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EOR Screening in Fractured Reservoirs Using Artificial Intelligence Technique

Eghbali, Sara | 2012

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 43181 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Ayatollahi, Shahabaldin; Bozormehry, Ramin
  7. Abstract:
  8. Part1: Since conventional production has continued to fall, oil Production through EOR processes will supply an increasing percentage of the world’s oil demand in future years. Therefore; the importance of choosing the best recovery method becomes increasingly important to decrease the risk and find the best solution to the oil production decline from matured reservoirs. An expert system whose main task is to recommend the most appropriate EOR method will be described. The proposed expert system is utilized fuzzy logic system to screen four well known EOR methods of miscible 〖CO〗_2 injection, miscible HC gas injection, polymer flooding and steam injection based on reservoir and rock properties. Since this fuzzy expert system has incorporated the rules from successful past experiences, it reduces the requirement of massive laboratory and field data. The expert system can be used as a quick estimation for the successfulness possibility of the EOR processes for a specific reservoir before executive decisions are made to commit the technique into the field. The results of this work are now incorporated into a screening software capable of ranking proper EOR techniques. The output results were compared with the results of a system.Part 2: The potential for enhanced oil recovery in oil-wet, fractured carbonates is very high because of large hydrocarbon reserves retained in the matrix of giant oil reservoirs in the Middle East. Naturally fractured Reservoirs (NFR) are often considered to be short-lived with high flow rates, rapid production declines, and low ultimate recovery factors. Engineers often look unfavorably on fractured reservoirs because they are difficult to be characterized and the decision to use any EOR techniques must be carefully and wisely made in order to avoid production failure. Since many EOR methods were found to be less feasible in naturally fractured reservoirs, screening EOR methods in these reservoirs is of great importance to save the time and money. The aim of this expert system is to provide a tool to screen EOR processes for NFR on the basis of reservoir characteristics. Because of the sparse field-scale information available on fractured reservoirs, and also the cost and time involved for the measurement of the parameters specified for fractured reservoirs, reservoir simulation was chosen as the basic technique to assess the effects of different fracture parameters on the success of EOR method. Furthermore; fuzzy logic expert system was implemented effectively to predict the most suitable EOR technique for each specific fractured reservoir. The results were tested against some of the field experiences available which were found to be promising
  9. Keywords:
  10. Fuzzy Logic ; Enhanced Oil Recovery ; Fractured Reservoirs ; Screening Analysis

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