EconPapers    
Economics at your fingertips  
 

Research on the Mechanism and Prediction Model of Pressure Drive Recovery in Low-Permeability Oil Reservoirs

Haicheng Liu () and Binshan Ju ()
Additional contact information
Haicheng Liu: School of Energy Resources, China University of Geosciences (Beijing), Beijing 100083, China
Binshan Ju: School of Energy Resources, China University of Geosciences (Beijing), Beijing 100083, China

Energies, 2024, vol. 17, issue 21, 1-26

Abstract: China boasts significant reserves of low-permeability oil reservoirs, and the economic and efficient development of these reservoirs plays a crucial role in enhancing oil and gas production. However, the “difficult injection and difficult recovery” issue in low-permeability oil reservoirs is a major challenge. To address this, research is conducted on the mechanism of pressure drive based on the mathematical model of oil-water seepage in low-permeability reservoirs and the model of fracture permeability. The study finds that pressure drive technology, by directly delivering the pressure drive agent deep into the low-permeability reservoir, effectively prevents viscosity loss and adhesion retention of the agent in the near-wellbore area. This technology expands the swept volume, improves oil washing efficiency, replenishes formation energy, and facilitates the gathering and production of scattered remaining oil. For reservoirs with higher permeability, pressure drive yields quick results, and high-pressure water injection can be directly adopted for pressure drive to reduce costs. On the other hand, reservoirs with lower permeability have difficulty in water absorption, and the use of surfactant-based pressure drive can effectively reduce the seepage resistance of the reservoir, enhancing its water absorption capacity and improving development outcomes. Based on the mechanism of pressure drive development, further research is conducted on the production characteristics of pressure drive mines. Addressing the variability in pressure drive effects, big data analysis tools such as SHAP analysis and correlation analysis are employed to evaluate the main controlling factors of pressure drive in both new and old areas. Additionally, non-time series and time series pressure drive production forecasting models are established based on pressure drive data.

Keywords: low-permeability oil reservoirs; main controlling factors; model of fracture permeability; physical simulation; mechanism of pressure drive (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/17/21/5253/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/21/5253/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:17:y:2024:i:21:p:5253-:d:1503915

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:17:y:2024:i:21:p:5253-:d:1503915