Digital Modeling of the Drilling Process and Automated Operations Recognition as Basis for Optimizing Drilling Economics

Hermann Friedrich Spoerker

Digital Modeling of the Drilling Process and Automated Operations Recognition as Basis for Optimizing Drilling Economics

Hermann Friedrich Spoerker

Chair of Drilling and Completion Engineering (590)

Research output: Thesis › Doctoral Thesis

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Abstract

The thesis presents the development of a discrete description of the drilling process (i.e. the process of physically constructing a wellbore), based on a four-tier system. Core- and subprocesses are described, further broken down into detailed activities and supported by start/stop definitions and key performance indicators (KPIs) for each process step. Planning/definition methodologies are discussed for the presented four-tier approach (strategic/tactical/detailed/machine) and evaluated against their impact on standardizing/optimizing execution processes. Finally, the impact of automated recognition of drilling unit operational conditions on enhancing operational performance is demonstrated. Removing human bias from the definition of time coding and performance benchmarking provides a more solid foundation for assessing and improving operational performance.

Translated title of the contribution	Digitale Beschreibung des Bohrprozesses sowie automatische Erkennung von Bohranlagen-Betriebszuständen als Basis zur Optimierung der Bohreffizienz
Original language	English
Qualification	Dr.mont.
Supervisors/Advisors	Thonhauser, Gerhard, Assessor A (internal) Kessler, Franz, Assessor B (internal)
Publication status	Published - 2013

Bibliographical note

no embargo

Keywords

drilling
process
operations recognition

Access to Document

VolltextFinal published version, 6.21 MB

Cite this

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title = "Digital Modeling of the Drilling Process and Automated Operations Recognition as Basis for Optimizing Drilling Economics",

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N2 - The thesis presents the development of a discrete description of the drilling process (i.e. the process of physically constructing a wellbore), based on a four-tier system. Core- and subprocesses are described, further broken down into detailed activities and supported by start/stop definitions and key performance indicators (KPIs) for each process step. Planning/definition methodologies are discussed for the presented four-tier approach (strategic/tactical/detailed/machine) and evaluated against their impact on standardizing/optimizing execution processes. Finally, the impact of automated recognition of drilling unit operational conditions on enhancing operational performance is demonstrated. Removing human bias from the definition of time coding and performance benchmarking provides a more solid foundation for assessing and improving operational performance.

AB - The thesis presents the development of a discrete description of the drilling process (i.e. the process of physically constructing a wellbore), based on a four-tier system. Core- and subprocesses are described, further broken down into detailed activities and supported by start/stop definitions and key performance indicators (KPIs) for each process step. Planning/definition methodologies are discussed for the presented four-tier approach (strategic/tactical/detailed/machine) and evaluated against their impact on standardizing/optimizing execution processes. Finally, the impact of automated recognition of drilling unit operational conditions on enhancing operational performance is demonstrated. Removing human bias from the definition of time coding and performance benchmarking provides a more solid foundation for assessing and improving operational performance.

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