Simulation on water and sand separation from crude oil in settling tanks based on the particle model
Title
Simulation on water and sand separation from crude oil in settling tanks based on the particle model
Subject
Crude oil
Separation
Emulsification
Oil fields
Drops
Oil tanks
Sand
Settling tanks
Description
Settling tanks have been widely applied to water and sand separation from crude oil. At present, the related studies on the effect of water and sand separation in settling tanks mainly focus on computational simulation methods. This paper puts forward a model to simulate the settling process, which considers the heterogeneous diameter distribution of real particles and the variation of emulsion viscosity with water content. In this model, water and sand are perceived as dispersed water droplets and sand particles. By means of tracking the positions of all droplets and particles, variation of water and sand contents are obtained and influential factors of water and sand separation such as settling time, temperatures and processing capacity are analyzed. An experiment conducted in Lao Junmiao oil-field verifies accuracy of the model. Water contents were measured at every 1 m height of a settling tank under the condition of 20 C. Compared with the experimental data, the maximum relative error of the model simulation is 9.38% while the corresponding results of Euler-Eulerian method solved by FLUENT is 33.46%, which identifies that the model is better coincident with the field production. In practical application, the model can determine the processing capacity, settling time and temperature, which are significant for enhancing separation efficiency. 2017 Elsevier B.V.
366-372
156
Publisher
Journal of Petroleum Science and Engineering
Date
2017
Contributor
Zhang, Haoran
Liang, Yongtu
Yan, Xiaohan
Wang, Bohong
Wang, Ning
Type
journalArticle
Identifier
9204105
10.1016/j.petrol.2017.06.012
Collection
Citation
“Simulation on water and sand separation from crude oil in settling tanks based on the particle model,” Lamar University Midstream Center Research, accessed May 14, 2024, https://lumc.omeka.net/items/show/24851.