The aim of this work is to present an integrated workflow for the one-dimensional (1-D) analysis of pore-pressure (PP) prediction and mud-weight window (MWW) for sub-salt well sections as well as high-angle inclined well sections. In this integrated workflow, empirical information, such as measured data and records of drilling events from offset wells, plays an essential role in the prediction of PP and MWW at the target well, along with a set of theoretical equations. The major steps in the workflow include the following: 1) With given data from a set of offset wells and a given location for a target well, prediction analysis of PP and MWW are performed with logging data and various measured data from offset wells first. These calculations and calibrations with known data from offset wells generate the values of model parameters for this field, and, thus, the results are empirical. These empirical values of model parameters will be used for subsequent calculations of PP and MWW at target well locations. 2) The tops-table method, which performs depth-shift calculations is used for extrapolating/interpolating gamma ray and sonic logging data from offset wells to the target well location. 3) With logging data generated using the tops-table method and the empirical model data, PP and MWW can be obtained at the target well location. A practical case using the workflow introduced here is also presented. This case is from an oil field in deepwater Gulf of Mexico.


Pore-pressure (PP) prediction and mud-weight window design (MWW) are two of the most popular topics in the area of drilling geomechanics. There are plenty of works on these topics done by various researchers [1][2][3][4][5].

For pore pressure prediction, Mouchet and Mitchell [1] introduced major methods used in the prediction of pore pressure, such as the Eaton Method, Ratio Method, etc. Jones, Matthews, and Standifird [2] introduced their work on pore-pressure prediction with basin modeling. Sayers and Woodward [3] reported their work on porepressure prediction with focus on techniques for using seismic data for accurate results. For brevity purposes, the general principle of pore pressure prediction via the Eaton Method is just briefly reviewed.

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