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The productivity segmented calculation model of perforated horizontal wells considering whether to penetrate the contaminated zone

Authors :
Shuangshuang Zhang
Kangliang Guo
Haoran Yang
Xinchen Gao
Source :
Frontiers in Earth Science, Vol 11 (2023)
Publication Year :
2023
Publisher :
Frontiers Media S.A., 2023.

Abstract

Perforation technology is often used to improve the productivity of horizontal wells in oilfield exploitation. During the perforation process, the formation seepage mode and productivity will change accordingly whether the contaminated zone is shot through. If we continue to use the previous productivity formula, it will cause a large calculation error and bring economic loss to the development of oil and gas fields. Firstly, based on the principle of equivalent seepage resistance, the reservoir-hole inflow profile in these two cases is analyzed in detail, and the reservoir-hole seepage model is constructed in different regions. The perforated horizontal well section is divided into N micro-unit sections, and the pressure drop model in the wellbore is constructed using the fluid mechanics theory. A new perforated horizontal well productivity prediction model is then created by coupling the reservoir-hole seepage model with the pressure drop model in the wellbore as a whole to accurately reflect the production performance of the perforated horizontal well. Through comparison and verification, it is concluded that the calculation results of the model are more precise, which can greatly reduce the productivity error. This method is reasonable and practical. When the oilfield’s actual well data is substituted into this model, it is discussed and analyzed that the reservoir’s physical characteristics, contamination level, and perforation completion parameters all have an impact on the productivity of horizontal wells, with the original formation’s permeability and reservoir contamination thickness having the most pronounced effects. These findings may effectively direct the design of technological processes and performance impact prediction.

Details

Language :
English
ISSN :
22966463
Volume :
11
Database :
Directory of Open Access Journals
Journal :
Frontiers in Earth Science
Publication Type :
Academic Journal
Accession number :
edsdoj.87f90bb5654439f8f785800c7cebe44
Document Type :
article
Full Text :
https://doi.org/10.3389/feart.2023.1270662