Density Measurement and Prediction Model of the CO2–Water-Bearing Crude Oil System
Year: 2025
Type: article
Abstract: High Resolution Image Download MS PowerPoint Slide Accurately predicting the density variation trend of water-bearing crude oil in high-CO 2 -concentration production wells is of great significance for forecasting wellbore fluid flow dynamics and designing lifting processes at different stages of development. Indoor experiments were conducted on the CO 2 –water-bearing crude oil system, measuring the crude oil density under various conditions of temperature, pressure, CO 2 concentration, and water cut. The study explored the behavior of crude oil density under different working conditions, and a predictive model for high-CO 2 -concentration water-bearing crude oil density was developed using multiple regression analysis. The results indicate that under a certain water-cut condition, when the CO 2 content is below 50%, the density of the mixed fluid increases with rising pressure. However, when the CO 2 content exceeds 50%, the density first decreases and then increases as the pressure continues to rise. Under the same CO 2 injection volume, the density of the mixed fluid decreases with increasing temperature, and compared to the pressure, the density is more sensitive to temperature changes. Under the same temperature and pressure conditions, the density of the mixed fluid decreases with increasing the CO 2 injection volume but increases with higher water content. The new predictive model for the density of the CO 2 –water-bearing crude oil system, accounting for the combined influence of multiple factors, has an average error of just 3.16%, meeting the precision requirements for engineering calculations. This model offers valuable theoretical guidance for CO 2 flooding development in similar high-water-cut reservoirs.
Source: ACS Omega
Authors: Menglan Li, Yingzhu Guan, Weiqi Wang
Institution: Yangtze University
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,935
OpenAlex ID: W4407673728