Reservoir sustainability is strongly impacted by the reservoir sedimentation processes. Most of the substantial sedimentation processes occur in non‐stationary flows such as in the case of flash floods, surges and tidal waves. However, a stationary probability assumption is normally adopted to reduce mathematical model complexity. This work develops a non‐stationary Gambler's ruin model using the Monte‐Carlo simulation method. Daily water‐level data for the Xia‐Yun station are used to predict the effective risk that the maximum capacity of the water treatment plant in the Shihmen Reservoir is reached. This non‐stationary model yields fairly accurate probabilities of sedimentation by the transitional probability of a reservoir reaching different levels of turbidity, and the average time to reach a designated reservoir maximum handling turbidity. The extended capacity of the proposed model demonstrates the major particle processes during non‐stationary flows. Such analytical results offer water resources agency to scientifically evaluate the dredging/remediation strategies with the existing reservoirs. Transport capacities of rivers and streams, and the potential consequences of flood risks in response to reservoir sedimentation can then be comprehensively estimated in order to allow effective contingency planning for public safety.

中文翻译：

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非平稳流下油藏沉降的风险分析

油藏的可持续性受到油藏沉降过程的强烈影响。大多数实质性沉积过程都发生在非平稳流动中，例如在山洪，潮汐和潮汐的情况下。但是，通常采用固定概率假设来降低数学模型的复杂性。这项工作使用蒙特卡洛模拟方法开发了一个非平稳赌徒的废墟模型。夏云站的每日水位数据用于预测石门水库水处理厂达到最大容量的有效风险。该非平稳模型通过储层达到不同浊度水平的过渡概率，以及达到指定储层最大处理浊度的平均时间，得出了相当准确的沉降概率。拟议模型的扩展能力证明了非平稳流动过程中的主要颗粒过程。这样的分析结果为水资源机构提供了科学评估现有水库疏the /修复策略的方法。然后可以对河流和河流的运输能力以及洪水对水库沉降的潜在后果进行综合估算，以便为公共安全制定有效的应急计划。