A New Characterization Method for Dynamic Connectivity Field Between Injection and Production Wells in Offshore Reservoir

Connectivity between injection and production wells is critical for efficient oil production, especially in offshore reservoirs where the number of wells is limited. Though several methods for point-to-point connectivity have been developed, there is a lack of characterization methods for the dynamic connectivity field, which describes connectivity for the whole reservoir. Based on the concept of pore-scale connectivity, this work proposes a multi-parameter integrated model to represent the connectivity field. The calculated connectivity is consistent with simulated streamlines between wells. Key influencing factors, including permeability heterogeneity, injection rate and viscosity ratio on the connectivity field, are systematically analyzed. The established method is then applied to construct the connectivity field in an offshore reservoir. First, a point cloud is applied to represent the reservoir characteristics. Then, the connection network is established, with parameters obtained from history matching. In this way, the point-to-point connectivity is transformed into a connectivity field. The connectivity between injection and production wells is validated by comparing with the on-site tracer test and measured allocation factor of water injection. This approach holds significant potential for enhancing the efficiency of water injection and optimizing offshore reservoir management.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2025-05-02
DOI
https://doi.org/10.3390/jmse13050906
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

A New Characterization Method for Dynamic Connectivity Field Between Injection and Production Wells in Offshore Reservoir

Fankun Meng, Hui Zhao, Mengna Cheng, Yuzhou Hu et al.
Journal of Marine Science and Engineering
Reservoir Engineering and Simulation Methods
article

A New Characterization Method for Dynamic Connectivity Field Between Injection and Production Wells in Offshore Reservoir

Fankun Meng, Hui Zhao, Mengna Cheng, Yuzhou Hu, Fengshuang Du, Changchun Guo, Tao Li
article en

Abstract

Connectivity between injection and production wells is critical for efficient oil production, especially in offshore reservoirs where the number of wells is limited. Though several methods for point-to-point connectivity have been developed, there is a lack of characterization methods for the dynamic connectivity field, which describes connectivity for the whole reservoir. Based on the concept of pore-scale connectivity, this work proposes a multi-parameter integrated model to represent the connectivity field. The calculated connectivity is consistent with simulated streamlines between wells. Key influencing factors, including permeability heterogeneity, injection rate and viscosity ratio on the connectivity field, are systematically analyzed. The established method is then applied to construct the connectivity field in an offshore reservoir. First, a point cloud is applied to represent the reservoir characteristics. Then, the connection network is established, with parameters obtained from history matching. In this way, the point-to-point connectivity is transformed into a connectivity field. The connectivity between injection and production wells is validated by comparing with the on-site tracer test and measured allocation factor of water injection. This approach holds significant potential for enhancing the efficiency of water injection and optimizing offshore reservoir management.

Journal of Marine Science and EngineeringVol. 13(5)
Sinopec (China) (CN), Yangtze University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 88%
Reservoir Engineering and Simulation Methods
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A New Characterization Method for Dynamic Connectivity Field Between Injection and Production Wells in Offshore Reservoir — Fankun Meng, Hui Zhao, et al. · Journal of Marine Science and Engineering (2025) | TGRS Research Map | TGRS