Study of the Impact of Hydrocarbon Fluid Distribution on Reservoir Electrical Resistivity
Unconventional oil and gas reservoirs have complex geological structures, and very often consists of dense fracture network. The charging and migration of hydrocarbon fluids within it also exhibit heterogeneity and anisotropy. In the oil and gas exploration process, geophysical parameters such as resistivity are widely used for inversion to estimate the proportion of hydrocarbons and other components. However, establishing the relationship between hydrocarbon distribution and equivalent resistivity is the foundation for improving the accuracy of inversion predictions. Based on pore-scale multiphase flow simulation and tensor resistivity analysis methods, we can simulate the overall migration process of hydrocarbon fluids in fractured media and calculate changes in resistivity. The results indicate a correlation between the direction of hydrocarbon charging and changes in the equivalent resistivity of the medium. In order to predict the migration paths of hydrocarbons and the orientation of medium fractures, we change the angle of the factures to observe the effect of hydrocarbon injection on the effective resistivity of the medium. Based on the observed results, we construct inversion models for the variation of resistivity at different angles. This work is expected to improve the accuracy of resistivity inversion, determine the oil and gas formation patterns, and optimize oil and gas extraction strategies, provide theoretical references for related fields.
Authors
- Bowen Ling (ORCID: https://orcid.org/0000-0002-3218-4807)
- Chen Guo (ORCID: https://orcid.org/0000-0001-7049-4403)
- Tian Hua Zou
Institutions
- Chang'an University (CN)
- Institute of Mechanics (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Published
- 2024-08-16
- DOI
- https://doi.org/10.1109/aces-china62474.2024.10699902
- Primary Topic
- Oil and Gas Production Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation