Viscosity Correlations for Saudi Arabian Crude Oils

Abstract

Empirical equations for estimating viscosity: above, at, and below the bubble point pressure were developed based on data from Saudi Arabian crude oils. Both statistical and graphical techniques have been employed to evaluate these equations as compared to other published crude oil viscosity correlations using the same data. It is shown that the developed correlations provide more accurate estimates of viscosity in all three regimes of pressure. Introduction Viscosity is the measure of resistance to fluid flow. Knowledge of viscosity is required in reservoir simulation, fluid flow through porous media and pipelines, well testing, and design of production pipelines, well testing, and design of production equipment. Crude oil viscosity can be classified into three regimes. Bubble Point Oil Viscosity It is the viscosity of crude oil at the bubble point pressure and a given temperature. point pressure and a given temperature. Oil Viscosity Above the Bubble Point It is defined as the crude oil viscosity at a pressure higher than the bubble point pressure and a pressure higher than the bubble point pressure and a given temperature. Oil Viscosity Below the Bubble Point It is the viscosity of crude oil below the bubble point pressure and a given temperature. With the point pressure and a given temperature. With the lowering of pressure below the bubble point pressure, gas is released leaving behind a saturated oil at the new pressure. When the pressure is lowered to atmospheric pressure, there is no dissolved gas left in the oil and such oil is called dead oil whose viscosity is referred to as the dead oil viscosity. In many cases, the only information available from PVT analysis of an oil sample are simple and readily PVT analysis of an oil sample are simple and readily measurable parameters such as gas relative density, oil API gravity, and gas-oil ratio. Direct viscosity measurements or complete compositional analyses of crude oils are expensive, therefore, empirical correlations, which are functions of these readily measurable PVT properties, are used to estimate oil viscosity. A number of different viscosity correlations have been presented in the literature, as shown in Table 1, and reviewed in detail by Khan. Most of these correlations were based on limited data from different geographical locations which introduced large potential errors. Moreover, these correlations involve complex mathematical expressions which do not explain the behavior of oil viscosity very clearly. In this study, an alternative approach to viscosity correlation development, along with new viscosity equations have been derived. In this approach, emphasis is placed on the natural variation of viscosity with PVT parameters. In this paper, the new correlations and four of the published correlations, namely those of Beal, Chew and Connally, Beggs and Robinson, and Vazquez, will be evaluated using Saudi Arabian crude oil viscosity data which was used to develop the new correlations. VISCOSITY DATA This study utilized viscosity data for 75 bottom hole samples taken from 62 Saudi Arabian oil reservoirs. P. 251

PVT correlations for Pakistani crude oils using artificial neural network

“…These are those of Beggs and Robinson (1975), Chew and Connaly (1959), Khan et al (1987), andLabedi (1992). The statistical results of the comparison are given in Table 8.…”

Experimental and Theoretical Determination of Heavy Oil Viscosity Under Reservoir Conditions

“…These models do not assume the knowledge of the dead-oil viscosity. Khan et al 74 proposed a correlation for the bubble point viscosity, while Petrosky 76 proposed a correlation for the dead-oil viscosity. The experimental ranges of pressure, oil gravity, temperature, and solution-gas/oil ratios are similar to those of our databases.…”

“…The predictions were compared with those predicted from the correlations of Khan et al 74 and of Petrosky 76 that are applicable to the experimental conditions of our data sets.…”

Evaluation of crude oil property using intelligence tool: fuzzy model approach

“…These correlations are Beal [2], Vazquez and Beggs [6], Khan Correlation [13] and Kartoatmodjo and Schmidt [8] .These correlations are shown in Table 2.…”