LAPSE:2023.36552
Published Article
LAPSE:2023.36552
Research on Formation Pressure Prediction Method for Ultra-Deep Tight Sandstone Based on Collocated Cokriging
Qiang Wei, Yaoting Lin, Gang Gao, Zhixian Gui, Zhendong Wu, Jiaqi Liu
August 3, 2023
Compared to conventional reservoirs, the prediction of pressure in ultra-deep tight sandstone formations is difficult. The prediction of seismic pressure is more challenging than well-logging pressure prediction. The main methods for seismic pressure prediction include the equivalent depth method, Eaton method, Fillippone formula, and modified versions. Among them, the Eaton method is widely used and has good effectiveness. However, this method relies on difficult-to-obtain normal compaction trend lines, which leads to low prediction accuracy in space. To address this issue, a method combining the Eaton method and collocated cokriging is proposed. Herein, the Eaton formula is used to predict formation pressure at the well, with compressional wave velocity as the covariate for predicting the main variable—formation pressure. By simulating the shear wave velocity based on seismic compressional wave velocity, the influence of various parameters on the prediction results is analyzed, and the accuracy of this method is verified by comparing it with other methods. The proposed method is then applied to predict formation pressure in the ultra-deep formations of the Junggar Basin. The simulation results show that the collocated cokriging method achieves higher planar accuracy and better matches the experimental expectations in terms of prediction results. The application results also demonstrate the scientific effectiveness of the combined method, which has achieved good results in practical production applications.
Keywords
cokriging method, collocated cokriging, Eaton method, formation pressure prediction, variation function
Suggested Citation
Wei Q, Lin Y, Gao G, Gui Z, Wu Z, Liu J. Research on Formation Pressure Prediction Method for Ultra-Deep Tight Sandstone Based on Collocated Cokriging. (2023). LAPSE:2023.36552
Author Affiliations
Wei Q: Key Laboratory of Exploration Technologies for Oil and Gas Resources, Yangtze University, Ministry of Education, Wuhan 430100, China
Lin Y: Department of Mathematics and Statistics, University of Calgary, 2500 University Dr. NW, Calgary, AB T2N 1N4, Canada
Gao G: Key Laboratory of Exploration Technologies for Oil and Gas Resources, Yangtze University, Ministry of Education, Wuhan 430100, China
Gui Z: Key Laboratory of Exploration Technologies for Oil and Gas Resources, Yangtze University, Ministry of Education, Wuhan 430100, China
Wu Z: Dagang Branch, GRI, BGP Inc., CNPC, Tianjin 300280, China
Liu J: Key Laboratory of Exploration Technologies for Oil and Gas Resources, Yangtze University, Ministry of Education, Wuhan 430100, China
Journal Name
Processes
Volume
11
Issue
7
First Page
2010
Year
2023
Publication Date
2023-07-05
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr11072010, Publication Type: Journal Article
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LAPSE:2023.36552
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doi:10.3390/pr11072010
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Aug 3, 2023
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Aug 3, 2023
 
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Calvin Tsay
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