Identifying the Optimum Zone for Reducing Drill String Vibrations

Etaje, Darlington Christian

Identifying the Optimum Zone for Reducing Drill String Vibrations

dc.contributor.advisor	Shor, Roman J.
dc.contributor.author	Etaje, Darlington Christian
dc.contributor.committeemember	Gates, Ian Donald
dc.contributor.committeemember	Hassay, Derek N.
dc.date	2018-11
dc.date.accessioned	2018-07-12T13:50:23Z
dc.date.available	2018-07-12T13:50:23Z
dc.date.issued	2018-07-10
dc.description.abstract	This thesis was written to address the vibration problems that occur during drilling operations. Due to the rotational motion effected on the drill string while drilling, vibrations occur, and when these vibrations become excessive, the drill string may oscillate in a manner that could damage the pipes and damage other tools attached to the drill string. Machine learning may be used to identify the vibration prone zones and provide recommendations to the driller to change the operating weight on bit (WOB) and rotation speed (RPM) to achieve drilling efficiency while reducing the possibility of damages downhole. Data received from the rig is processed through a dimension reduction process and then categorized using a decision tree classification method. The rules behind the decision tree was created by reversing conventional ways of curbing vibration problems during drilling operations. In the course of the research, it was discovered that there is a need for additional safety gap away from the usual boundary for vibration problems. Quantitative risk analysis was used to identify this gap. This report explains the process of identifying that safety gap. The machine learning model used throughout this research was trained on recorded downhole data and tested with surface data from the electronic drilling recorder. The reports also highlight the findings from market research done to identify the possibility of deploying this research as a startup in Calgary, Canada. Detailed competitor analysis is shown based on customer discovery and customer validation interviews. This has led to the development of business model canvas which is described in this report. A blue ocean strategy was graphed showing that the startup, “Optimum Zone Identifier, OZI” can be differentiated from competitors by being in a market segment that has unique needs with OZI being the only player fitting this category.	en_US
dc.identifier.citation	Etaje, D. C. (2018). Identifying the Optimum Zone for Reducing Drill String Vibrations (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/32358	en_US
dc.identifier.doi	http://dx.doi.org/10.11575/PRISM/32358
dc.identifier.uri	http://hdl.handle.net/1880/107136
dc.language.iso	eng
dc.publisher.faculty	Graduate Studies
dc.publisher.faculty	Schulich School of Engineering
dc.publisher.institution	University of Calgary	en
dc.publisher.place	Calgary	en
dc.rights	University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subject	Drill String Vibrations
dc.subject.classification	Engineering--Petroleum	en_US
dc.title	Identifying the Optimum Zone for Reducing Drill String Vibrations
dc.type	master thesis
thesis.degree.discipline	Chemical and Petroleum Engineering
thesis.degree.grantor	University of Calgary
thesis.degree.name	Master of Science (MSc)
ucalgary.item.requestcopy	true

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