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Acidizing Operation Design for Oil Fields by Use of Neural Network Method

Masoumi, Abdolkhalegh | 2016

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 49441 (06)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Goodarznia, Iraj
  7. Abstract:
  8. The acidizing operations have significant impact on productivity and production of oil and gas wells, so that wells having shell or regional damage are good candidates for well stimulation operations which could result in significant increase for efficiency or injectivity. Generally, the neural networks are nonlinear learning mathematical systems. In this project consists, At first, wellhead data of acidizing operation are collected in two Gachsaran oil field (38 wells) and Nar and Kangan gas field (35 wells). Generally, the neural networks are nonlinear learning mathematical systems. In the neural Network by using two algorithms, back propagation algorithm and Quick Propagation algorithm and output layer with linear stimulation function have been selected. Many of algorithms which simply have been differentiated from error function (performance) toward network parameters and we used gradient decrease method with the mean square error performance function as networks’ learning algorithms. In this project, we try to investigate the design of acidification operations for an oilfield and gas well by using artificial neural networks and conclude by comparing these characteristics to other methods
  9. Keywords:
  10. Neural Network ; Acidizing Treatment ; Neural Network ; Oil Wells ; Formation Damage

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