Journal
GEOFLUIDS
Volume 2022, Issue -, Pages -Publisher
WILEY-HINDAWI
DOI: 10.1155/2022/5033078
Keywords
-
Categories
Funding
- Natural Science Foundation of Guangxi Province [2016GXNSFBA380180, 2017GXNSFAA198105, 2021GXNSFAA220012]
- Thousands Elite Plan Foundation [GJSF(2019)81]
Ask authors/readers for more resources
This study predicts and characterizes the permeability of Daniudi tight gasfield in China from a new perspective using geoscience data mining algorithms and modeling techniques. The results show that the facies-controlled modeling system based on the hydrodynamic characteristics of tight gas reservoirs effectively improves reservoir prediction accuracy.
Due to poor physical properties and strong heterogeneity of Daniudi tight gasfield (China), traditional methods are not ideal for predicting reservoir permeability. Based on geoscience data mining algorithms and modeling techniques, this parameter is predicted and characterized from a new perspective. The high precision hydraulic unit information was outputted by the BP neural network and the interwell database was predicted by sequential indicator simulation based on the logging and core data, the exponential and power law relationship functions were selected to participate in the construction of the permeability model. The results showed that the facies-controlled modeling system for permeability based on the hydrodynamic characteristics of tight gas reservoirs could effectively improve the accuracy of reservoir prediction, and the logging information in the longitudinal direction and the facies information in the plane were combined by the hydraulic unit.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available