碳酸盐
磁导率
生产力
对比度(视觉)
化学
石油工程
材料科学
化学工程
计算机科学
地质学
工程类
人工智能
有机化学
膜
生物化学
经济
宏观经济学
作者
Akmal Nizam Mohammed,A. Mohd,Hadi Amat,Tan Boon Choon
标识
DOI:10.2523/iptc-24943-ms
摘要
Abstract New wells drilled in the Middle East's vast carbonate fields face significant damage from drilling and completion operations, which severely impacts productivity. Damage can extend from a few inches to over 3 feet into the formation, impairing permeability across pay zones. Natural permeability contrast, due to carbonate build-up over time and depositional environments, also affects lower zone productivity, requiring near-wellbore permeability enhancement. Conventional hydrochloric acid (HCl) is ineffective due to its high reaction rate. A retarded acid system is essential for controlling reaction rates and improving wormhole development. The new methodology employed a bullheading operation, combining a high-viscous non-reactive solids-free (HVNRSF) chemical diverter with a single-phase retarded acid system (SPRAS). Coiled tubing (CT) was used throughout the operation, beginning with perforation conditioning prior to acid treatment. Real-time fiber optics combined with coiled tubing (FOECT) and distributed temperature surveys (DTS) were employed to identify high and low intake zones, enabling on-the-fly adjustments to the diversion strategy and monitoring the diverter's effectiveness. During the 3-well campaign, significant injection pressure increases were observed when diverter pills reached the formation. DTS data demonstrated more uniform acid distribution across perforated intervals compared to previous methods. Production contribution from the bottom zone was validated using production logging data. Continuous well test production monitoring post-treatment with SPRAS and HVNRSF diverter pills showed a ~25% increase in production, due to enhanced penetration into the lower permeability formation. The combination of SPRAS and HVNRSF chemical diverters significantly improved matrix stimulation, leading to a ~25% production increase. This paper shares the experiences and lessons learned during the initial campaign and provides recommendations for further improvement and broader implementation in the field.
科研通智能强力驱动
Strongly Powered by AbleSci AI