Estimating Probability of Failure for Drilling Tools with Life Prediction

Abstract

Drilling tools are subject to numerous operational parameters such as revolutions per minute (RPM), vibration (lateral, stickslip and axial), pressure, torque and temperature. These parameters can greatly fatigue even the most robust tool depending on where and how the tool is operated. Lifetime prediction methodologies represent an affordable and statistically significant way to estimate the probability of failure (risk) of drilling tools in a cost effective way. Understanding the potential risk is vital to ensuring reliability, performing the most efficient maintenance on the equipment and improving drilling performance. Sophisticated risk-modeling techniques reduce uncertainty in drilling operations by making use of readily available operational field data, thus eliminating the need for costly laboratory experiments. Blind spots in the decision making process are eliminated by proactively identifying precursors to costly failures in the field. Preemptive guidance during maintenance periods, for parts that may have otherwise been overlooked based strictly on procedure, is enabled. Statistical models that relate the operating environment to component life are derived from field component failure data, and introduce a fresh way to boost the drilling tool efficiency. A Bayesian-based model selection technique is also developed which incorporates operating environment variables after each successful drilling run to dynamically select the model that gives the best survival probability, ensuring maximum utilization of a component, while avoiding failure and improving the overall reliability of the tool in the field. The implementation of lifetime prediction methodologies also leads to lowered life-cycle and maintenance costs, reduced risk and improved operational performance. The paper presents the methodology used to estimate the probability of failure of drilling tools and further illustrates how to reach risk-informed decisions.

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

“…CBM focuses on the system failure prognostic and remaining useful life estimation/prediction approach with historical and real-time data instead of predetermined failure time limit approach to determine appropriate maintenance [11,96]. Maintenance plants can incorporate risk-informed CBM decision into reliability constraint and spare part forecasting for tool maintenance or replacement [3]. CBM available input can include historical and real-time field data of the monitored parameters (e.g., vibration, temperature, sound, heat, noise levels, etc.…”

“…With drilling technology advancement, oil and gas drilling activities more frequently occur in the rock layer of thousands of meters depth and severe downhole conditions [1]. The challenging downhole environment includes temperature exceeding 200 C, shock and vibration levels surpassing 15 g, pressure beyond 207 MPa, strong abrasive formation, horizontal path instead of conventional vertical bore hole, and others [2,3]. Figure 1 illustrates several typical features of drilling activities.…”

“…The harsh downhole conditions are around or beyond operating tools' design specification constraints, and severely damage even the sturdiest and most reliable components, such as printed circuit board Fig. 1 Illustration of drilling activity [3] 1 assemblies parts in logging-while-drilling (LWD) and measurement-while-drilling (MWD) tools [2,4,5]. This phenomenon leads to the increased tool failure rate, system downtime, nonproductive time, higher maintenance and repair costs, and lowered operation reliability for both drilling operators and service providers [3,4,6].…”

“…1 Illustration of drilling activity [3] 1 assemblies parts in logging-while-drilling (LWD) and measurement-while-drilling (MWD) tools [2,4,5]. This phenomenon leads to the increased tool failure rate, system downtime, nonproductive time, higher maintenance and repair costs, and lowered operation reliability for both drilling operators and service providers [3,4,6]. Consequently, the analysis, evaluation, and prediction of drilling tool failure and operation reliability in the complicated downhole conditions, as well as the methodology for optimizing maintenance plan and reducing lifecycle cost, has become an emerging research topic in reliability engineering field [2,4,7].…”

“…These factors include drilling, operating, circulation hours, drilled depth, temperature, vibration, shock, pressure, face angle, torque, rotation speed, current, voltage, power cycle, well deviation, orientation, inclination, humility, flow rate, gamma radiation, viscosity, sand content, weight on bit (WOB), mud type, mud weight, PH of mud, contaminants, noise levels, and others [8]. Due to the system and human factor limitation, the interactive impact of multiple parameters to different drilling tools cannot be accurately measured [3,4]. However, the previous research reveals that downhole vibration is one important factor to weaken tool robustness, reduce tool reliability and life expectancy [2,4,5,7,9].…”