Automation of Brownfield Development Workflows

Research output: ThesisMaster's Thesis

Abstract

Brownfields are gaining increased attention by the oil and gas industry as they bear a high potential of being an important energy source, providing a big part of futures hydrocarbon production. Brownfields are very old fields with a long production history. Usually the wells in a Brownfield are approaching the end of their productive lives and very often they are being produced with the technology that has been installed back then when the field was brought on-stream. In the first part of this work an approach to identify development opportunities in a Brownfield is presented. The available data to evaluate these fields are usually restricted to produced and injected monthly volumes and very few petrophysical data. Based on this sparse set of information a series of workflow steps is performed to suggest an optimal field development plan. The suggested operations in the field development plan are drilling additional infill wells, recomplete wells in another layer, change wells from producer to injector or do a work over operation on a specific well. The second part of this work elaborately deals with the implementation of the workflow steps in a software product. The software product reduces the necessary time for a field study from eight weeks to three or four days by simultaneously improving the overall study accuracy. The user is automatically guided through the workflow and the necessary user intervention is reduced to a minimum. In the given version the software is able to automatically generate a rough geologic model, forecast the well production, find significantly better or worse producing wells (outliers) and suggest the best infill locations.

Details

Translated title of the contributionAutomatisierung von Feldentwicklungsworkflows für reife Öl- und Gasfelder
Original languageEnglish
QualificationDipl.-Ing.
Supervisors/Advisors
  • Zangl, Georg, Co-Supervisor (external), External person
  • Ruthammer, Gerhard, Supervisor (internal)
Award date15 Dec 2006
Publication statusPublished - 2006