We present a synthetic multi-scale, multi-physics dataset constructed from the Kimberlina 1.2 CO₂ reservoir model based on a potential CO₂ storage site in the Southern San Joaquin Basin of California. Among 300 models, one selected reservoir-simulation scenario produces hydrologic-state models at the onset and after 20 years of CO₂ injection. Subsequently, these models were transformed into geophysical properties, including P- and S-wave seismic velocities, saturated density where the saturating fluid can be a combination of brine and supercritical CO₂, and electrical resistivity using established empirical petrophysical relationships. From these 3D distributions of geophysical properties, we have generated synthetic time-lapse seismic, gravity and electromagnetic responses with acquisition geometries that mimic realistic monitoring surveys and are achievable in actual field situations. We have also created a series of synthetic well logs of CO₂ saturation, acoustic velocity, density and induction resistivity in the injection well and three monitoring wells. These were constructed by combining the low-frequency trend of the geophysical models with the high-frequency variations of actual well logs collected at the potential storage site. In addition, to better calibrate our datasets, measurements of permeability and pore connectivity have been made on cores of Vedder Sandstone, which forms the primary reservoir unit. These measurements provide the range of scales in the otherwise synthetic dataset to be as close to a real-world situation as possible. This dataset consisting of the reservoir models, geophysical models, simulated time-lapse geophysical responses and well logs forms a multi-scale, multi-physics testbed for designing and testing geophysical CO₂ monitoring systems as well as for imaging and characterization algorithms. The suite of numerical models and data have been made publicly available for downloading on the National Energy Technology Laboratory's (NETL) Energy Data Exchange (EDX) website.

中文翻译：

---

用于二氧化碳监测研究的 Kimberlina 综合多物理数据集

我们提出了一个综合的多尺度、多物理数据集，该数据集是根据加州南圣华金盆地潜在的 CO _{2封存地点的 Kimberlina 1.2 CO 2}储层模型构建的。在 300 个模型中，选定的一个水库模拟场景可在 CO ₂注入开始时和 20 年之后生成水文状态模型。随后，这些模型被转化为地球物理特性，包括纵波和横波地震速度、饱和密度（其中饱和流体可以是盐水和超临界CO ₂的组合）以及使用已建立的经验岩石物理关系的电阻率。根据这些地球物理特性的 3D 分布，我们生成了合成的时移地震、重力和电磁响应，其采集几何形状模仿了真实的监测调查，并且可以在实际现场情况下实现。我们还在注入井和三个监测井中创建了一系列CO ₂饱和度、声速、密度和感应电阻率的合成测井曲线。这些是通过将地球物理模型的低频趋势与在潜在封存地点收集的实际测井曲线的高频变化相结合而构建的。此外，为了更好地校准我们的数据集，对构成主要储层单元的维德砂岩岩心进行了渗透率和孔隙连通性测量。这些测量提供了其他合成数据集中的尺度范围，使其尽可能接近真实世界的情况。该数据集由储层模型、地球物理模型、模拟延时地球物理响应和测井记录组成，形成了一个多尺度、多物理测试平台，用于设计和测试地球物理CO ₂监测系统以及成像和表征算法。这套数值模型和数据已在国家能源技术实验室 (NETL) 能源数据交换 (EDX) 网站上公开下载。