%0 Journal Article
%T Static Modeling of Oil Field Mineral Scales: Software Development
%J Journal of Petroleum Science and Technology
%I Research Institute of Petroleum Industry (RIPI)
%Z 2251-659X
%A Parvazdavani, Mohammad
%A Kari Payhan, Behjat
%A Dinmohammad, Mahmood
%A Mousavi Dehghani, seyed Ali
%D 2017
%\ 06/20/2017
%V 7
%N 2
%P 77-90
%! Static Modeling of Oil Field Mineral Scales: Software Development
%K CaSO4 Scale
%K Laboratory Static Jar Tests
%K Iterative Mathematical Solver
%K Pitzer Thermodynamic Model
%K Ions Binary Interactive Coefficient
%R 10.22078/jpst.2017.750
%X Mineral scale deposition in near wellbore regions of injection wells is one of the main challengeable issues during the water injection process, which magnifies the importance of robust models in predicting the amount of mineral scale deposition such as calcium sulfate. One of the main challenges of CaSO4 scale is in carbonated reservoirs, in which sensitive behavior is observed in related to the contribution of both calcium and sulfate ions in carbonated and sulfated scale reactions. This defect is mirror of wrong procedure and value in the estimation of first kind/value of precipitant contributed in scale deposition reactions (ions competition) as well as inconsistent temperature/pressure dependent coefficients of prediction model. The objective of this study is to develop a model that can accurately predict the formation and amount of CaSO4 scale as the dominant scale in multicomponent aqueous systems by three major tools, namely utilization the best temperature- and pressure-dependent thermodynamic interactive ion coefficients (MSE Model: Pitzer), developing our fine-tuned iterative mathematical solver, and verification of the results of the model by accurate experimental data. The results showed that at the optimum value of precipitant (10%) in scale deposition reactions and by defining the best temperature- and pressure-dependent coefficients, we can attain the best accuracy in the prediction of CaSO4 scale deposited amount (less than 0.06% as a relative error compared to 36% overestimation and 22% underestimation in commercial software). The output of this study is developed software leading to the more accurate prediction of the amount of promising scales in near wellbore regions or pipelines.
%U https://jpst.ripi.ir/article_750_21f4fdb0e626006e106d8b1cba50ed29.pdf