Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"Rate of penetration (ROP)"”.
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Designing neural networks for the prediction of the drilling parameters for Kuwait oil and gas fields
… Three models were developed to predict bit type, rate of penetration (ROP), and cost-per-foot (cost/ft), respectively.;The prediction of bit type and other drilling parameters from the current available data is an important criterion in selecting the most cost efficient bit. History of bit runs …
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Development of drilling optimization models for autonomous rotary drilling systems.
… strict environmental policies motivate the use of technology and performance improvement techniques in drilling operations. Traditional drilling methods depend on the effectiveness of the human-driller in the management of operating parameters to improve system performance. Although existing …
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Analytical Modeling and Diagnosis of Penetration Rate Performance of PDC Bits
The high cost of drilling deep (15000+ ft) wells, due to slow rate of penetration (ROP) at depth, has severely limited the utilization and economic significance of deep hydrocarbon resources. The overall objective of this study was to obtain a better understanding of the major cause(s) of slow ROP …
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Unconfined compressive strength prediction using drilling parameters and analyzing feature importance through principal components analysis
Knowledge of geomechanical properties is beneficial if not essential for drilling and completion operations in the oil and gas industry. The Unconfined Compressive Strength (UCS) is the maximum compressive force applied to cylindrical rock samples without breaking under unconfined conditions. …
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Predicting tunnel boring machine utilization using discrete event simulation models for hard rocks
… as they have become the dominant mode and method of tunneling around the world. One of the essential steps for justification of the use of TBMs as well as planning the completion time and estimating the cost of projects involving TBMs is estimating the machine performance in given ground …
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Deep Neural Networks for Rate of Penetration Prediction: A Subsurface-Centric Approach Using Well Logs in the Volve Oil Field
Accurate Rate of Penetration prediction is pivotal for optimizing drilling efficiency, yet conventional models often neglect subsurface heterogeneity and rely heavily on operational parameters. This thesis introduces a subsurface-centric deep learning framework for ROP prediction based solely on …
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Deep Neural Networks for Rate of Penetration Prediction: A Subsurface-Centric Approach Using Well Logs in the Volve Oil Field
Accurate Rate of Penetration prediction is pivotal for optimizing drilling efficiency, yet conventional models often neglect subsurface heterogeneity and rely heavily on operational parameters. This thesis introduces a subsurface-centric deep learning framework for ROP prediction based solely on …