Appalachian Basin Temperature-Depth Maps and Structured Data in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy

This dataset contains shapefiles and rasters that summarize the results of a stochastic analysis of temperatures at depth in the Appalachian Basin states of New York, Pennsylvania, and West Virginia. This analysis provides an update to the temperature-at-depth maps provided in the Geothermal Play Fairway Analysis of the Appalachian Basin (GPFA-AB) Thermal Quality Analysis (GDR repository 879: https://gdr.openei.org/submissions/879). This dataset improves upon the GPFA-AB dataset by considering several additional uncertainties in the temperature-at-depth calculations, including geologic properties and thermal properties. A Monte Carlo analysis of these uncertain properties and the GPFA-AB estimated surface heat flow was used to predict temperatures at depth using a 1-D heat conduction model. In this data submission, temperatures are provided for depths from 1-5 km in 0.5 km increments. The mean, standard deviation, and selected quantiles of temperatures at these depths are provided as shapefiles with attribute tables that contain the data. Rasters are provided for the mean and standard deviation data. Figures and maps that summarize the data are also provided. For the pixel corresponding to Cornell University, Ithaca, NY, a .csv file containing the 10,000 temperature-depth profiles estimated from the Monte Carlo analysis is provided. These data are summarized in a figure containing violin plots that illustrate the probability of obtaining certain temperatures at depths below Cornell.本数据集包含形状文件（shapefile）与栅格数据（raster），汇总了纽约州、宾夕法尼亚州与西弗吉尼亚州所属阿巴拉契亚盆地区域深部温度的随机分析结果。本次分析对《阿巴拉契亚盆地地热有利区带分析（GPFA-AB）热质量分析》（GDR知识库藏品编号879：https://gdr.openei.org/submissions/879）收录的深部温度图进行了更新。本数据集相较GPFA-AB数据集实现了优化，在深部温度计算环节纳入了多项额外的不确定性参数，涵盖地质属性与热物性参数。本研究采用一维热传导模型，通过对上述不确定性参数与GPFA-AB估算的地表热流开展蒙特卡洛分析（Monte Carlo analysis），实现深部温度的预测。本次提交的数据覆盖了1至5千米、以0.5千米为间隔的所有深度的温度结果。上述深度下的温度均值、标准差以及指定分位数均以携带属性数据表的形状文件形式提供。栅格数据则用于提供温度均值与标准差的结果。本数据集同时附带汇总该数据的图表与地图。针对纽约州伊萨卡市康奈尔大学对应的栅格像素，本数据集附带一份.csv格式文件，其中包含通过蒙特卡洛分析估算得到的10000条温度-深度剖面数据。上述数据已通过一张附带小提琴图的图表进行汇总，该图直观展示了康奈尔大学下方不同深度下出现特定温度的概率分布。