Dynamic Calibration of the Empirical Pore Pressure Estimation Methods Using MPD Data

Abstract

Abstract Pore pressure (PP) is one of the most critical parameters in geomechanical analyses of wellbore stability along with well planning. Several empirical methods aim to estimate the pore pressure using seismic and logging while drilling data, and drilling parameters. Considerable number of studies addressed the uncertainty in the PP estimate using these methods due to noise and fluctuation in the received data as well as under compaction effect in over-pressured formations. It is common practice to calibrate these methods with data from Repeat Formation Tester (RFT) or Drill Stem Test (DST). Managed pressure drilling (MPD) allows precise measurement of the PP with dynamic pore pressure testing (DPPT), reducing the non-productive time inherit in RFT and DST without compromising operational safety. This paper presents methodology to calibrate the available pore pressure prediction methods using dynamic PPT data. Presented methodology involves comparison of several correlations and selection of the one with the best fit to the dynamic PPT data, and determination of the formation-specific correlation coefficients using regression analysis. The work includes validation of the method on case study example. The technique implemented in a new MPD control software platform for real time analysis of the dynamic PPT data to forecast the pore pressure of the following formations while drilling.