Step Change in BHA Reliability and Performance Due to Utilization of Downhole Drilling Dynamics Services

Reckmann, Hanno; Hohl, Andreas; Oueslati, Hatem; Akimov, О.

doi:10.2118/191096-ms

Cited by 6 publications

(2 citation statements)

References 19 publications

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“…However, maintaining such an approach on a global scale and throughout many departments participating in the development, maintenance and operation of the tools requires considerable efforts Garvey et al [85] highlights the need for complete and concise history data throughout the entire life of a downhole tool, essential for robust lifetime prediction. Reckmann et al [86] discusses the importance of high quality/high frequency data for detection of tool failures and a complementary tool database capturing the tool history from various data sources. In [12] and [87] case studies of the challenges the oil and gas industry is facing in centralizing and streamlining drilling data are listed.…”

Section: Bda: An Oil and Gas Industry Reviewmentioning

confidence: 99%

“…The overall life of the BHA is estimated based on these results which simplifies the deployment and distribution of the data. Reckmann et al [86] define the requirements for an offline RUL estimation model supporting the operator's decision whether to rerun a downhole tool. In order to reduce NPT, Lahmadi et al [89] present an approach to estimate the RUL of composite drill pipes.…”

Section: Bda: An Oil and Gas Industry Reviewmentioning

confidence: 99%

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AI-Driven Maintenance Support for Downhole Tools and Electronics Operated in Dynamic Drilling Environments

et al. 2020

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Downhole tools are complex electro-mechanical systems that perform critical functions in drilling operations. The electronics within these systems provide vital support, such as control, navigation and front-end data analysis from sensors. Due to the extremely challenging operating conditions, namely high pressure, temperature and vibrational forces, electronics can be subjected to complex failure modes and incur operational downtime. A novel Artificial Intelligence (AI)-driven Condition Based Maintenance (CBM) support system is presented, combining Bottom Hole Assembly (BHA) data with Big Data Analytics (BDA). The key objective of this system is to reduce maintenance costs along with an overall improvement of fleet reliability. As evidenced within the literature review, the application of AI methods to downhole tool maintenance is underrepresented in terms of oil and gas application. We review the BHA electronics failure modes and propose a methodology for BHA-Printed Component Board Assemblies (PCBA) CBM. We compare the results of a Random Forest Classifier (RFC) and a XGBoost Classifier trained on BHA electronics memory data cumulated during 208 missions over a 6 months period, achieving an accuracy of 90 % for predicting PCBA failure. These results are extended into a commercial analysis examining various scenarios of infield failure costs and fleet reliability levels. The findings of this paper demonstrate the value of the BHA-PCBA CBM framework by providing accurate prognosis of operational equipment health leading to reduced costs, minimised Non-Productive Time (NPT) and increased operational reliability. INDEX TERMS Bottom hole assembly, oil drilling, printed component board assembly, dynamic environments, failure modes, condition based maintenance, diagnostics, prognostics, machine learning, artificial intelligence.

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Section: Bda: An Oil and Gas Industry Reviewmentioning

confidence: 99%

Section: Bda: An Oil and Gas Industry Reviewmentioning

confidence: 99%

AI-Driven Maintenance Support for Downhole Tools and Electronics Operated in Dynamic Drilling Environments

et al. 2020

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Best Practices for Operations in HFTO Prone Applications

Hohl

Kulke

Kueck

et al. 2020

Day 3 Thu, November 19, 2020

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Vibrations impact the drilling process by reducing reliability, increasing maintenance costs and reducing rate of penetration and drilling efficiency. Herein, torsional vibrations are typically distinguished into low-frequency torsional oscillations and stick/slip with frequencies below 1 Hz and high-frequency torsional oscillations (HFTO) with frequencies up to 450 Hz. HFTO is associated to high accelerations with critical values above 150 g and dynamic torsional torque values above the make-up torque. A HFTO mitigation strategy is mandatory for prone applications to guarantee high reliability and drilling efficiency. In this work different best practices for mitigation of HFTO and their interdependency are discussed along with their operational efficiency. The discussed scenarios include coupling between stick/slip and HFTO, different formation properties, and tools that are used for vibration mitigation such as isolators and mud motors. The analysis includes the review of time-based acceleration and load data with a sampling frequency of 1000 Hz and 2500 Hz and numerical modeling to determine the application and environment specific critical range of operational parameters in a holistic approach. The extracted critical range of operational parameters enables operations to optimally adjust parameters with a minimum of torsional loads and optimal drilling efficiency. This analysis again unveils that the general effect of HFTO is triggered by the cutting forces between PDC bits and hard and dense formation. It is shown qualitatively and quantitatively that high WOB values and low rotary speed values correspond to HFTO. The case study shows opportunities of a reduction of HFTO related loads by increase of the rotary speed without compromising the ROP in specific applications and environments. It is shown that special tools for vibration mitigation influence the stable operational window and need to be considered. Depending on the scenario a complete mitigation of HFTO or at least a significant reduction of loads can be achieved by targeted adjustment of operational parameters and use of tools for vibration mitigation. The drilling process can be optimized leading to a reduced cost of the well delivery since HFTO can be a major cause for non-productive time if not handled properly.

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Bit Design Methodology to Mitigate High-Frequency Torsional Oscillation

Tipples¹,

Keshiyev²,

Sheikhrezaei³

et al. 2021

Day 3 Thu, September 23, 2021

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This paper reviews field data where high-frequency torsional oscillation (HFTO) was seen on previous bit runs and hypothesizes on features or design metrics that may have directly influenced this vibration. This paper investigates four metrics of bit design: Cutter wear, shear length:shear area ratio, choice of secondary cutter material, and effective backrake. Hypotheses are established linking these metrics to HFTO, and then data from field runs is shown to correlate the hypotheses. At this point, a bit was designed and manufactured to put the HFTO avoidance hypotheses into practice. Prior to laboratory testing, a theoretical model is used to identify resonant torsional frequencies. A series of laboratory experiments followed to test the hypotheses and demonstrated that there is correlation between all factors, but in one case is counter to the hypothesis. This information is of use when selecting or designing bits in environments where HFTO is known to occur. The findings may also assist in explaining performance that's below expectations where HFTO is not able to be explicitly measured.

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Step Change in BHA Reliability and Performance Due to Utilization of Downhole Drilling Dynamics Services

Cited by 6 publications

References 19 publications

AI-Driven Maintenance Support for Downhole Tools and Electronics Operated in Dynamic Drilling Environments

AI-Driven Maintenance Support for Downhole Tools and Electronics Operated in Dynamic Drilling Environments

Best Practices for Operations in HFTO Prone Applications

Bit Design Methodology to Mitigate High-Frequency Torsional Oscillation

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