Abstract
This paper describes field experience of designing a successful scale squeeze program for an oil well. This was done utilizing an adsorption isotherm derived from a core flood data from other reservoir. Correlation and reliability of the adsorption isotherm with actual field flow back data after squeeze treatment for a period of 18-month are given. Moreover, utilizing the knowledge generated, a bespoke multilayer adsorption isotherm was optimized for a treated well for more efficient squeeze design for next treatment.
In order to achieve our objective, an adsorption isotherm from other reservoir core flood was first generated. With the knowledge not limited to current candidate well production rates, well properties, perforation height, number of zones and other essential parameters, a 18-month squeeze treatment program was designed. Water chemistry 18-month data was utilized to validate the scale squeeze design. An improved multilayer adsorption isotherm bespoke for this well was generated.
In conjunction with flow-back production data, a scheduled sampling program and water analysis utilizing Inductively Coupled Plasma (ICP) for post treatment Scale Inhibitor (SI) residuals data was collected to validate the adsorption isotherm derived from other reservoir. As predicted by the model for post treatment monitoring, the SI residual concentration; back calculated from SI chemistry utilized for the treatment are found to have an excellent correlation with the adsorption isotherm derived from a different reservoir. Hence, the 18-month squeeze design derived from a different reservoir was a great success. The slight difference between real flow back data and the adsorption isotherm generated from other reservoir become a benchmark to derive an improved adsorption isotherm to optimize the scale inhibition protection than the current treatment.
In summary, parameters such as mineralogy study, porosity, permeability, crude properties and dynamic scale loop (DSL) study are the utmost important information to be analyzed prior using other reservoir core flood data as reference. As results shown, these are the best way to generate squeeze design with limited information had in hand.