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Assessment and Modelling of Wear prediction and Bit Performance for Roller Cone and PDC Bits in Deep Well Drilling
Mazen, Ahmed Z.M.
Mazen, Ahmed Z.M.
Publication Date
2020
End of Embargo
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The University of Bradford theses are licenced under a Creative Commons Licence.
Peer-Reviewed
Open Access status
Accepted for publication
Institution
University of Bradford
Department
Faculty of Engineering and Informatics
Awarded
2020
Embargo end date
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Abstract
Drilling is one of the important aspects in the oil and gas industry due to the high
demand for energy worldwide. Drilling time is considered as the major part of the
operations time where the penetration rate (ROP) remains as the main factor for
reducing the time. Maximizing ROP to lower the drilling cost is the main aim of
operators. However, high ROP if not controlled may impact on the well geometry
in terms of wellbore instability, cavities, and hole diameter restrictions.
Accordingly, more time is needed for the other operations that follow such as:
pool out of hole (POOH), casing running, and cementing. Bit wear is considered
as the essential issue that influences in direct way on the bit performance and
reduce ROP. Predicting the abrasive bit wear is required to estimate the right time
when to POOH to prevent any costly job to fish any junk out to the surface. The
two-common types of bits are considered in the research, rock bits (roller cone
bits) and Polycrystalline Diamond Compact bits (PDC). This study focuses more
on PDC bits because about 60% of the total footage drilled in wells worldwide
were drilled by PDC bits and this is expected to reach 80% in 2020.
The contribution of this research is to help reducing the drilling cost by
developing new tools not to estimating the time when to POOH to surface but
also to measure the wear and enhance the accuracy of prediction the bit
efficiency. The work is broken down into four main stages or models to achieve
the objective: The first stage; estimating of the rock abrasiveness and calculate
the dynamic dulling rate of the rock bit while drilling. The second stage; estimating
the PDC abrasive cutters wear by driving a new model to determine the
mechanical specific energy (MSE), torque, and depth of cut (DOC) as a function
of effective blades (EB). The accuracy of the predicted wear achieves 88%
compared to the actual dull grading as an average for bits used in five wells. The
third stage; modifying the previous MSE tool to develop a more accurate
approach; effective mechanical specific energy (EMSE), to predict the PDC bit
efficiency in both the inner and outer cone to match the standard bit dulling. The
fourth stage; predicting ROP while PDC drilling in hole by accounting three parts
of the process: rock drillability, hole cleaning, and cutters wear. The results
achieve an enhancement of about 40% as compared to the available previous
models.
Consequently, the developed models in this study provide a novelty on
understanding in more details the bit rock interface process and gain an idea of
the relationship between the drilling parameters to enhance the bit performance
and avoid damaging the bit. This is basically about optimisation the controllable
factors such as: weight on bit (WOB), rotary speed (RPM), and flow rate. The
result is the reduction in time losses and the operations cost.
To ensure reliability and consistency of the proposed models, they were
validated with several vertical oil wells drilled in Libya. The results from the
validation of the models are consistent with the real field data. The research
concludes that the developed models are reliable and applicable tool for both: to
assist decision-makers to know when to pull the bit out to surface, and also to
estimate the bit performance and wear.
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Type
Thesis
Qualification name
PhD