利用电容电阻模型和分层分流模型估算成熟水驱性能及优化

F. Gamarra, Manuela Saénz Caba Argentina Sinopec Argentina E P, Néstor E Ramos, Ignacio Borsani
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引用次数: 1

摘要

在阿根廷的Golfo San Jorge盆地,水驱是一种最古老、最广泛的方法,用于提高低天然能量初级采收率。事实证明,在Golfo San Jorge盆地Cañadón Minerales油田CM-123-A项目中,注水是提高油藏采收率的有效方法。根据油藏的地质构造,确定最佳的注入速度和注入方式,是油藏管理的一项重要的操作和经济决策。本文采用隐式考虑地质和储层参数的电容电阻模型(CRM),按层(独立储层)寻找井间连通性,通过补充净砂图、岩石物理和生产测试数据来优化注入速度,并检查解与所有可用数据的一致性,以支持决策。CRM接收来自不同储层的注入速率变化作为输入信号,而采油者的响应则定量地确定了注入器/采油者对的连通性。CRM的不同运行可用于检测生产商人工举升的一些突然变化如何影响连通性,并提出一些改进建议。此外,该模型还可用于预测单个储层的总产量,并与多层FFM(分流模型)一起估算每个储层的产油量,识别不同储层的潜力,并改进注入速度以优化产油量。结果表明,CRM能够匹配生产历史,校准动态有效参数,并通过该表征优化不同井注水井和油藏的注入速度,在非混相驱过程中,了解注水运动,并作为净砂图联合验证的辅助。该CRM系统不仅能够检测到一线和二线生产商的井间连通性,而且能够在现场得到明确的响应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of Mature Water Flooding Performance and Optimization by Using Capacitance Resistive Model and Fractional Flow Model by Layer
Waterflooding is the oldest and most extended method to enhance recovery from oil reservoirs in primary production with low natural energy in the Golfo San Jorge Basin, Argentina. Water injection has proven to be an effective method to enhance recovery from oil reservoirs for project CM-123-A at Cañadón Minerales field, Golfo San Jorge Basin. Defining the optimized injection rates and injection patterns, which depend on the geological structure of the reservoir, is an essential operational and economical decision for reservoir management. In this paper, the capacitance resistive model (CRM), which takes into account implicitly the geological and reservoir parameters, is used to find inter-well connectivity by layer (independent reservoir), optimize injection rates with the complement of net sand maps and petro-physical and production test data, and check the consistency of the solutions with all the available data to support the decisions. The CRM receives the injection rates variations as input signal, from the different reservoirs, whereas the producer responses determine the injector/producer pair connectivity quantitatively. The different runs of the CRM can be used to detect how some abrupt changes in the artificial lift of the producers affect the connectivity and propose some improvements. Also, this model is used to predict gross production for individual reservoir, together with a multilayer FFM (fractional flow model) can be estimated the oil production for each individual reservoir, identify the potential from different reservoirs and improvements in the injection rates to optimize the oil production. The results reveal that the CRM has the capability to match the production history to calibrate the dynamical effective parameters and with this characterization optimize the injection rates of the different wells injectors and reservoirs, during the immiscible flooding, understand water injection movement, and as accessory the joint validation of the net sand maps. The CRM was able to detect inter-well connectivity for producers connected not only at the first line but also at the second line, with a clear response in the field.
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