DEEPEN 3D PFA Index Models for Exploration Datasets at Newberry Volcano

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.

As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), index models needed to be developed to map values in geoscientific exploration datasets to favorability index values. This GDR submission includes those index models.

Index models were created by binning values in exploration datasets into chunks based on their favorability, and then applying a number between 0 and 5 to each chunk, where 0 represents very unfavorable data values and 5 represents very favorable data values. To account for differences in how exploration methods are used to detect each play component, separate index models are produced for each exploration method for each component of each play type.

Index models were created using histograms of the distributions of each exploration dataset in combination with literature and input from experts about what combinations of geophysical, geological, and geochemical signatures are considered favorable at Newberry. This is in attempt to create similar sized bins based on the current understanding of how different anomalies map to favorable areas for the different types of geothermal plays (i.e., conventional hydrothermal, superhot EGS, and supercritical). For example, an area of partial melt would likely appear as an area of low density, high conductivity, low vp, and high vp/vs. This means that these target anomalies would be given high (4 or 5) index values for the purpose of imaging the heat source. To account for differences in how exploration methods are used to detect each play component, separate index models are produced for each exploration method for each component of each play type.

Index models were produced for the following datasets:
- Geologic model
- Alteration model
- vp/vs
- vp
- vs
- Temperature model
- Seismicity (density*magnitude)
- Density
- Resistivity
- Fault distance
- Earthquake cutoff depth model

DEEPEN项目旨在对岩浆环境中的地热储进行风险降低式勘探。该项目在开发针对岩浆型地热储（包括传统热液、超高温增强型地热系统及超临界型）的3D勘探有利区分析（PFA）方法的过程中，需建立指数模型，以将地球科学勘探数据集中的数值映射至有利度指数值。本GDR提案包含了这些指数模型。

指数模型是通过将勘探数据集中的数值根据其有利性进行分箱，并对每个分箱赋予介于0至5之间的数值来构建的，其中0代表极其不利的数值，而5代表极其有利的数值。为考量不同勘探方法在探测每种地热储组成部分时的差异，为每种勘探方法以及每种地热储类型的每个组成部分均制作了独立的指数模型。

指数模型的构建，是通过结合每个勘探数据集的分布直方图、文献资料以及专家意见，关于在Newberry地区，哪些地球物理、地质和地球化学特征组合被视为有利。此举措旨在根据当前对不同异常如何映射到不同类型地热储（即传统热液、超高温增强型地热系统及超临界型）的有利区的理解，创建相似大小的分箱。例如，部分熔融区域可能表现为低密度、高电导率、低纵波速度和高纵波速度与横波速度之比。这意味着，这些目标异常将获得高（4或5）的指数值，以实现热源的成像。为考量不同勘探方法在探测每种地热储组成部分时的差异，为每种勘探方法以及每种地热储类型的每个组成部分均制作了独立的指数模型。

以下数据集针对指数模型进行了制作：
- 地质模型
- 变质模型
- 纵波速度与横波速度比
- 纵波速度
- 横波速度
- 温度模型
- 地震活动性（密度*震级乘积
- 密度
- 电阻率
- 断层距离
- 地震截止深度模型