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The AAPG/Datapages Combined Publications Database
GCAGS Transactions
Abstract
Applying Rock Physic Models for Optimized Pore Pressure Prediction
Abstract
There are several drilling challenges when operating in the deepwater Gulf of Mexico and in many other basins globally. One of the significant challenges related to drilling safe wells is to produce accurate pre-drill pore pressure estimates.
Issues related to produce accurate pre-drill pore pressure estimates in the Gulf of Mexico, and elsewhere, can amongst others, be related to relative changes in clay volume (vclay) and/or total organic carbon (TOC), factors that are often not accounted for in traditional pore pressure prediction techniques (e.g., Equivalent Depth Method and Eaton Ratio Method) and/or workflows. Traditional pore pressure prediction techniques rely on the assumption that shales are at their current maximum burial depth, have uniform composition (vclay) and have not undergone significant clay diagenesis or other cementation (e.g., quartz cementation). Rock physics models (RPMs) such as the clay-dependent pore pressure prediction model presented in Vernik (2011) and in Vernik (2016) can take variable clay content into account. In addition, the presence of organic matter in excess amounts in shale formations that have not been exposed to the pressure-temperature conditions of the oil window can cause marked overprediction of pore pressure in thermally immature mudrocks. Green and Vernik (2020) presented a case study from the Kimmeridge Clay Formation in the North Sea with TOC content in the range of 2–12% where implementation of bulk density and sonic velocity log corrections in organic-rich shales prior to performing any pore pressure prediction dramatically improved pore pressure estimates.
The two case studies presented in this paper illustrate workflows designed to account for the lithological variability associated with clay and/or TOC content and its effect on wireline response through a series of rock physics models. Accounting for these changes within a pore pressure prediction workflow has the potential to lead to a more robust pressure model helping to decrease uncertainty and thereby significantly reduce the risk of encountering unexpected pressures while drilling.
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