November 23, 2024
Soroush Ahmadi

Soroush Ahmadi

Academic Rank: Assistant professor
Address: Faculty of Petroleum, Gas and Petrochemical Engineering, Department of Chemical Engineering
Degree: Ph.D in Chemical Engineering
Phone: 0
Faculty: Faculty of Petroleum, Gas and Petrochemical Engineering

Research

Title Prediction of barium sulfate precipitation in dynamic tube blocking tests and its inhibition for waterflooding application using response surface methodology
Type Article
Keywords
Scaling, Pressure drop, Barium sulfate, RSM, Dynamic tube blocking test, Waterflooding
Journal Petroleum Exploration and Production Technology
DOI https://doi.org/10.1007/s13202-023-01679-2
Researchers Azizollah Khormali (First researcher) , Soroush Ahmadi (Second researcher)

Abstract

Scale precipitation is one of the major problems in the petroleum industry during waterflooding. The possibility of salt formation and precipitation should be monitored and analyzed under dynamic conditions to improve production performance. Scale precipitation and its dependence on production parameters should be investigated before using scale inhibitors. In this study, the precipitation of barium sulfate salt was investigated through dynamic tube blocking tests at different injection rates and times. For this purpose, the pressure drop caused by salt deposition was evaluated at injection rates of 1, 2, 3, 4, and 5 mL/min. The software determined the worst conditions (temperature, pressure, and water mixing ratio) for barium sulfate precipitation. Moreover, during the experiments, the pressure drop caused by barium sulfate precipitation was measured without using scale inhibitors. The pressure drop data were evaluated by the response surface method and analysis of variance to develop a new model for predicting the pressure drop depending on the injection rate and time. The novelty of this study lies in the development of a new high-precision correlation to predict barium sulfate precipitation under dynamic conditions using the response surface methodology that evaluates the effect of injection rate and time on the possibility of salt precipitation. The accuracy and adequacy of the obtained model were confirmed by using R2 statistics (including R2-coefficient of determination, adjusted R2, and predicted R2), adequate precision, and diagnostic charts. The results showed that the proposed model could fully and accurately predict the pressure drop. Increasing the time and decreasing the injection rate caused an increase in pressure drop and precipitation of barium sulfate salt, which was related to the formation of more salt due to the contact of ions. In addition, in a short period of the injection process, the pressure drop due to salt deposition increased sharply,