Detection and mapping of overpressure subsurface formations are of prime importance in exploration and appraisal drilling. Such a phenomenon can cause serious problems with borehole stability especially in areas subjected to severe tectonic stresses and presents significant drilling safety threats. The main causes of overpressure are undercompaction and fluid expansion. Fluid expansion is the result of hydrocarbon maturation in high temperature formations, aquathermal pressuring, and clay diagenesis. Careful planning before drilling is required for safe and cost-effective drilling. Seismic velocities generally play an important role to mitigate the risk involved with drilling into an overpressure. Since the effective stress can be calculated from the interval velocity profile, the pore pressure was then computed by subtracting the effective stress from the overburden stress. These velocities are affected by the effective stress in a given basin. Using the seismic velocity wavefield in 3D volume, overpressure can be mapped using appropriate pore pressure-velocity models. Although the derived pore pressure distribution from surface seismic measurements provides valuable information for planning wells, an accurate definition of the top of an overpressure zone and interval velocity trend below the bit requires much more improved detection method. Such accurate detection is achieved in the borehole environment through the use of high density borehole seismic measurements. In this paper, we show an example of overpressure prediction in a well in the Mahakam Delta in Indonesia, where overpressure posed a serious challenge to drillers and explorationists. The reservoir target is deep in this area which also has a high temperature gradient. Seismic velocities derived from surface seismic data in the Mahakam delta are generally not accurate enough for the purpose of predicting top of overpressure zone. To address this challenge, VSP method was used in accurately estimating seismic velocity to determine depth to overpressure zone. To derive an accurate interval velocity profile below the bit, we have used two inversion methods, the Bayesian method and the Minimum Entropy. The pore pressure was computed and mud weight profile was derived using the Eaton method. The predicted mud weight profile was then implemented in drilling the 6-inch section of the well. The well was safely and successfully drilled to total depth.
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