Prediction of Weight-on-Bit based on Real-Time Surface Measurements

Rainer Paulic

Research output: ThesisMaster's Thesis

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Abstract

High rates of penetration can be achieved when drilling with the right weight-on-bit. Using surface measurements of the hookload, the weight-on-bit can be estimated. Other surface measurements can be used to detect various drilling dysfunctions like stick-slip which influence the transfer of force to the bit. By correlating surface measurements with downhole measurements taken by an ISUB tool, the influence of different drilling dysfunctions on force transfer can be estimated. A spring-mass model is proposed to simulate the force transfer to the bit. Because of the complexity of such a system, neural networks may be the best solution to solve this task in real-time.
Translated title of the contributionVorhersage der Meißellast mittels Echtzeitmessungen an der Oberfläche
Original languageEnglish
QualificationDipl.-Ing.
Supervisors/Advisors
  • Thonhauser, Gerhard, Supervisor (internal)
Award date30 Mar 2007
Publication statusPublished - 2007

Bibliographical note

embargoed until null

Keywords

  • axial force transfer weight-on-bit stick-slip neural networks mass-spring model

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