Applying a Cutting Edge Solution to Predict Breakthrough Time of Water Coning in Naturally Fractured Reservoirs
Publish place: The 14th Conference of chemical Engineering
Publish Year: 1391
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
NICEC14_742
تاریخ نمایه سازی: 3 آذر 1391
Abstract:
Water coning caused water flow into the wellbore from below the perforations and causes several problems in wellbore and surface facilities. For solve these problems, we must know breakthrough time of water in wellbore. In this paper, potential application of feed-forward Artificial Neural network (ANN) is proposed to predict breakthrough time of water coning. The BP is implemented here to decide on initial weights of the parameters used in neural network. The developed BP-ANN model is examined by using new experimental data. Results obtained from the developed BP-ANN model were compared with the experimental water coning data. The average relative absolute deviation between the model predictions and the experimental data was found to be less than 9%. Results from this study indicate that application of BP-ANN in breakthrough time prediction which can lead to design of more efficient production scenarios.
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Authors
Mohammad Ali Ahmadi
petroleum University of Technology
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