Given the ill-defined term “naphthenic acids”(NAs), we will classify NAs as the carboxylic
acids found naturally in crude oil, which include both classic NAs (c-NAs, monoacids) and ox …

Quantitative prediction of crude oil properties (eg API gravity, kinematic viscosity, sulfur
content) can be conducted using multivariate calibration models. The growth and the …

In the current research, an analytical method was proposed for rapid quantitative
determination of saturates, aromatics, resins and asphaltenes (SARA) fractions of crude oil …

Classification based on° API gravity is very important to estimate the parameters related to
the extraction, purification, toxicity, and pricing of crude oils. Spectroscopy methods show …

252 literature sources and about 5000 crude oil assays were reviewed in this work. The
review has shown that the petroleum characterization can be classified in three categories …

Gradient-based algorithms are commonly used for training radial basis function neural
network (RBFNN). However, one of the challenges in the training process is determining …

The interfacial tension (IFT) between oil and brine is a key parameter affecting the enhanced
oil recovery process. Despite the several theoretical and experimental investigations on the …

Two data-driven approaches based on the Fourier-transform infrared spectroscopy (FTIR)
data are presented in this work to predict crude oil properties. The first approach is the …

Carboxylic acids (CAs), common oxygen-containing compounds in petroleum samples,
have been paid high attention in several areas, including petroleum geochemistry …

This study aims to develop an industrially reliable and accurate method to estimate crude oil
properties from their Fourier transform infrared spectroscopy (FTIR) spectra. We used the …