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. Processes2023, 11, 2010.
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. Processes 2023, 11, 2010.
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. Processes2023, 11, 2010.
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. Processes 2023, 11, 2010.
Abstract
Comparison with 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 equivalent depth method, Eaton method, Fillippone formula, and its 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 line, which leads to low prediction accuracy in space. To address this issue, a method combining the Eaton method and Collocated cokriging is proposed. 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.
Environmental and Earth Sciences, Geophysics and Geology
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