LAPSE:2024.1008
Published Article

LAPSE:2024.1008
New Method for Capacity Evaluation of Offshore Low-Permeability Reservoirs with Natural Fractures
June 7, 2024
Abstract
In recent years, the development of two offshore low-permeability oil fields has revealed unexpected challenges. The actual productivity of these fields significantly deviates from the designed capacity. Some wells even outperform the expectations for low-permeability limestone fields. This discrepancy primarily stems from a lack of accurate understanding of natural fractures before and after drilling, resulting in substantial errors in capacity assessment. This paper addresses these challenges by proposing a new production capacity model and evaluation method for both vertical and horizontal wells in low-permeability limestone reservoirs. The method leverages logging curve data, incorporating vertical gradation and fractal analysis to effectively represent the fracture’s complexity and connectivity. It uniquely considers factors such as fracture fractal dimensions, threshold pressure, and stress sensitivity, significantly enhancing prediction accuracy. Furthermore, by analyzing the longitudinal gradient in logging curves, the method effectively identifies strong heterogeneity, leading to more accurate capacity evaluations in actual fields. The results demonstrate that our model reduces the average prediction error to less than 15%, markedly outperforming traditional methods. Calculation results of the newly developed capacity formula align closely with actual production data and tracer test results, showcasing its practical applicability and potential for widespread use. This study notably advances the evaluation of reasonable production capacity in similar offshore reservoirs.
In recent years, the development of two offshore low-permeability oil fields has revealed unexpected challenges. The actual productivity of these fields significantly deviates from the designed capacity. Some wells even outperform the expectations for low-permeability limestone fields. This discrepancy primarily stems from a lack of accurate understanding of natural fractures before and after drilling, resulting in substantial errors in capacity assessment. This paper addresses these challenges by proposing a new production capacity model and evaluation method for both vertical and horizontal wells in low-permeability limestone reservoirs. The method leverages logging curve data, incorporating vertical gradation and fractal analysis to effectively represent the fracture’s complexity and connectivity. It uniquely considers factors such as fracture fractal dimensions, threshold pressure, and stress sensitivity, significantly enhancing prediction accuracy. Furthermore, by analyzing the longitudinal gradient in logging curves, the method effectively identifies strong heterogeneity, leading to more accurate capacity evaluations in actual fields. The results demonstrate that our model reduces the average prediction error to less than 15%, markedly outperforming traditional methods. Calculation results of the newly developed capacity formula align closely with actual production data and tracer test results, showcasing its practical applicability and potential for widespread use. This study notably advances the evaluation of reasonable production capacity in similar offshore reservoirs.
Record ID
Keywords
capacity evaluation, fractal parameters, natural fractures, offshore low-permeability reservoirs, threshold pressure gradient
Subject
Suggested Citation
Wang K, Xie M, Liu W, Li L, Liu S, Huang R, Feng S, Liu G, Li M. New Method for Capacity Evaluation of Offshore Low-Permeability Reservoirs with Natural Fractures. (2024). LAPSE:2024.1008
Author Affiliations
Wang K: State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610500, China; Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China [ORCID]
Xie M: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Liu W: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Li L: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Liu S: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Huang R: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Feng S: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Liu G: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Li M: State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610500, China
Xie M: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Liu W: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Li L: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Liu S: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Huang R: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Feng S: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Liu G: Nanhai East Petroleum Research Institute, Shenzhen Branch of CNOOC Limited, Shenzhen 518000, China
Li M: State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610500, China
Journal Name
Processes
Volume
12
Issue
2
First Page
347
Year
2024
Publication Date
2024-02-06
ISSN
2227-9717
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Original Submission
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PII: pr12020347, Publication Type: Journal Article
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LAPSE:2024.1008
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https://doi.org/10.3390/pr12020347
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[v1] (Original Submission)
Jun 7, 2024
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