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A Three-Dimensional Model for the Formation Pressure in Wellbores under Uncertainty

Jiawei Zhang*, Qing Wang, Hongchun Huang, Haige Wang, Guodong Ji, Meng Cui, Hongyuan Zhang

Strategic Planning and Technical Support Institute, CNPC Engineering Technology R&D Co., Ltd., Beijing, 102206, China

* Corresponding Author: Jiawei Zhang. Email: email

(This article belongs to the Special Issue: Fluid Flow and Materials Strength related to the Wellbore Safety)

Fluid Dynamics & Materials Processing 2023, 19(9), 2305-2314. https://doi.org/10.32604/fdmp.2023.026304

Abstract

Formation pressure is the key parameter for the analysis of wellbore safety. With increasing drilling depth, however, the behavior of this variable becomes increasingly complex. In this work, a 3D model of the formation pressure under uncertainty is presented. Moreover a relevant algorithm is elaborated. First, the logging data of regional key drilling wells are collected and a one-dimensional formation pressure profile along the well depth is determined. Then, a 3D model of regional formation pressure of the hierarchical group layer is defined by using the Kriging interpolation algorithm relying on a support vector machine (SVM) and the formation pressure of the drilled wells. To validate the method, the formation pressure of one pre-drilled well is compared with the well logging results. The comparison reveals that the maximum relative error is less than 4.5%. The software based on this model is complemented by a computer visualization technology, which provides a relevant tool for understanding and analyzing the 3D formation pressure. The outcomes of this study are intended to support the characterization of areas with missing or poor 3D seismic data and provide more accurate information for the analysis of wellbore integrity.

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Cite This Article

Zhang, J., Wang, Q., Huang, H., Wang, H., Ji, G. et al. (2023). A Three-Dimensional Model for the Formation Pressure in Wellbores under Uncertainty. FDMP-Fluid Dynamics & Materials Processing, 19(9), 2305–2314. https://doi.org/10.32604/fdmp.2023.026304



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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