Comprehensive Evaluation Method of the Tight Oil Reservoir Quality in the Ordos Basin

The Wuqi area of the Ordos Basin boasts significant resource potential in the Chang 8 member of the Yanchang Formation. However, under the dual control of lithology and physical properties, reservoirs are generally dense and heterogeneous, and the quality of the oil layer changes rapidly, which brings difficulties to the optimization of favorable areas. To evaluate the reservoir quality more accurately, based on core observations, and logging and dynamic data analysis, combined with casting thin sections, scanning electron microscopy, high‐pressure mercury injection, nuclear magnetic resonance, and other related experiments, different reservoir types and characteristics were analyzed, and a comprehensive method for evaluating the reservoir quality was established. There are three types of sand body structures in the shallow‐water delta of Chang 8 in the study area, including the continuous superposition type, interval superposition type, and lateral single‐layer type. They mainly experienced diagenesis, such as compaction, cementation, and dissolution. Among these, porosity loss in the Chang 8 reservoir due to compaction and cementation reached 79.3%, consistent with trends observed in other continental tight oil plays such as the Songliao and Junggar Basins, while the improvement in physical properties due to dissolution was minimal. The main parameters influencing different reservoir types are optimized, and the comprehensive classification with the multivariate coefficient is constructed after providing coefficients with different weights. Four reservoir types are quantitatively delineated, among which the physical properties of Type I reservoirs are the best and the physical properties of Type IV reservoirs are the worst. Combined with the difference in the characteristics of sensitive logging curve responses, four logging parameters, density, neutron, resistivity, and acoustic time difference, are optimized, and different reservoir types are quantitatively identified by Fisher discriminant analysis. Comprehensively considering the change in the vertical sand body structure and reservoir type, the three key parameters of interlayer density, interlayer frequency, and reservoir thickness are selected, and the comprehensive evaluation index N of reservoir quality is innovatively constructed. The proposed evaluation index effectively decouples lithological and petrophysical variations, refining reservoir quality assessments for enhanced exploration and production strategies. The greater the N value is, the better the quality of the oil layer. The smaller the N value is, the thinner the oil layer, the more developed the interlayer, and the worse the oil layer quality. The N index exhibits a strong correlation with production characteristics, indicating that the method has effectively evaluated reservoir quality and provided a theoretical basis for targeting favorable areas.

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Publication Details

Journal
Geofluids
Published
2025-01-01
DOI
https://doi.org/10.1155/gfl/7745871
Citations
1
Primary Topic
Hydrocarbon exploration and reservoir analysis
Type
article
Field-Weighted Citation Impact
0.86

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Comprehensive Evaluation Method of the Tight Oil Reservoir Quality in the Ordos Basin

Xinju Liu, Peng Song, Haiyang Yu, Shuheng Li et al.
1 citations
Geofluids
Hydrocarbon exploration and reservoir analysis
0.86
article

Comprehensive Evaluation Method of the Tight Oil Reservoir Quality in the Ordos Basin

Xinju Liu, Peng Song, Haiyang Yu, Shuheng Li, Yan Zhou, Shuxun Zhou, Jian Shi, Yang Wei-guo
article en
1 citations

Abstract

The Wuqi area of the Ordos Basin boasts significant resource potential in the Chang 8 member of the Yanchang Formation. However, under the dual control of lithology and physical properties, reservoirs are generally dense and heterogeneous, and the quality of the oil layer changes rapidly, which brings difficulties to the optimization of favorable areas. To evaluate the reservoir quality more accurately, based on core observations, and logging and dynamic data analysis, combined with casting thin sections, scanning electron microscopy, high‐pressure mercury injection, nuclear magnetic resonance, and other related experiments, different reservoir types and characteristics were analyzed, and a comprehensive method for evaluating the reservoir quality was established. There are three types of sand body structures in the shallow‐water delta of Chang 8 in the study area, including the continuous superposition type, interval superposition type, and lateral single‐layer type. They mainly experienced diagenesis, such as compaction, cementation, and dissolution. Among these, porosity loss in the Chang 8 reservoir due to compaction and cementation reached 79.3%, consistent with trends observed in other continental tight oil plays such as the Songliao and Junggar Basins, while the improvement in physical properties due to dissolution was minimal. The main parameters influencing different reservoir types are optimized, and the comprehensive classification with the multivariate coefficient is constructed after providing coefficients with different weights. Four reservoir types are quantitatively delineated, among which the physical properties of Type I reservoirs are the best and the physical properties of Type IV reservoirs are the worst. Combined with the difference in the characteristics of sensitive logging curve responses, four logging parameters, density, neutron, resistivity, and acoustic time difference, are optimized, and different reservoir types are quantitatively identified by Fisher discriminant analysis. Comprehensively considering the change in the vertical sand body structure and reservoir type, the three key parameters of interlayer density, interlayer frequency, and reservoir thickness are selected, and the comprehensive evaluation index N of reservoir quality is innovatively constructed. The proposed evaluation index effectively decouples lithological and petrophysical variations, refining reservoir quality assessments for enhanced exploration and production strategies. The greater the N value is, the better the quality of the oil layer. The smaller the N value is, the thinner the oil layer, the more developed the interlayer, and the worse the oil layer quality. The N index exhibits a strong correlation with production characteristics, indicating that the method has effectively evaluated reservoir quality and provided a theoretical basis for targeting favorable areas.

GeofluidsVol. 2025(1)
Petro-Canada (CA), China University of Petroleum, Beijing (CN), Research Institute of Petroleum Exploration and Development (CN), Oil and Gas Center (CN), China National Petroleum Corporation (China) (CN)
National Natural Science Foundation of China, Ministry of Science and Technology of the People's Republic of China, National Science and Technology Major Project
Openalex Percentile: Top 31%
Hydrocarbon exploration and reservoir analysis
0.86
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