Abstract
Efficient drilling operations hinge on accurately obtaining the rate of penetration (ROP), a crucial parameter influencing well delivery costs and overall project timelines. While existing predictive models predominantly cater to rotary and rotary steerable system bottom hole assemblies (BHAs), motorized BHAs have received comparatively less attention. Addressing this gap, our study introduces a pioneering artificial intelligence (AI) model powered by artificial neural networks (ANN) to forecast ROP for motorized BHAs. By integrating surface drilling parameters, mud characteristics, and motor output features, the model undergoes rigorous training, validation, and testing on a comprehensive dataset sourced from six wells in the Middle East, encompassing over 5,800 data points. Robust evaluation metrics, including Root mean square error (RMSE) and correlation coefficient (R), affirm the model's exceptional accuracy (R of 0.97) in predicting ROP. Beyond its predictive capabilities, the ANN-based model provides valuable insights into the impact of diverse drilling parameters on motorized BHA performance, enabling operators to optimize ROP, minimize drilling costs, and enhance overall operational efficiency in the field.
Original language | English |
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Title of host publication | 58th US Rock Mechanics / Geomechanics Symposium 2024, ARMA 2024 |
Publisher | American Rock Mechanics Association (ARMA) |
ISBN (Electronic) | 9798331305086 |
DOIs | |
State | Published - 2024 |
Event | 58th US Rock Mechanics / Geomechanics Symposium 2024, ARMA 2024 - Golden, United States Duration: 23 Jun 2024 → 26 Jun 2024 |
Publication series
Name | 58th US Rock Mechanics / Geomechanics Symposium 2024, ARMA 2024 |
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Conference
Conference | 58th US Rock Mechanics / Geomechanics Symposium 2024, ARMA 2024 |
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Country/Territory | United States |
City | Golden |
Period | 23/06/24 → 26/06/24 |
Bibliographical note
Publisher Copyright:Copyright 2024 ARMA, American Rock Mechanics Association.
ASJC Scopus subject areas
- Geochemistry and Petrology
- Geophysics