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Data-Driven Optimization of Drilling Parameters Considering the Interaction Between Formation and Borehole Assembly

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Course Credit: 0.15 CEU, 1.5 PDH

A major challenge during drilling is to identify the sub-formation change and near real-time adjustment of the drilling parameters to enhance the performance. An algorithm, which determines sub-formations, optimizes drilling parameters as formations change and updates itself, solves this problem.

The presented workflow leverages drilling and geological information, statistical analysis, and physics-based models to identify sub-formations and transition zones in active wells. Rock drillability is calculated and used to identify the formation change. Simultaneously, optimal drilling parameters for the formation are generated, using an approach, which relies on the concept of mechanical specific energy (MSE).

The workflow was successfully applied to a significant population of wells in multiple fields. Analyzing the results, the main observations were as follows: reduced cumulative MSE and drilling time on average, improved consistency, and expedited learning curve. These achievements to a large extent are due to improved downhole dynamics, the reduction of input variability on the drilling system and the compound effect of the statistical analysis of the algorithm.

The power of the algorithm comes from the fact that it considers geological effects along with surface controls and BHA on the performance. This enables it to determine the formations that affect drilling operation and the optimum drilling parameters for that formation zone. Quantifying the effects of formation change, along with surface controls for a given BHA, significantly improves the performance.

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Course Chapters

  • 1Data-Driven Optimization of Drilling Parameters Considering the Interaction Between Formation and Borehole Assembly - Chapter 1
    Media Type: Video

Credits

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

Speakers

Dr. Reza Asgharzadeh Shishavan