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Reassessing Helium Reserves in Continental China: A Machine Learning–Monte Carlo Framework

NIAID Data Ecosystem2026-05-10 收录

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https://figshare.com/articles/dataset/Reassessing_Helium_Reserves_in_Continental_China_A_Machine_Learning_Monte_Carlo_Framework/31323187 数据链接链接失效反馈

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Reassessing Helium Reserves in Continental China

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创建时间：

2026-02-12

非常规油气

地质储量预测

The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is...

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USGS National and Global Oil and Gas Assessment Project-Gulf Coast Mesozoic Province, Lower Cretaceous Travis Peak and Hosston Formations: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables

石油资源评估

地质储量预测

This data release contains the boundaries of assessment units and input data for the assessment of undiscovered conventional and continuous oil and gas resources in the Lower Cretaceous Hosston and Tr

USGS-Science Data Catalog10

USGS National and Global Oil and Gas Assessment Project-Eastern Great Basin Province, Delle Phosphatic Member Shale Assessment Unit Boundaries and Assessment Input Data Forms

非常规油气

地质储量预测

This data release contains the boundaries of assessment units and input data for the assessment of continuous oil and gas resources in the Delle Phosphatic Member of...

data.gov00

USGS National Assessment of Oil and Gas Project - Unconventional Assessment Units from 2000 to 2011

非常规油气

地质储量预测

The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is...

data.gov10

A parameterized framework for Helium enrichment assement and potential play analysis in fault-related geothermal systems, Southeastern Tibetan Plateau

氦气资源评估

地热系统勘探

This table contains 640 geothermal gas data and references published on the southeastern edge of the Qinghai Tibet Plateau, and provides helium enrichment potential for each region.

NIAID Data Ecosystem10

Reassessing Helium Reserves in Continental China: A Machine Learning–Monte Carlo Framework

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