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May 25, 2026ProcessesOpen Access

Correction: Zhou et al. A Mathematical Model Accounting for Pore Pressure Generation in Sedimentary Basins. Processes 2026, 14, 297

Lihao Zhou Liangbin Dou Chengyun Ma Shanshan Quan Fengtao Qu Wenxuan Kou Chenbo Gu Chi Zhao Baiqi Mao Kai Zhao Yanfang Gao

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Key Points

To acknowledge the correction of authorship in the previously published mathematical model regarding pore pressure generation.
Correction of author list and attribution in a previously published mathematical model.
Review of authorship criteria to align with publication standards.
Yanfang Gao has been officially added as an author in the corrected publication.

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Implication

Correction notes additional author Yanfang Gao in mathematical modeling of pore pressure in sedimentary basins, suggesting refinement of findings.

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Cite This Study

Zhou et al. (2026) studied this question.

synapsesocial.com/papers/6a168a7f0c924ddd1bd59292 https://doi.org/10.3390/pr14111704

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Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1A Mathematical Model Accounting for Pore Pressure Generation in Sedimentary BasinsOriginal Research · 2026 · 1 citations
2Correction: Liu et al. Quantitative Evaluation of the Formation and Evolution of Underpressure in Tight Sandstone of the Upper Paleozoic Shanxi Formation, Ordos Basin. Appl. Sci. 2026, 16, 475Original Research · 2026
3Correction: Chang et al. A Novel Three-Zone Material Balance Model for Zone Reserves and EUR Analysis in Shale Oil Reservoirs. Energies 2026, 19, 998Original Research · 2026
4Correction: Sun et al. Tectonic Controls on Late Paleozoic Shale Gas Preservation in Western Shandong, China. J. Mar. Sci. Eng. 2025, 13, 11212025
5Correction: Sun et al. Evolution Mechanism of Permeability Characteristics of Shale Reservoirs During Supercritical Fluid Fracturing and Displacement. Appl. Sci. 2025, 15, 10043Original Research · 2026

Correction: Mahmoud et al. A New Empirical Correlation for Pore Pressure Prediction Based on Artificial Neural Networks Applied to a Real Case Study. Processes 2026, 12, 6642026
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