A method to reduce the uncertainty of pressure prediction in HPHT prospects: a case study of Onshore Niger Delta depobelt, Nigeria

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Abstract

The search for hydrocarbons has gone beyond shallow hydrostatic reservoirs, necessitating deep drilling beyond known depths in the mature Onshore Niger Delta fields. Often times, the challenge has been the ambiguity in pore pressure prediction beyond the shallow depths where disequilibrium compaction is no longer the active overpressure contributor. This leads to underbalanced drilling with the implication that well drilling is terminated at the occurrence of the first kick, before reaching the target depth. Thus, in this study, the dominant overpressure mechanism is determined by the analyses of velocity, density versus depth cross-plots. The Eaton empirical approach, equivalent depth method (EDM), a deterministic approach, and Bowers velocity–vertical effective stress (Vp–VES) relationship were applied to Vp-sonic log to compare prediction profiles. Pressure data were used to infer geologically consistent Eaton’s exponents and Vp–VES curve for loading and unloading scenarios. The results show that deeper than the approximately 11,000 ft where unloading began, EDM and Eaton’s exponent of 3.0 would fail. However, higher exponents can be adopted for the area at onset of unloading temperatures ranging from 98 to 100 °C. The estimated shale pressure profile from the EDM, Eaton’s exponents and Vp–VES models accurately fit the measured pressure data. In that way, the uncertainty in the prediction can be quantified. Hence, predrill estimates of shale pressures can be generated beyond known depths since the model can be used to transform seismic velocity to formation pressure, thereby ensuring better anticipation of potential risks and cost-effective drilling.

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Asedegbega, J. E., Oladunjoye, M. A., & Nwozor, K. K. (2018). A method to reduce the uncertainty of pressure prediction in HPHT prospects: a case study of Onshore Niger Delta depobelt, Nigeria. Journal of Petroleum Exploration and Production Technology, 8(2), 375–380. https://doi.org/10.1007/s13202-017-0401-8

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