Eaton Exponent Sensitivity in Sonic and Resistivity Log-Based Pore Pressure Prediction: Supporting Sustainable Energy Exploration in South Sembakung Field, Indonesia
DOI:
10.29303/jppipa.v12i5.15205Published:
2026-05-25Downloads
Abstract
Accurate pore pressure prediction is critical for safe drilling operations during early exploration when direct measurements are limited. The Eaton method is widely applied, yet the exponent (n) is treated as a fixed constant without sensitivity evaluation under normal pore pressure regimes. This study quantifies the effect of exponent variation using sonic and resistivity logs from Well X, South Sembakung Field, Tarakan Basin. Normal Compaction Trends (NCTs) were constructed from shale intervals (GR ≥ 75 API). NCT quality differs substantially between log types with R² = 0.79 for sonic versus R² = 0.076 for resistivity, causing residual deviations amplified nonlinearly by n, making exponent selection consequential even under normal pressure. Systematic variation (n = 2.50–3.50 for sonic; n = 1.00–2.00 for resistivity) was validated against three DST measurements using Mean Absolute Error (MAE). Sonic predictions yielded MAE of 309.89–402.40 psi, outperforming resistivity predictions (584.50–995.85 psi), reflecting superior NCT stability. Resistivity errors reflect petrophysical heterogeneity including formation water salinity and clay mineral content. Lower n values mechanically converge predictions toward the hydrostatic baseline as a mathematical consequence of the Eaton formulation. The Eaton exponent must therefore be treated as a site-specific calibration parameter, not a universal constant.
Keywords:
Eaton method Exponent sensitivity Normal pressure regime Pore pressure prediction Resistivity log Sonic logReferences
Asfha, D. T., Gebretsadik, H. T., Latiff, A. H. A., & Rahmani, O. (2024). Predictive Pore Pressure Modeling Using Well-Log Data in the West Baram Delta, Offshore Sarawak Basin, Malaysia. Geomechanics and Geophysics for Geo-Energy and Geo-Resources, 10, 196. https://doi.org/10.1007/s40948-024-00903-5
Asquith, G. B., & Krygowski, D. (2004). Basic well log analysis. AAPG.
Avasthi, D., Islam, A., & Guo, B. (2022). Improving Pore Pressure Prediction Using Resistivity and Sonic Logs in Structurally Complex Settings. Journal of Natural Gas Science and Engineering, 104, 104654. https://doi.org/10.1016/j.jngse.2022.104654
Bjørlykke, K. (2015). Petroleum Geoscience: From Sedimentary Environments to Rock Physics. Springer.
Bourgoyne, A. T., Millheim, K. K., Chenevert, M. E., & Young, F. S. (1991). Applied Drilling Engineering. Society of Petroleum Engineers.
Bowers, G. L. (1995). Pore Pressure Estimation from Velocity Data: Accounting for Overpressure Mechanisms Besides Undercompaction. SPE Drilling & Completion, 10(2), 89–95. https://doi.org/10.2118/27488-PA
Eaton, B. A. (1975). The Equation for Geopressure Prediction from Well Logs. Proceedings of the SPE Annual Technical Conference and Exhibition (SPE Paper 5544-MS. https://doi.org/10.2118/5544-MS
Ehsan, M., Manzoor, U., Chen, R., Hussain, M., Abdelrahman, K., Radwan, A. E., Ullah, J., Iftikhar, M. K., & Arshad, F. (2024). Pore Pressure Prediction Based on Conventional Well Logs and Seismic Data Using an Advanced Machine Learning Approach. Journal of Rock Mechanics and Geotechnical Engineering. https://doi.org/10.1016/j.jrmge.2024.09.049
Fjaer, E., Holt, R. M., Horsrud, P., Raaen, A. M., & Risnes, R. (2008). Petroleum Related Rock Mechanics (2nd ed.). Elsevier.
