AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (5 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Open Access

Classification and evaluation method for deep low-permeability sandstone reservoirs in Lufeng Sag

Qing YANGJunyi LIU( )Wei SONGTao CHENJiarong ZHANG
Shenzhen Branch of CNOOC (China) Co., Ltd., Shenzhen 518054, Guangdong, China
Show Author Information

Abstract

Low-porosity and low-permeability reservoirs are developed in the Enping Formation and Wenchang Formation in the Lufeng Sag, the Pearl River Mouth Basin. Due to their complex pore structure and strong heterogeneity, conventional porosity-permeability relationship models exhibit low accuracy in permeability calculation, making it difficult to meet the actual production needs such as reservoir effectiveness identification and productivity prediction. Starting from the generation principle of porosity spectrum in electrical imaging, and combining with core experiments and forward simulation results, the authors systematically compared the differences between nuclear magnetic resonance (NMR) T2 spectra and porosity spectrum generated by conventional methods, deeply analyzed the reasons for the shortcomings of conventional porosity spectrum in characterizing rock pore structure, and proposed an improved porosity spectrum construction method based on pore volume statistics. The improved porosity spectrum shows excellent consistency with the NMR T2 spectrum, which can more accurately reflect the pore structure characteristics of the reservoir. On this basis, the pseudo-NMR Schlumberger-Doll Research (SDR) model is used for reservoir permeability evaluation, which significantly improves the calculation accuracy over conventional methods. It can better reflect the advantage of high resolution compared to nuclear magnetic logging, providing reliable data support for fine reservoir description and productivity prediction.

Article ID: 1673-9736(2026)02-0137-11

References

【1】
【1】
 
 
Global Geology
Pages 137-147

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
YANG Q, LIU J, SONG W, et al. Classification and evaluation method for deep low-permeability sandstone reservoirs in Lufeng Sag. Global Geology, 2026, 29(2): 137-147. https://doi.org/10.3969/j.issn.1673-9736.2026.02.04

195

Views

11

Downloads

0

Crossref

Received: 12 December 2025
Accepted: 06 February 2026
Published: 25 May 2026
© 2026 GLOBAL GEOLOGY