as a function of flow rate. Many different models and correlations have appeared in the literature for this purpose. In addition, there are a number of correlations available for estimating the fluid properties required for these calculations when experimental data are not available. In recent years, computer programs containing many of these models and fluid property correlations have been developed and are readily available to the engineer. Unfortunately, however, the choice of the appropriate method for a particular problem is seldom obvious. Thus, some guidelines are required to help resolve the following questions:Which multiphase flow calculation method is the most reliable for a given system?What influence would errors in the estimation of fluid properties have on the pressure-drop calculations? In this paper, we attempt to answer these two questions for typical oil wells, where gas-oil flow occurs over at least part of the producing string. The resolution of the same two questions for gas-condensate wells requires a somewhat different treatment, and will be considered in a separate paper. Effect of Calculation Direction The total pressure drop over a differential length of the tubing may be separated into three components: (Equation Available In Full Paper) The first term,, is the contribution to the total pressure change due to the hydrostatic-head effects. It is proportional to the density of the fluid mixture inside the pipe under flowing conditions (in-situ density). The second term, aPr, includes all frictional effects, and it is proportional, among other factors, to the fluid velocity and viscosity. Finally, the third term, ΔPKE, results from velocity changes (acceleration) caused by the expansion of the fluid with decreasing pressure. In oil wells, the fluid properties are such that the proper engineering design usually requires that the flow pattern be bubble or slug (see reference 1 for a description of various flow patterns). In some situations, the gas/oil ratio (GOR) may be high enough to cause froth flow, but this situation is more common in condensate wells.