The drilling mud weight window addresses two modes of wellbore rock failure which lie on opposite ends. Breakouts being near the minimum limit and fracturing at the maximum. However, as evidenced by image logs, it's not uncommon to identify breakouts and induced fractures taking place within the same interval. Exploring this interesting phenomenon should lead to better understanding of how the window changes. This should also serve to identify near misses preceding drilling troubles.

In this work, field data are first used for the diagnostics of this phenomenon and to verify the order of occurrence of each mode of failure. Different forms of image logs taken at different time intervals are used for this purpose. Having established the values of relevant variables such as mud properties, rock properties, and wellbore dimensions, a 3D finite element model is then used to quantify the changes in the drilling window as each mode of failure starts to take place.

It is observed that while fluctuations in the bottomhole pressure during the different drilling phases could be a starting point to understand this phenomenon, it's not sufficient. This is especially apparent when considering the size of the window or the various measures taken by modern day drilling practices to maintain the bottomhole pressure within the window. Understanding the order of each failure occurrence and their impact on each other serves to accurately identify the onset of a host of drilling troubles such as lost circulation, poor hole cleaning, and stuck-pipe incidents. This will essentially work to produce a first attempt at estimating the life cycle of the drilling window throughout the different drilling phases with the end result being a dynamic definition of the window. The outcome of this work presents a new perspective through which, different drilling variables can be manipulated to eliminate the onset of drilling troubles. Based on this, it can be shown how the allowable mud weight is evolving from its base range as the wellbore begins to deform. The implications of these changes of the drilling window can be reflected on other peripheral variables such as surge and swab tolerance and allowable equivalent circulating density.

The results of the model can be used to insure more efficient employment of bottomhole pressure maintenance techniques such as managed pressure drilling. Also, in a system where the required real-time data gathering equipment is available, the model provides a path towards automating the responses to the constantly changing environment downhole.

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