Yes / Predicting the PDC bit performance during drilling operation is important for the cost effectiveness of the operation. The majority of PDC bits are assessed based on their performance that are relative to offset wells. Determination of mechanical specific energy (MSE) in real time and compare it with the known MSE for a sharp bit to assess the bit life has been utilized by several operators in the past. However, MSE still cannot be used to predict the bit performance in exploration wells and also it cannot assess the bit efficiency in the inner and outer cones. A more precise approach needs to be devised and applied to improve the prediction of bit life and the decision when to pull the bit out of the hole. Effective mechanical specific energy (EMSE) developed in this work is a new wear and performance predictive model that is to measure the cutting efficiency based on number of cutters, which contact the rock as a function of weight on bit (WOB), rotary speed (RPM), torque, and depth of cut (DOC). This model modifies the previous MSE model by incorporating such parameters and including detailed design of the bit, number of blades, cutter density, cutter size, and cutting angle. Using this approach together with the analysis of rock hardness, a level of understanding of how the drilling variables influence the bit performance in the inner and outer cone is improved, and a convenient comparison of the bit condition in the frame of the standard bit record is achieved. This work presents a new simple model to predict the PDC cutters wear using actual data from three sections drilled in three oil wells in Libya. It is found that the obtained results are in well agreement with the actual dull grading shown in the bit record.
Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/18821 |
Date | 18 March 2022 |
Creators | Mazen, Ahmed Z., Rahmanian, Nejat, Mujtaba, Iqbal M., Hassanpour, A. |
Source Sets | Bradford Scholars |
Language | English |
Detected Language | English |
Type | Article, Accepted manuscript |
Rights | © 2021 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license., CC-BY-NC-ND |
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