CBM reservoir thickness prediction using the seismic nonlinear stochastic inversion method-Reference-Cited by-同舟云学术

CBM reservoir thickness prediction using the seismic nonlinear stochastic inversion method

Published:2023-04-10 Issue: Volume: Page:1-19
ISSN:1091-6466
Container-title:Petroleum Science and Technology
language:en
Short-container-title:Petroleum Science and Technology

Author:

Chen Fangbo¹²^ORCID,Iqbal Ibrar³^ORCID,Wang Jiabao²,Zhang Tianyu³,Yang Yang³,Chen Meng⁴

Affiliation:

1. School of Geophysics and Information Technology, China University of Geosciences, Beijing, China

2. Geophysical Survey Center, China Geological Survey, Langfang, Hebei, China

3. College of Earth Sciences, Guilin University of Technology, Guilin, Guangxi, China

4. School of Geography, Beijing Normal University, Beijing, China

Publisher

Informa UK Limited

Subject

Geotechnical Engineering and Engineering Geology,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/10916466.2023.2183216

Reference40 articles.

1. Channel identification using 3D seismic attributes and well logging in lower Shihezi Formation of Hangjinqi area, northern Ordos Basin, China

2. Controls on Reservoir Heterogeneity of a Shallow-Marine Reservoir in Sawan Gas Field, SE Pakistan: Implications for Reservoir Quality Prediction Using Acoustic Impedance Inversion

3. A Core Logging, Machine Learning and Geostatistical Modeling Interactive Approach for Subsurface Imaging of Lenticular Geobodies in a Clastic Depositional System, SE Pakistan

4. Application of Unconventional Seismic Attributes and Unsupervised Machine Learning for the Identification of Fault and Fracture Network

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