In order to mitigate predrill uncertainties and provide the well team with the best information to drill proactively, monitoring of borehole operations in real-time is vital on wells drilled today. Real-time monitoring (Pore Pressure while Drilling – PPwD) gives the team the best chance to drill the well safely and efficiently to planned targets. Recent proposals by the United States Bureau of Safety and Environmental Enforcement indicate real-time monitoring might soon be mandatory on many offshore US wells. One particularly important aspect of real-time monitoring is pore pressure and fracture gradient estimation and prediction.
Most analysis of drilling data, such as petrophysical, drilling parameters, gas and geology, relies solely on depth-based data, which of course are only available while drilling ahead, i.e. wellbore depth is increasing. The depth-based analysis model is relatively low resolution with data points at 0.5 foot or 0.2 meter intervals. If calibrated correctly the models are valuable and accurate, providing the well team with useful insight about present and possible future events.
However, there are many operations during the drilling of a well that do not generate depth-based data, such as pipe connections, circulating off-bottom, wiper trips, flow-checks etc., that instead, generate time-based data. When analyzed, such data provide invaluable information to permit further calibration of the models. Realtime pore pressure models that only contain depth-based information are potentially flawed because the many calibration points that occur while the bit is off bottom are not captured/recorded in the model. Building a time-based model in parallel to the depth-based model allows for a far more robust picture of downhole conditions.
This paper will use real examples from the Gulf of Mexico to explain the importance and benefits of constructing a time-based model that will be used alongside the depth-based model. It will also demonstrate how discrepancies between depth-based models and time-based models can arise. The result of using all available data, in both depth and time domain, is a more robust, integrated model on which to base the pore pressure estimation and prediction and ensure the well team gets the best 2 OTC-27145-MS possible information.
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