Thermally induced fractures (TIFs) are common in waterflooded fields where the injection of (relatively) cold water leads to a cooling front that reduces a formation's in-situ stresses. Understanding TIFs is important since their existence impacts oil recovery potential, well injectivity, injection well integrity, and injector-producer well spacing in reservoirs under waterflooding. Identifying and characterizing dynamic TIF growth is a critical step in defining field development strategies and making daily reservoir management decisions. This research introduces a workflow that integrates analytical well monitoring and semi-analytical models to identify TIF onset, propagation properties, direction, and impact during dynamic reservoir events occurring at different levels. The practicality of the proposed workflow has been tested using synthetic data and its robustness confirmed by an analysis of actual field data. The novelty of the approach presented here is in its efficient integration of recent analytical and semi-analytical models to identify TIF onset, propagation, characteristics, and impact from generally available well injection production history data. This practical workflow will help engineers detect and monitor TIFs and evaluate the metrics describing waterflood performance, including flood efficiency, inter-well communication, and pressure maintenance.

热致裂缝（TIF）在注水领域很常见，在该领域注入（相对）冷水会导致冷却锋面减小地层应力。了解TIF非常重要，因为它们的存在会影响注水条件下油藏中的采油潜力，油井注入能力，注入井完整性以及注入井与生产井的井距。确定和表征动态TIF的增长是定义油田开发策略和制定日常油藏管理决策的关键步骤。这项研究引入了一个工作流程，该工作流程集成了分析井监测和半分析模型，以识别在不同水平发生的动态油藏事件期间的TIF发生，传播特性，方向和影响。拟议工作流程的实用性已使用合成数据进行了测试，并且其健壮性通过对实际现场数据的分析得到了证实。本文介绍的方法的新颖之处在于，它有效地整合了最新的分析模型和半分析模型，从而可以从通常可获得的注井生产历史数据中识别TIF的起效，扩散，特征和影响。这个实用的工作流程将帮助工程师检测和监控TIF，并评估描述注水性能的指标，包括注水效率，井间通讯和压力维护。以及一般可获得的注井生产历史数据的影响。这个实用的工作流程将帮助工程师检测和监控TIF，并评估描述注水性能的指标，包括注水效率，井间通讯和压力维护。以及一般可获得的注井生产历史数据的影响。这个实用的工作流程将帮助工程师检测和监控TIF，并评估描述注水性能的指标，包括注水效率，井间通讯和压力维护。