Novel empirical correlations for estimation of bubble point pressure,saturated viscosity and gas solubility of crude oils

Knowledge of petroleum fluid properties is crucial for the study of reservoirs and their development. Estimation of reserves in an oil reservoir or determination of its performance and economics requires a good knowledge of the fluid physical properties. Bubble point pressure, gas solubility and viscosity of oils are the most important parameters in use for petroleum and chemical engineers. In this study a simple-to-use, straight-forward mathematical model was correlated on a set of 94 crude oil data. Three correlations were achieved based on an exponential regression, which were different from conventional empirical correlations, and were evaluated against 12 laboratory data other than those used for the regression. It is concluded that the new exponential equation is of higher precision and accuracy than the conventional correlations and is a more convenient mathematical formulation.

The impact of salinity,alkalinity and nanoparticle concentration on zeta-potential of sand minerals and their implication on sand production

The effect of brine salinity,cation type,pH,and produced sand on zeta potential(ZP)measurements with and without the presence of silica nanoparticles is investigated through pH measurement,static tests for sand and ZP measurements as well as Field Emission Scanning Electron Microscope(FESEM)analyses.Three important factors were investigated:composition of the injected brine,surface charge and pH.Their influence on stability of nanoparticles in the injected brine and amount of sand segregation was determined and the analysis of the new outcomes based on rock/brine ZP measurements was reported.The results show that the use of silica nanoparticles with high pH helps in preventing sand production and that pH has a main effect on the surface charge of the sand particle released,affecting the ZP of the solution.Nanoparticles can be active as a coating on sand grains and prevent sand segregation during water flooding.Divalent cations have been found to acquire a more substantial impact on neutralizing the negative charge of the sand particles than monovalent cations at the same concentration and pH conditions at 25℃.The value of ZP becomes of higher negative value with the decrease of brine salinity.The effectiveness of SiO_(2)nanoparticles is quite different for soft water and smart water.For soft water,the nanoparticles work more effective at pH higher than 8;and for smart water,the nanoparticles perform better at pH lower than 8.To reduce sand production with the use of silica nanoparticles,it is highly suggested to increase pH,as pH and sand production mechanisms were observed to be inversely related.

A novel model for predicting the temperature profile in gas lift wells

One of the most common methods for calculating the production oil rate in a gas lift well is nodal analysis.This manner is an accurate one,but unfortunately it is very time consuming and slow.In some modern studies in petroleum engineering such as close loop control of the wells this slowness makes it impossible to have an online optimization.In fact,before the end of the optimization the input parameters have changed.Thus having a faster model is necessary specially in some of the new studies.One of the sources of slowness of the nodal analysis is the temperature profile estimation of the wells.There are two general approaches for temperature profile estimation,some like heat balance are accurate but slow.Others,similar to linear profile assumption are fast but inaccurate and usually are not used commonly.Here,as a new approach,a combination model of heat balance and linear temperature profile estimation has represented which makes the nodal analysis three times faster and it is as accurate as heat balance calculations.To create this,two points(gas injection point and end of tubing)are selected,then using heat balance equations the temperature of those two points are calculated.In normal nodal analysis the temperature of each wanted point in the well is estimated by heat balance and it is the source of slowness but here just two points are calculated using those complex equations.It seems that between these points assuming a linear temperature profile is reasonable because the parameters of the well and production such as physical tubing,and casing shape and properties and gas oil ratio are constants.But of course,it still has some deviation from the complete method of heat balance which using regression and assigning a coefficient to the model even this much of the deviation could be overcame.Finally,the model was tested in various wells and it was compared with the normal nodal analysis with complete heat balance models.Results showed that the new model is as accurate as normal heat balance but three times faster.