Gholami, S., & Soltani, M. (2021). Well Log-Based Model for Pore Pressure Prediction Integrating Shale Compaction and Sonic Data. Journal of Petroleum Science and Engineering, 203, 108587. https://doi.org/10.1016/j.petrol.2021.108587
Khaled, S., Mahmoud, M., Elkatatny, S., & Abdulraheem, A. (2022). New Models for Predicting Pore Pressure and Fracture Pressure While Drilling. ACS Omega, 7(20), 17455–17467. https://doi.org/10.1021/acsomega.2c01602
Khan, F., & Ahmad, S. (2023). Quantifying Uncertainty in Pore Pressure Prediction Using Conventional Well Logs. Journal of Petroleum Exploration and Production Technology, 13, 2843–2858. https://doi.org/10.1007/s13202-023-01909-7
Li, W., Zhang, Y., Liu, H., & Chen, X. (2025). Pore Pressure Prediction Using Improved Eaton Method: A Case Study in the Luzhou Block, Sichuan Basin. Energies, 18(10), 2647. https://doi.org/10.3390/en18102647
Magara, K. (1978). Compaction and Fluid Migration. Elsevier.
Moghadam, A., & Jahanbakhshi, R. (2022). Comparison of Sonic and Resistivity Logs for Accurate Pore Pressure Prediction in Deep Marine Clastics. Marine and Petroleum Geology, 147, 105763. https://doi.org/10.1016/j.marpetgeo.2022.105763
Nelson, J. D., & Miller, D. J. (1992). Expansive Soils (Problems and Practice in Foundation and Pavement Engineering). John Wiley and Sons, Inc.
O’Connor, S., Ramdhan, A. M., Arifin, A., & Ellis, A. C. (2023). The Resistivity Log and Its Role in Understanding Sediment Unloading in the Lower Kutai Basin, Indonesia. Indonesian Journal on Geoscience, 10(3), 379–392. https://doi.org/10.17014/ijog.10.3.379-392
Osborne, M. J., & Swarbrick, R. E. (1998). Mechanisms for Generating Overpressure in Sedimentary Basins: A Reevaluation: Reply. AAPG Bulletin, 82(12), 2270–2271. https://doi.org/10.1306/00AA7F0E-1730-11D7-8645000102C1865D
Rider, M., & Kennedy, M. (2011). The Geological Interpretation of Well Logs (3rd Ed.). Rider-French Consulting.
Sayers, C. M. (2013), The Effect of Anisotropy on the Young's Moduli and Poisson's Ratios of Shales. Geophysical Prospecting, 61, 416-426. https://doi.org/10.1111/j.1365-2478.2012.01130.x
Sclater, J. G., & Christie, P. A. F. (1980). Continental Stretching: An Explanation of the Post-Mid-Cretaceous Subsidence of the Central North Sea Basin, J. Geophys. Res., 85(B7), 3711–3739, doi:10.1029/JB085iB07p03711
Shabangu, P. P., Dlamini, S., & Nxumalo, N. (2025). Pore Pressure Prediction Using Eaton and Bowers Methods: A Comparative Evaluation in Clastic Formations. Applied Sciences, 15(13), 7154. https://doi.org/10.3390/app15137154
Shatyrbayeva, A. (2024). Drilling-Data-Calibrated Shale Compaction Models for Improved Pore Pressure Evaluation. Petroleum Geoscience, 30(3), 2024–014. https://doi.org/10.1144/petgeo2024-014
Terzaghi, K. (1943). Theoretical Soil Mechanics. John Wiley & Sons.
Zhang, J. (2011). Pore Pressure Prediction from Well Logs: Methods, Modifications, and New Approaches. Earth-Science Reviews, 108(1–2), 50–63. https://doi.org/10.1016/j.earscirev.2011.06.001
Zhang, J., Huang, Z., & Chen, Y. (2021). A Comprehensive Sensitivity Analysis of Eaton-Based Pore Pressure Prediction in Shale Reservoirs. Journal of Petroleum Science and Engineering, 197, 108204. https://doi.org/10.1016/j.petrol.2020.108204
Zoback, M. D. (2010). Reservoir Geomechanics. Cambridge University Press.
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