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Statistical modeling of geopressured geothermal reservoirs

机译：地压地热藏统计模型

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摘要

Identifying attractive candidate reservoirs for producing geothermal energy requires predictive models. In this work, inspectional analysis and statistical modeling are used to create simple predictive models for a line drive design. Inspectional analysis on the partial differential equations governing this design yields a minimum number of fifteen dimensionless groups required to describe the physics of the system. These dimensionless groups are explained and confirmed using models with similar dimensionless groups but different dimensional parameters. This study models dimensionless production temperature and thermal recovery factor as the responses of a numerical model. These responses are obtained by a Box-Behnken experimental design. An uncertainty plot is used to segment the dimensionless time and develop a model for each segment. The important dimensionless numbers for each segment of the dimensionless time are identified using the Boosting method. These selected numbers are used in the regression models. The developed models are reduced to have a minimum number of predictors and interactions. The reduced final models are then presented and assessed using testing runs. Finally, applications of these models are offered. The presented workflow is generic and can be used to translate the output of a numerical simulator into simple predictive models in other research areas involving numerical simulation.
机译：确定有吸引力的候选储层以生产地热能需要预测模型。在这项工作中，检验分析和统计建模用于为线路驱动器设计创建简单的预测模型。对支配该设计的偏微分方程的检验分析得出描述系统物理特性所需的最少15个无量纲组。使用具有相似无量纲组但尺寸参数不同的模型来解释和确认这些无量纲组。本研究将无量纲的生产温度和热回收系数建模为数值模型的响应。这些反应是通过Box-Behnken实验设计获得的。不确定性图用于分割无因次时间，并为每个分段建立模型。使用Boosting方法识别无量纲时间每个片段的重要无量纲数字。这些选定的数字用于回归模型。已开发的模型被简化为具有最少数量的预测变量和交互作用。然后提供简化的最终模型，并使用测试运行进行评估。最后，提供了这些模型的应用。呈现的工作流是通用的，可用于将数值模拟器的输出转换为涉及数值模拟的其他研究领域中的简单预测模型。

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