Abstract
Abstract
The wellbore quality can be affected by a multitude of factors that include drilling operations practices, drilling fluids quality, and geomechanical quality. Low quality wellbores lead to many complications that will result in well completion delay of. One factor of success in drilling operations is minimizing enlargements and tight spots. A new assessment process was developed to understand and analyze the influence of drilling operational practices on the wellbore shape. The analysis helps to identify the root causes of wellbore enlargement and propose mitigation solutions.
More than 20 wellbores have been analyzed. Those wellbores penetrate a carbonate sequence followed by a sandstone sequence. This is to characterize the variations in the wellbore shape, in terms of enlargements and tight spots, against a set of well-defined parameters affecting it. For these wellbores, the mechanical properties and the stresses were estimated to correlate the geomechanical aspects of penetrated formations to the behavior of the wellbore geometry. Cyclic lateral loading of the drillstring, mud-controlled swabbing, and unintentional deviation in some wellbores were also investigated.
The assessment concluded that cyclic lateral loading, due to reaming and vibrations, is a key factor of influence in changing the wellbore shape. Also, the mud-controlled swabbing proved to have a significant role in hole enlargements specifically. This was found to be evident in wellbores that employ highly viscous mud with a 30 min. gel strength of more than 25 lb/ft2. It was also found that using mud with low chloride concentration, below 30 g/L, contributed to the varying geometry of wellbores.
Applying the recommendations generated by this work will help to refine the quality of future drilled wellbores and consequently, mitigate the risks of pack-offs, stuck-pipe incidents, sidetracking, low quality logs, and casing-casing annular pressure. Also, this work will present a new approach for real- time wellbore quality prediction and monitoring using advanced data analytics tools.
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