Automated Wellbore Stability Systems - Experience With Pore Pressure Modeling
Authors: Wessling Stefan , Bartetzko Anne , Wang Xiaowei , Pei Jianyong , Dahl Thomas 
Published: May 2016

Abstract
Overpressure is observed in many sedimentary basins worldwide, and knowledge of it is critical to the oil industry as it can cause severe operational problems. The most commonly applied methods for quantifying pore pressure from downhole logging data, drilling data, and seismic measurements rely on the compaction behavior of shales. These methods require the determination of a so-called normal compaction trend line that represents the normal and expected decrease in porosity under normal, hydrostatic conditions. Deviations from this trend are associated with overpressure. Typically, these normal compaction trend lines are defined manually by an expert. However, with the increasing interest in automation for drilling and also real-time wellbore stability modeling, the required manual input poses challenges for automation.
In this paper we present an approach for the automatic definition of the normal compaction trend line. This includes automatically defining the transition from hydrostatic conditions to an overpressured formation. The approach was developed for real-time applications and is based on a regression analysis. By analyzing the compaction trend line, the approach determines if the bottom of the well is still in a normally pressured formation or if the transition zone into an overpressured interval has been reached. In the latter case, an alert will be triggered and the engineer will decide if this is a serious alert that requires reaction or if drilling can proceed under the given conditions. Parameters of the algorithm can be modified to control the number of alerts and the precision of the results.
One critical aspect for automation is the careful design of valuable alerting functions. We propose an alert filtering approach which assigns confidence levels to alerts that were generated by different analysis methods. Testing on an example data set shows that a large number of alerts can be generated, but the amount of high confidence level alarms remains acceptable. Our approach is one step towards an automated wellbore stability system. Such a system would give additional expertise to rigsite engineers and enable simultaneous supervision of more than one well for remote operating engineers.

1 Introduction
Knowledge and understanding of overpressure magnitudes and mechanisms is very important as it may cause severe drilling problems. As the drilling industry moves forward towards automation, real-time modeling and monitoring of wellbore stability events are candidates for automation. Automation enables the rig site, remote and office-based engineers to simultaneously identify and mitigate wellbore stability issues before they become critical. However, automation of the wellbore stability workflow is particularly challenging because of the complexity of the workflow, the variety of data types and models utilized, and the amount of manual input and visual inspection required from an expert (e.g. Bartetzko et al., 2011; Wessling et al., 2011). An example of this is the manual setting of compaction trend lines in a pore pressure analysis.
In consideration of the complexity of the wellbore stability workflow and the challenges associated with its automation, different levels of automation may be targeted, as suggested by Thorogood et al. (2010). At a low automation level, the algorithms may check for consistency of input parameters and offer suggestions. At these low automation levels, the user still maintains control. At a higher automation level, the system may proceed automatically but still informs the user of the actions that were carried out. At the highest level, a fully autonomous system would not require any user interaction at all. Low automation level is addressed in this paper. An algorithm will be presented which generates alerts but decisions need to be made by the user.