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Probabilistic Approach in Wellbore Stability Analysis during Drilling
Author(s) -
Mahmood R. Al-Khayari,
A. Al-Ajmi,
Yahya Al-Wahaibi
Publication year - 2016
Publication title -
journal of petroleum engineering
Language(s) - English
Resource type - Journals
eISSN - 2314-5005
pISSN - 2314-5013
DOI - 10.1155/2016/3472158
Subject(s) - wellbore , drilling , petroleum engineering , monte carlo method , probabilistic logic , underbalanced drilling , instability , geology , drilling engineering , oil field , stability (learning theory) , pore water pressure , drilling fluid , geotechnical engineering , engineering , mechanics , computer science , mechanical engineering , mathematics , statistics , physics , artificial intelligence , machine learning
In oil industry, wellbore instability is the most costly problem that a well drilling operation may encounter. One reason for wellbore failure can be related to ignoring rock mechanics effects. A solution to overcome this problem is to adopt in situ stresses in conjunction with a failure criterion to end up with a deterministic model that calculates collapse pressure. However, the uncertainty in input parameters can make this model misleading and useless. In this paper, a new probabilistic wellbore stability model is presented to predict the critical drilling fluid pressure before the onset of a wellbore collapse. The model runs Monte Carlo simulation to capture the effects of uncertainty in in situ stresses, drilling trajectories, and rock properties. The developed model was applied to different in situ stress regimes: normal faulting, strike slip, and reverse faulting. Sensitivity analysis was applied to all carried out simulations and found that well trajectories have the biggest impact factor in wellbore instability followed by rock properties. The developed model improves risk management of wellbore stability. It helps petroleum engineers and field planners to make right decisions during drilling and fields’ development

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