LAPSE:2024.0942
Published Article
LAPSE:2024.0942
Modeling of Quantitative Characterization Parameters and Identification of Fluid Properties in Tight Sandstone Reservoirs of the Ordos Basin
June 7, 2024
The Ordos Basin has abundant resources in its tight sandstone reservoirs, and the use of well logging technology stands out as a critical element in the exploration and development of these reservoirs. Unlike conventional reservoirs, the commonly used interpretation models are not ideal for evaluating tight sandstone reservoirs through logging. In order to accurately evaluate parameters and identify fluid properties in the tight sandstone reservoirs of the Ordos Basin, we propose the adaption of conventional logging curves. This involves establishing an interpretation model that integrates the response characteristics of logging curves to tight sandstone reservoirs in accordance with the principles of logging. In this approach, we create interpretation models specifically for shale content, porosity, permeability, and saturation within the tight sandstone reservoir. Using the characteristics of the logging curves and their responses, we apply a mathematical relationship to link these parameters and create a template for identifying fluid properties within tight sandstone reservoirs. The average absolute errors of the new multi-parameter weighting method shale content interpretation model and porosity classification saturation interpretation model for quantitative evaluation of reservoir shale content and oil saturation are small, and the accuracy meets the production requirements. In this paper, the four-step method is used to identify the fluid properties of tight sandstone reservoirs step by step, which is to use the interrelationship between curves, eliminate the useless information, enhance the useful information, and finally solve the problem of identifying the fluid properties of tight sandstone reservoirs, which is difficult to identify, and realize the linear discrimination of the interpretation standard, which improves the accuracy of interpretation. The proven multi-information, four-step, step-by-step fluid property identification template has an accuracy of more than 90%. The interpretation model has been applied to 20 wells on the block with a compliance rate of 95.23%, providing the basis for accurately establishing the tight sandstone interpretation standard. The newly introduced log evaluation approach for tight sandstone reservoirs effectively overcomes the technical hurdles that have previously hindered the evaluation of such reservoirs in the Ordos Basin. This method is suitable for wide application and can be used for quantitative evaluation of tight sandstone reservoirs in different regions.
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Keywords
fluid property identification, logging interpretation, model, siliciclastic reservoirs, tight sandstone, unconventional petroleum resources
Subject
Suggested Citation
Xu B, Wang Z, Song T, Zhang S, Peng J, Wang T, Chen Y. Modeling of Quantitative Characterization Parameters and Identification of Fluid Properties in Tight Sandstone Reservoirs of the Ordos Basin. (2024). LAPSE:2024.0942
Author Affiliations
Xu B: School of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China; Key Laboratory of Special Stimulation Technology for Oil and Gas Fields in Shaanxi Province, Xi’an 710065, China [ORCID]
Wang Z: Research Institute of Shannxi Yanchang Petroleum (Group) Co., Ltd., Xi’an 710065, China
Song T: No.11 Oil Production Plant, Changqing Oilfield Company, PetroChina, Qingyang 745000, China
Zhang S: Research Institute of Shannxi Yanchang Petroleum (Group) Co., Ltd., Xi’an 710065, China
Peng J: School of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China; Key Laboratory of Special Stimulation Technology for Oil and Gas Fields in Shaanxi Province, Xi’an 710065, China
Wang T: School of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China; Key Laboratory of Special Stimulation Technology for Oil and Gas Fields in Shaanxi Province, Xi’an 710065, China
Chen Y: School of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China; Key Laboratory of Special Stimulation Technology for Oil and Gas Fields in Shaanxi Province, Xi’an 710065, China
Wang Z: Research Institute of Shannxi Yanchang Petroleum (Group) Co., Ltd., Xi’an 710065, China
Song T: No.11 Oil Production Plant, Changqing Oilfield Company, PetroChina, Qingyang 745000, China
Zhang S: Research Institute of Shannxi Yanchang Petroleum (Group) Co., Ltd., Xi’an 710065, China
Peng J: School of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China; Key Laboratory of Special Stimulation Technology for Oil and Gas Fields in Shaanxi Province, Xi’an 710065, China
Wang T: School of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China; Key Laboratory of Special Stimulation Technology for Oil and Gas Fields in Shaanxi Province, Xi’an 710065, China
Chen Y: School of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China; Key Laboratory of Special Stimulation Technology for Oil and Gas Fields in Shaanxi Province, Xi’an 710065, China
Journal Name
Processes
Volume
12
Issue
2
First Page
278
Year
2024
Publication Date
2024-01-26
ISSN
2227-9717
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Original Submission
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PII: pr12020278, Publication Type: Journal Article
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LAPSE:2024.0942
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https://doi.org/10.3390/pr12020278
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[v1] (Original Submission)
Jun 7, 2024
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Jun 7, 2024
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