Drilling Modeling and Simulation: Current State and Future Goals

Abstract

The process of drilling a borehole is very complex, involving surface and downhole drilling systems, which interact with the drilling fluid and the surrounding rocks. Modeling and simulating every aspect of the drilling process and drilling system is still considered too complex to be realized. However, many areas of modeling and simulation are currently undergoing very aggressive development. These areas include rig systems, downhole dynamics, rock-bit interaction, drilling/formation fluid, and the Earth model. High-fidelity models in these well-defined areas have demonstrated some success. Lately, drilling modelling and simulation has become one of the key factors for advancing drilling systems automation/control, intelligent managed pressure drilling and drilling optimization by understanding and/or predicting downhole dynamics. Modeling the magnitude and spatiotemporal distribution of uncertainty in the actual drilling process poses serious challenges in constructing high-fidelity models of the entire drilling system. However, the advancement of technology may dramatically improve the future of such an attempt to accurately model and simulate the whole drilling process. The topics presented in this paper include the current state of drilling process simulation software and simulators, the challenges of modelling drilling systems for automation and control, adaptive simulations for downhole drilling systems and the operator's perspective on drilling modelling. This paper examines the current state of drilling modelling and simulation and identifies its future goals.

The Application of Downhole Vibration Factor in Drilling Tool Reliability Big Data Analytics—A Review

“…Meeker and Hong provide a strategic perspective on the potential impact of FRBD in reliability with a natural extension from traditional reliability methods and propose the ideas to enhance the impact of the statistical and reliability analysis based on FRBD [17,60]. Additionally, drilling industry has utilized FRBD to perform reliability analytics and prediction to improve drilling reliability, efficiencies, proactive, and reactive reliability decision-making [1,2,6,7,13,[61][62][63].…”

“…Combine information from different sources such as data from product design, laboratory experiment, accelerating life test, manufacturing quality, field operation, maintenance workshop, and engineering knowledge to enable reliability analytics to be performed in a broader scale and produce an enhanced influence from product design. Especially, degradation data caused by downhole vibration have valuable dynamic covariate information to improve reliability predictions on severe vibrations, whirl, or bump events [16,63]. Autocorrelation in the covariate process can be modeled to reduce analytical time and improve efficiency [16].…”

Vibration of drilling motors in unconventional oil and gas exploration with a miniature recorder

“…Downhole drilling dynamics or vibration have, therefore, become a subject of intensive research [8–10]. The study has focused on the downhole measurement of drilling vibration, its consequences, and tool and operation optimisation processes for mitigation [11, 12].…”

Rate of Penetration Prediction Utilizing Hydromechanical Specific Energy

“…During drilling operations, lots of realtime data are being gathered with quite a number related to ROP but are riddled with lots of uncertainties and complex relationships which are better handled by data-driven analytical techniques. The ability of AI techniques, to work through complex data sets and establish a relationship or trend without prior assumptions has made it endearing to the hearts of engineers who seek to solve complex drilling engineering problems, especially when the geology and rock mechanic parameters differs from well to well, and therefore may have different recommended drilling parameters within a wide range [4].…”