4.6 Article

Prediction of Longitudinal Superimposed Sweet Spot of Tight Gas Reservoir: A Case Study of Block G, Canada

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Engineering, Petroleum

A New Ensemble Machine-Learning Framework for Searching Sweet Spots in Shale Reservoirs

Jizhou Tang et al.

Summary: The study introduces a group of gradient-boosting decision tree algorithms to automatically determine sweet spots, significantly improving interpretation agreement rates. Additionally, the training data is augmented using generative adversarial networks, further enhancing the model. Finally, an ensemble learning framework connecting multiple classifiers is utilized to further improve agreement rates.

SPE JOURNAL (2021)

Article Energy & Fuels

Fluid charging and hydrocarbon accumulation in the sweet spot, Ordos Basin, China

Wen Zhao et al.

Summary: This study proposes a novel method to simulate the fluid charging and hydrocarbon accumulation processes in tight reservoirs. The results show that the presence of fractures is favorable for hydrocarbon charging into the reservoir rocks, but not for hydrocarbon accumulation.

JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2021)

Article Energy & Fuels

Development characteristics and orientation of tight oil and gas in China

Sun Longde et al.

PETROLEUM EXPLORATION AND DEVELOPMENT (2019)

Article Energy & Fuels

China's shale gas exploration and development: Understanding and practice

Ma Yongsheng et al.

PETROLEUM EXPLORATION AND DEVELOPMENT (2018)

Article Computer Science, Artificial Intelligence

Data mining and machine learning for identifying sweet spots in shale reservoirs

Pejman Tahmasebi et al.

EXPERT SYSTEMS WITH APPLICATIONS (2017)

Article Energy & Fuels

The organic matter distribution and methane capacity of the lower Cretaceous strata of northeastern British Columbia, Canada

Gareth R. L. Chalmers et al.

INTERNATIONAL JOURNAL OF COAL GEOLOGY (2007)