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The Automatic Matching of the Static Model of the Reservoir during Geosteering Using LWD Data

Bagheri, Mohammad Navid | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53912 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Jamshidi, Saeed; Jahanbakhshi, Saman
  7. Abstract:
  8. In many fields, due to the lack of thickness of the reservoir layer, vertical drilling cannot be used due to low wellbore efficiency, so to solve this problem, directional and horizontal drilling is used. During drilling of highly deviated wells, to increase the efficiency of directional drilling, it should be tried to keep the path of the well completely in the reservoir layer, so that the full capacity of this type of drilling is used and the efficiency of the well is increased. To achieve this goal, Geo-Steer drilling technology is proposed in which decisions on the path of the well are made with the help of current reservoir and geological data. In this type of drilling, instantaneous logging tools are used during drilling to improve and increase the accuracy of the static model and reservoir layering. This update is based on matching the expected log based on the geological information of the adjacent wells with the logging while drilling data, and thus can increase the probability of the well moving in the desired layer. One of the most important and complex parts of a Geo-Steer drilling operation is matching the actual and expected logs. Nowadays, this adaptation in common commercial software is done manually by the user, which is usually not easy to do and may not be accurate enough, subject to human error. Therefore, there is a need for an alternative method that can properly adapt the logs away from human error. This project aims to provide and implement such a method that can perform the adaptation automatically and, also reducing human error, and finally, performing this difficult process with greater simplicity and accuracy. The algorithm used in this research is the Ensemble Kalman Filter, which by modeling the problem in the state space, provides the possibility of real-time updating the model, with the help of new measurement data
  9. Keywords:
  10. Directional Drilling ; State Space ; Ensemble Kalman Filter ; Logging While Drilling ; Geo-Steer Drilling ; Automatic Geo-Steering

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