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Rate of Penetration Prediction for Multiple Well Profiles Using Artificial Intelligence Techniques

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Course Credit: 0.15 CEU, 1.5 PDH

Rate of Penetration (ROP) is defined as the volume of rock removed per unit area (ft) per unit time (hr). This important measurement factor is often captured by many drilling companies to gauge the speed and the efficiency of the time spent to drill a section. It has been reported in the industry that high percentage of the well budget is spent on the drilling phase, thus many drilling operators pay close attention to this factor and try to optimize it as much as possible. However, it is very challenging to capture the effect of each individual parameter since most of them are interconnected, and changing one parameter affects the other. As a result, many companies maintain data for the drilling performance per field and set certain benchmarks to gauge the speed of any newly drilled well. To date, no solid or reliable model exists because of the complexity of the drilling process, therefore, the utilization of artificial intelligence (AI) in drilling applications is a game changer since most of the unknown parameters are accounted for during the modeling or training process. The results presented in this webinar demonstrates the use of artificial intelligence techniques to develop rate of penetration models for multiple well profiles from actual field data. This includes model development, training and testing, and validating. It also lists some key challenges during AI modeling such as data quality, data analytics and leaving the model as a blackbox.

All content contained within this webinar is copyrighted by Dr. Ahmad Al-AbdulJabbar and its use and/or reproduction outside the portal requires express permission from Dr. Ahmad Al-AbdulJabbar.

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 1 chapter

Course Chapters

  • 1Rate of Penetration Prediction for Multiple Well Profiles Using Artificial Intelligence Techniques - Chapter 1
    Media Type: Video


Earn credits by completing this course0.15 CEU credit1.5 PDH credits


Dr. Ahmad Al-AbdulJabbar