NDLI: Advanced prognostic technique for improving the drilling performance of downhole tools

Content Provider	IEEE Xplore Digital Library
Author	Sheng Zhan Jinhai Zhao
Copyright Year	2015
Description	Author affiliation: Sinopec Tech Houston LLC, Houston, TX, USA (Sheng Zhan; Jinhai Zhao)
Abstract	Modern drilling equipment faces increasingly severe environments, with bottom hole temperatures excessing 200°C and high vibration stresses. Meanwhile, customers continuously demand high reliability to prevent bottom hole failures, which result in one half or two days of nonproductive time (NPT) on drilling rigs costing $100K-$1M per day [1]. However, the current periodic maintenance strategy is insufficient and costly to meet the new challenges. From a cost-effective perspective, developing a conditional-based maintenance (CBM) prognostic model to evaluate the health condition of bottom hole assembly (BHA) tools becomes important and necessary for the oil and gas industry. This paper presents a CBM prognostic model for assessing the life consumption (LC) of BHA tools. Based on the analysis of physics of failure (PoF) [2], there are four major impacts on electronics reliability, i.e., lateral vibration (LV), stick slip (STI), temperature (TEMP), and axial vibration (AX) [1][2]. The CBM prognostic model described in this paper is acumulative damage model with weibull distribution, which is a linear regression model synthesizing the four impacts. To estimate the parameters of the model, the maximum likelihood estimation (MLE) is utilized. The confidence interval and the Fisher information matrix theories are applied to assess the LC intervals of the tools. The developed model will allow service providers to make more efficient decisions to reduce operation cost and increase downholoe tool availability and reliability.
Starting Page	1
Ending Page	9
File Size	494831
Page Count	9
File Format	PDF
e-ISBN	9781467385572
DOI	10.1109/ICRSE.2015.7366418
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vibrations Maximum likelihood estimation Torque Prognostic Technique Maintenance engineering Life Consumption Reliability Weibull distribution Bottom Hole Assembly Assembly Prognostics Conditional Based Maintenance
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Conditional reliability lower bound for Weibull distribution without estimating shape parameter

Prognostics health management for a directional drilling system

Maximum likelihood estimation of weibull distribution based on random censored data and its application

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

Review and classification of reliability statistical models exhibiting failure-free life characteristic

Performance evaluation for maximum likelihood and moment parameter estimation methods on classical two Weibull distribution

Reliability models of repairable systems considering the effect of operating conditions

Linear Regression Method for Binary Life Data from Weibull Distribution

Improving the quality of field data reliability analysis

Advanced prognostic technique for improving the drilling performance of downhole tools

Similar Documents

Conditional reliability lower bound for Weibull distribution without estimating shape parameter

Prognostics health management for a directional drilling system

Maximum likelihood estimation of weibull distribution based on random censored data and its application

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

Review and classification of reliability statistical models exhibiting failure-free life characteristic

Performance evaluation for maximum likelihood and moment parameter estimation methods on classical two Weibull distribution

Reliability models of repairable systems considering the effect of operating conditions

Linear Regression Method for Binary Life Data from Weibull Distribution

Improving the quality of field data reliability analysis

Advanced prognostic technique for improving the drilling performance of downhole tools