首页/数据集/To enhance CO2 saturation prediction from seismic data by joint use of attenuation and elastic properties: A machine learning approach

To enhance CO2 saturation prediction from seismic data by joint use of attenuation and elastic properties: A machine learning approach

NIAID Data Ecosystem2026-05-02 收录

CO2预测

地震属性分析

数据链接：

https://zenodo.org/record/10869315 数据链接链接失效反馈

官方服务：

资源简介：

Wang and Zhao submitted for GJI

应用场景：

创建时间：

2024-05-31

碳循环模型参数

CO2预测

Accurate estimation and forecasts of net biome CO2 exchange (NBE) are vital for understanding the role of terrestrial ecosystems in a changing climate. Prior efforts to improve NBE predictions have pr

DataCite Commons2024-05-07 更新100

Data for: Multiple Point Geostatistical Simulation with Adaptive Filter Derived from Neural Network for Sedimentary facies Classification

沉积物分类

地震属性分析

Data of seismic attributes, filters obtained by FAE.

NIAID Data Ecosystem60

Data for: Short-term Prediction of CO2 Concentration based on a Wireless Sensor Network

环境监测

CO2预测

No Field Description 1 Record id Increment record id (unique) 2 timestamp Linux timestamp, anda bisa melihat konversi waktu linux time pada link berikut ini https://www.epochconverter.com/ 3 CO2 CO2

NIAID Data Ecosystem40

pCO2 reconstructions - Large Ensemble Testbed - RF - CESM

地球系统建模

CO2预测

Reconstructions of the Large Ensemble Testbed generated by NN, XGB, and RF algorithms.

Figshare2020-09-15 更新70

GRDs of the eight types seismic attributes.

地震属性分析

油气勘探地质建模

GRDs of the eight types seismic attributes.

NIAID Data Ecosystem40