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تشخیص و بررسی اثر بخشی عدم قطعیت‌های موجود در مدل یکی از میادین نفتی مشترک بر فرایند تزریق آب
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تشخیص و بررسی اثر بخشی عدم قطعیت‌های موجود در مدل یکی از میادین نفتی مشترک بر فرایند تزریق آب

پنبه ای، مهدی Panbei, Mahdi

Characterization and Investigating the Effectiveness of Reservoir uncertainty on Waterflooding in a Shared Oil Field

Panbei, Mahdi | 2017

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 49288 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Masihi, Mohsen; Ayatollahi, Shahaboddin
  7. Abstract:
  8. In field management workflow, after preparation of dynamic reservoir model, next step is determining the uncertain parameters and history matching. In this step, simulation model is conditioned to available field data. In this inverse problem, different geological and petrophysical properties may provide equally good history matches. Such diverse models are likely to show different production behaviors in future. This ties the history matching with the second step, uncertainty quantification of predictions. Multiple history matched models are essential for a realistic uncertainty estimate of the future field behavior.This thesis introduces the application of two novel population-based algorithms for history matching and uncertainty quantification of petroleum reservoir models. Imperialist competitive algorithm and state of matter search are used to search the space of parameters to find multiple history matched models and, using a Bayesian framework, the posterior probability of the models are evaluated for prediction of reservoir performance.Next step in field management procedure is the optimization of development plan. To maximize the reservoir performance, we optimize the number of producers and injectors, their types (e.g., vertical, horizontal or multilateral), locations and trajectories. Genetic algorithm serves as the engine for this optimization problem. Effects of uncertain engineering parameters are also considered in this optimization. In addition, an experimental design methodology is used to reduce the number of simulations required to quantify the effects of the multiple uncertain parameters during this optimization process
  9. Keywords:
  10. History Matching ; Imperialist Competitive Algorithm ; Genetic Algorithm ; Experimental Design ; Matter State Search ; Field Development Plan Optimization

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