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A m e r i c a

Pore-pressure prediction and wellbore stability in the deep Mexican Gulf of Mexico
JORGE MENDOZA-AMUCHÁSTEGUI, GABRIEL VÁZQUEZ-JIMÉNEZ, MANUEL ESPINOSA-ORTEGA, CELESTINO VALLE-MOLINA, ESTEBAN ALVARADO-HERNÁNDEZ, MARIO GERARDO GARCIA-HERRERA, and RUBÉN NICOLÁS-LÓPEZ, Instituto Mexicano del Petroleo (IMP)

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afe andeconomical exploration drilling largely relies on appropriate analyses and estimation of the overpressures in the subsurface. In contrast, incorrect predictions of these abnormal pressures can cause delays and increase costs due to failures of rock formations, lack of drilling mud circulation, collapse of the casing, and closures for differential pressures. The main advantage of the integral methodologyfor the pore-pressure prediction presented in this article is modeling at two different levels, regional modeling based on the basin model, and local modeling by means of geomechanical models applied to the wellbore stability. Figure 1 illustrates the overall integration of the pore-pressure methodology. The combination of the 3D formation velocities and well-log information allow modeling basinsand geomechanics for wellbore stability. This study also addresses the local modeling for wellbore stability.

Figure 1. Diagram of the pore-pressure methodology.

Methodology Our methodology to predict pore pressure consists of five steps: (1) initial model of migration velocities, (2) automatic, high-density velocity analyses based on maximum amplitude semblance spectra, (3) smoothing ofvelocity analyses, (4) calibration of seismic velocities with well-log velocities, and (5) effective stress calculation based on Eaton’s equation (Zoback, 2007). Prediction of pore pressure was performed at a site in deep waters of the Mexican Gulf of Mexico. Figure 2 shows the process to evaluate the velocities obtained at the site (steps 1 and 2). The seismic information used for velocity analysescovers 25 km2 and consists of prestack time-migrated CDP records. In this study, the pore-pressure prediction was undertaken for locating a delineation well in a water depth of 870 m. The initial velocity model was obtained from the PSTM velocity cube. This model is very helpful in guiding the subsequent velocity analyses. After the velocity model was defined, the parameters to perform the velocityanalyses were optimized. The “high-density picking process” using residual velocity analyses was then carried out. Residual velocity analyses were also performed to fine-tune the interval velocities. All velocity analyses were performed on a CDP by CDP basis. Figure 2b shows the prospective delineation well and the flattened CDP gathers. Figures 2c and 2d present the velocity analyses based onsemblance, including the semblance panel, the selected or picked values of velocity, the uncorrected gathers, and the final NMO-corrected gathers. Figure 3 shows a time-migrated section near the well. The semblance-based velocity analyses were considered adequate since the geologic variations do not seem complex.
702 The Leading Edge June 2009

Figure 2. High-density velocity analyses for pore-pressurepredictions: (a) steps of the high-density velocity analyses; (b) flattened CDP gathers and well location; (c) and (d) examples of semblance panels, picked values of velocity, uncorrected gathers, and final NMOcorrected gathers.

Figure 4 illustrates the smoothing process (step 3) applied to the interval velocities. Figure 4b, a section of interval velocities without smoothing, contains noise anddefinition of geological features is unclear. The smoothing starts with application of a 3D geostatistical filter (variogram-based kriging) to the interval velocity cube. Then, the interval velocity cube is reprocessed, now with median-type filter. Figures 4c and 4d show sections with smoothed interval velocities. Calibration, the fourth step, finds discrepancies between the seismic interval...