Basin modeling is an effective tool for pore pressure prediction. A model that can be updated as new data is acquired can provide a Look Ahead prediction that may be valid for several thousand feet ahead of the bit.A new modeling program is described that has proven effective both in pre-drill analysis and in while-drilling situations for a variety of geologic regimes. In the recently completed DEA 119 Phase 2 study, pressure gradients were predicted to less s than 1 ppg for the whole well in 62% of blind test analyses. In numerous wells, real time updating of the basin model has proved effective at narrowing the envelope of pore pressure and Earth stress uncertainty ahead of the bit.

The model utilizes conventional compaction principles derived from seismic and/or well gradient logs as calibration. It combines this information with geologic-based information (ages, thickness, porosity and lithology) to predict the geopressure environment that will be encountered by the well.

As the well is drilled, new information becomes available that will either confirm or refute the original geopressure prediction. This new data is well-specific and can be used to update the basin model. The data ahead of the bit still contains all of the information that is known about the area and has not been changed by the addition of the real time data. Adjusting the model with the newly acquired data will therefore reduce the envelope of uncertainty that existed in the original model and update the prediction with the new information. This updating is performed in real time and is available while the well is being drilled.

An early example of basin modeling in a real time look ahead mode is shown to demonstrate the challenges that have been addressed to date. Through careful examination of a case where performance could have been better, the authors reveal the weaknesses of the approach such that they can be better understood.Furthermore, the example demonstrates the capability to update the prediction of pore pressure ahead of the bit and use this advance prediction for other solutions such as wellbore stability computations. Aggregated look ahead performance results from five other projects are revealed that demonstrate the ability of this technology to provide information to operators that can improve the safety and performance of well construction.

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