海陆过渡相页岩气层系沉积研究进展与页岩气新发现.

董大忠, 邱振, 张磊夫, 李树新, 张琴… - Acta …, 2021 - search.ebscohost.com
摘要四川盆地海相页岩气成功规模效益开发, 使我国页岩气跨入了高速发展的快车道,
确立了页岩气在我国能源安全保障中的重要战略地位. 我国海陆过渡相页岩气资源丰富 …

Unusually petrophysical behavior and geological significance of mudrocks

J Lai, T Bai, Y Zhao, L Xiao, Z He, C Wang… - Geoenergy Science and …, 2023 - Elsevier
Mudrocks have varied composition and texture, and heterogeneous nano to micro-scale
pore assemblages, and therefore show distinctly different well log responses. A better …

Geological characteristics and shale oil potential of alkaline lacustrine source rock in Fengcheng Formation of the Mahu Sag, Junggar Basin, Western China

Y Wu, C Liu, F Jiang, T Hu, J Lv, C Zhang, X Guo… - Journal of Petroleum …, 2022 - Elsevier
Shale oil is the main field of unconventional hydrocarbon exploration and exploitation.
Additionally, deep (> 4500 m) petroleum exploration in sedimentary basins is a worldwide …

Mineralogical and chemical distribution of the Es3L oil shale in the Jiyang Depression, Bohai Bay Basin (E China): Implications for paleoenvironmental reconstruction …

J He, W Ding, Z Jiang, K Jiu, A Li, Y Sun - Marine and Petroleum Geology, 2017 - Elsevier
The Es 3 L (lower sub-member of the third member of the Eocene Shahejie Formation) shale
in the Jiyang Depression is a set of relatively thick and widely deposited lacustrine …

Improving uncertainty analysis in well log classification by machine learning with a scaling algorithm

R Feng - Journal of Petroleum Science and Engineering, 2021 - Elsevier
Uncertainty is an important indicator that can provide the confidence in the predictions.
However, most machine learning methods in classification problems are incapable of …

[HTML][HTML] Rapid identification of high-quality marine shale gas reservoirs based on the oversampling method and random forest algorithm

L Zhu, X Zhou, C Zhang - Artificial Intelligence in Geosciences, 2021 - Elsevier
The identification of high-quality marine shale gas reservoirs has always been a key task in
the exploration and development stage. However, due to the serious nonlinear relationship …

Data-driven machine learning approaches for precise lithofacies identification in complex geological environments

M Ali, P Zhu, M Huolin, R Jiang, H Zhang… - Geo-spatial …, 2024 - Taylor & Francis
Reservoir characterization is a vital task within the oil and gas industry, with the identification
of lithofacies in subsurface formations being a fundamental aspect of this process. However …

Data-driven lithofacies prediction in complex tight sandstone reservoirs: a supervised workflow integrating clustering and classification models

M Ali, P Zhu, R Jiang, M Huolin, U Ashraf… - … and Geophysics for Geo …, 2024 - Springer
Lithofacies identification plays a pivotal role in understanding reservoir heterogeneity and
optimizing production in tight sandstone reservoirs. In this study, we propose a novel …

Laminar characteristics of lacustrine organic-rich shales and their significance for shale reservoir formation: A case study of the Paleogene shales in the Dongying Sag …

J Shi, Z Jin, Q Liu, T Zhang, T Fan, Z Gao - Journal of Asian Earth Sciences, 2022 - Elsevier
Shale oil exploration in China has demonstrated that laminated shales are favorable
lithofacies for producing shale oil effectively. It is of great significance to study the type and …

[HTML][HTML] A FEM-DFN model for the interaction and propagation of multi-cluster fractures during variable fluid-viscosity injection in layered shale oil reservoir

CH Huang, HY Zhu, JD Wang, J Han, GQ Zhou… - Petroleum Science, 2022 - Elsevier
To investigate the height growth of multi-cluster fractures during variable fluid-viscosity
fracturing in a layered shale oil reservoir, a two-dimensional finite element method (FEM) …