Multi-element drilling parameter optimization based on drillstring dynamics and ROP model

Abstract

Drilling parameter optimization is a crucial methodology for enhancing the rate of penetration (ROP) and serves as an essential strategy for achieving cost reduction and efficiency improvements in drilling engineering. Drilling parameters optimization can be conducted based on the drillstring dynamics model and ROP model. Still, there remains a notable gap in multi-element drilling parameter optimization studies considering both models concurrently. This paper addresses the challenges associated with increasing ROP within the M formation of the D oilfield located in the Middle East. Establishing a comprehensive full-scale drillstring dynamics model alongside an ROP prediction and optimization model based on artificial neural networks(ANN). By taking into account energy transfer efficiency, vibration intensity, and various factors influencing ROP during the drilling process, we propose an innovative workflow for multi-element drilling parameter optimization. Ultimately, this process facilitates parameter optimization for well P, followed by application tracking. The results indicate that after employing the recommended combination of parameters, well P achieves an average ROP of 10.16 m/h representing a 51.4% increase compared to previously completed wells thus fulfilling our objective of enhanced ROP. Furthermore, the implementation of this parameter optimization substantiates both its effectiveness and reliability as a method for multi-element drilling parameter optimization. It offers recommendations for optimal controllable drilling parameters tailored to specific target blocks and formations while providing corresponding design guidance during the initial stages of drilling planning.