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A Methodology for Establishing a Data Reliability Measure for Value of Spatial Information Problems

机译:建立空间信息问题价值数据可靠性测度的方法

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摘要

We propose a value of information (VOI) methodology for spatial Earth problems. VOI is a tool to determine whether purchasing a new information source would improve a decision-makers’ chances of taking the optimal action. A prior uncertainty assessment of key geologic parameters and a reliability of the data to resolve them are necessary to make a VOI assessment. Both of these elements are challenging to obtain, as this assessment is made before the information is acquired.We present a flexible prior geologic uncertainty modeling scheme that allows for the inclusion of many types of spatial parameter. Next, we describe how to obtain a physics-based reliability measure by simulating the geophysical measurement on the generated prior models and interpreting the simulated data. Repeating this simulation and interpretation for all datasets, a frequency table can be obtained that describes how many times a correct or false interpretation was made by comparing them to their respective original model. This frequency table is the reliability measure and allows a more realistic VOI calculation. An example VOI calculation is demonstrated for a spatial decision related to aquifer recharge where two geophysical techniques are considered for their ability to resolve channel orientations. As necessitated by spatial problems, this methodology preserves the structure, influence and dependence of spatial variables through the prior geological modeling and the explicit geophysical simulation and interpretations.
机译:我们为空间地球问题提出了一种有价值的信息(VOI)方法。 VOI是确定购买新信息源是否会增加决策者采取最佳行动的机会的工具。要进行VOI评估,必须事先对关键地质参数进行不确定性评估以及解决这些问题的数据的可靠性。由于要在获取信息之前进行此评估,因此获取这两个元素都具有挑战性。我们提出了一种灵活的先验地质不确定性建模方案,该方案允许包含多种类型的空间参数。接下来,我们描述如何通过在生成的先前模型上模拟地球物理测量并解释模拟数据来获得基于物理的可靠性测量。对所有数据集重复此模拟和解释,可以获得频率表,该频率表通过将它们与各自的原始模型进行比较来描述进行了正确或错误解释的次数。该频率表是可靠性的量度,可以进行更实际的VOI计算。举例说明了与含水层补给有关的空间决策的VOI计算示例,其中考虑了两种地球物理技术解决通道方位的能力。由于空间问题的需要,该方法通过先验的地质建模以及明确的地球物理模拟和解释来保留空间变量的结构,影响和依赖性。

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