Implementation Of Intelligent Workflows For Early Detecting Well Integrity Problems & Preventive Maintenance

Max Hädicke

Research output: ThesisMaster's Thesis

Abstract

Intelligent workflows are increasingly used in science and in operational processes in order to manage complex computations and data processing at large scale. Such workflows use a semantic illustration that extends workflow representations with semantic constraints that express characteristics of the problems and analytic corrosion models. Corrosion is a great problem in the oil and gas industry. It causes tremendous costs in the up- and downstream sector. The prediction of this chemical and partly physical reaction is very time-consuming and requires a lot of technical understanding of the behavior of corrosion under several conditions. The industry tends to neglect this phenomenon by using cheap steel grades in order to save money. There are several developed prediction models available on the market. But not every model fits to every well, therefore it is necessary to gather and adjust the applicable data. The DeWaard and the NORSOK model are common prediction models on the field. It is possible to adjust them with some additional parameters e.g. critical erosional velocity, H2S proportion and many more to finally get a realistic approach for a corrosion rate in the future. This prediction is compared with a real measured corrosion rate from a wall thickness logging. The relation between the two measurements is used to build a KPI which will show the influence of the corrosion on the completion overtime. The results and some general information about the well are inserted into a Well Integrity Severity Evaluation Tool for the purpose of analyzing the state of the well. The evaluation has its main focus on any weariness of well barrier elements. Even the consequences for people, environment and business are included. The target of the thesis is primary a creation of modified corrosion prediction models which are based on different strategies and secondary a comparison of both models in the end. A well failure model approach may be adopted to streamline the risk assessment process including the influence of corrosion on the completion and downhole tools. The final part is the development of a business and failure matrix based on categorization and ranking of failures and economic impacts for the purpose of reporting and prioritization.
Translated title of the contributionErstellung von intelligenten Arbeitsabläufen für die frühe Erkennung von Bohrlochintegritäts Problemen und vorbeugsamen Wartungen
Original languageEnglish
QualificationDipl.-Ing.
Awarding Institution
  • Montanuniversität
Supervisors/Advisors
  • Solesa, Miso, Supervisor (internal)
Award date25 Oct 2019
Publication statusPublished - 2019

Bibliographical note

embargoed until null

Keywords

  • Well Integrity
  • Corrosion Prediction Models
  • Risk Matrix
  • Well Severity Evaluation
  • Barrier Envelope
  • Corrosion
  • MAASP
  • KPI
  • Casing Degradation

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