Scale formation at the subsurface can block perforations, fractures, and pore throats in the near-wellbore region, causing formation damage and loss of well productivity. This paper presents a field case study with an integrated data analysis approach and conceptual model on the diagnosis, remediation, and control of subsurface scale formation.

Unlike scale deposits in production tubing or topside facility, subsurface scale deposits cannot easily be collected or visually observed due to operational uncertainty/difficulty/cost, and safety considerations. In this study, integrated data analysis and scale modeling based on field conditions and water chemistry data from downhole formation water samples, preserved core samples, completion brines, and produced water samples were utilized to diagnose subsurface scale formation and help develop remediation strategy for a deep water well with significant production underperformance (50%+ lower than expected).

MDT (modular formation dynamics tester) water data from this field can be categorized into 3 groups with higher (Type 1), medium (Type 2), and lower (Type 3) concentrations of Cl-, Ca2+, and Ba2+. A novel mathematical algorithm was developed and successfully implemented to calculate produced water source allocation and the composition of produced formation water over time. The calculated produced formation water chemistry data is consistent with MDT water database with respect to both total ion concentrations and ion-ion correlations. Produced water source allocation results show the produced formation water changed from type 1/2 water-dominating composition to type 3 water-dominating composition over time. Integration of the time-lapse produced water source allocation results, production data, and scale modeling results, and comparison with analog wells indicate potential block-out of production from certain formation zones at the underperforming well. Calcite scale precipitation at subsurface due to completion brine-formation water commingling in the near wellbore region during well completion and shut-in stages prior to production is deemed as a primary cause of the production allocation change and significant production underperformance. Learnings from this study provided an important basis to develop/optimize well remediation and subsurface scale control strategies.

This paper clearly demonstrates an integrated data analysis approach based on historical water chemistry and production profile for subsurface scale diagnosis. Moreover, a conceptual model has been developed to help explain, diagnose, and control subsurface scale formation and its impact on well production underperformance. The developed model is successfully applied and validated in explaining findings/results in this field case study.

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