New method for predictingn-tetradecane/bitumen mixture density: correlation development

Abstract

Nowadays, incredible growth of the energy consumption has changed the global attention to the production and utilization of the heavy crude oils such as bitumen resources around the globe. Amongst the bitumen properties, density is an important parameter which improves bitumen recovery efficiency and transportation quality. For easy production of bitumen, n-alkanes are usually injected into the reservoir to reduce its viscosity and density; however, there are few numbers of models focusing on proper estimation/prediction of diluted bitumen mixture density in literature. In present work, a new method was proposed to accurately prognosticate the bitumen/n-tetradecane mixture density as a function of thermodynamic conditions using Gene Expression Programming (GEP) for the first time as a function of solvent composition, pressure and temperature. Consequently, the proposed model here predicts the mixture density with the average Absolute Relative Deviation (AARD%) of 0.3016% and R-squared (R 2) of 0.9943. Moreover, it is found out the solvent concentration has the highest impact value on mixture density estimation. In conclusion, results of the present study can be so valuable for field engineers and researchers working on solvent-assisted recovery methods from heavy oil reservoirs.

Application of a new approach for modeling the oil field formation damage due to mineral scaling

“…A database with the feature of all-inclusiveness makes the constructed model to be applied for a wider ranges of operational conditions. In other words, the proposed model is not limited to a specific condition and can be employed for mathematical description of the interest phenomenon at different conditions [35,[44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62]. In present research, 431 datapoints of permeability reduction values as a function of temperature, differential pressure, volume of injected water, initial permeability, flowrate, and ionic concentrations of cationic species (i.e., strontium, calcium and barium) and anionic species (i.e., sulfate) is taken from the open literature (see Supplementary Material) [40][41][42][43].…”

“…Genetic based calculations have been commonly used in petroleum industry as a promising approach in estimating several parameters [34][35][36]. In recent years, Gene Expression Programming (GEP) [37] as an evolutionary algorithm, has been increasingly applied in different disciplines of petroleum and chemical engineering.…”

Development of Generalized Correlations for Thermophysical Properties of Light Hydrocarbon Solvents (C1–C5)/Bitumen Systems Using Genetic Programming

“…Baghban et al 10 modeled the viscosity of Athabasca bitumen with n -tetradecane using the least square support vector machine method. Finally, Rostami et al 11 modeled bitumen/ n -tetradecane mixture density using gene expression programming as a function of solvent composition, pressure, and temperature. Their developed model predicts the mixture density with an AARD % of 0.3%.…”

Predictive models for density correction factor of natural gas and comparison with standard methods

“…Representing of a novel model and modifying other methods for natural gas density calculation implementing intelligent-based techniques is the goal of this work. These models are more efficient in such cases which involve nonlinear mathematical modeling along time consumption, and when there is not any significant relation between input and output of a system [17][18][19]. The intelligent models developed in this study are Artificial Neural Network (ANN) and Genetic Algorithms (GAs) Using Matlab (8.1.0.604).…”