In field work recently conducted, it was revealed that there were no scale control measures in place because scale prediction conducted earlier had concluded that there was no scaling risk. However, a field survey later observed calcium carbonate deposits. In view of the inconsistency between theoretical prediction and field observations, another scale prediction study was conducted to understand the real field scaling potential.
Carbonate scale prediction is more challenging due to the CO2 evolution and partitioning into all three (water/oil/gas) phases during production. This paper describes the scale prediction conducted at three different scenarios: (1) prediction without hydrocarbon, i.e., only water production during the calculation; (2) prediction with water and gas, i.e., gas production is considered; and (3) prediction with all three phases, i.e., the true replication of the production. The effect of pH was studied in detail during sensitivity runs. In addition, the effect of power oil on scaling potential is also investigated. It is well known that pH increase has a profound effect to prompt calcium carbonate scaling potential; a local increase in pH contributed to the solid deposition observed in field. The exclusion of the oil and gas phases in the previous modeling underestimated the real scaling risk. The carbonate scaling potential increases significantly when hydrocarbon was included into the calculation. The addition of power oil has little effect on the overall scaling potential in this case.
This is a typical case in demonstrating that invalid scaling prediction can cause misinterpretation of true scale potential and therefore insufficient scale control resulting in scale buildup in field. This work highlights the importance of validity and reliability of data input into scale prediction software, in particular for carbonate scale prediction. It is essential to have a comprehensive understanding of reactions in all three phases, i.e., the total alkalinity and CO2 mass balance, to ensure an accurate prediction. Because CO2 can partition into all the three phases (water, oil and gas), compositional analysis for both oil and gas at the water sampling/analysis condition should be obtained before an accurate scale prediction can be made. Prediction results from any scale prediction software are only accurate if the input information is correct and sufficient. Without the complete information set, the scale prediction can only be treated as indicative. Field observations and deposit analysis should be incorporated into the consideration to evaluate the true likelihood and severity of the scale problem.
Scale prediction software has been widely used in the industry to diagnose the scale type, location and severity. It is used as part of the scale control and management process to identify when and where there is scaling risk and how to best control it. There are several industrial recognized scale prediction software packages including Multiscale, Scalechem, ScaleSoftPitzer, which are all based on thermodynamic (rather than kinetic) equations. They are more reliable in predicting the type of scale, the likelihood of scale formation and the maximum scale amount, but they are not sensitive in identifying.