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Pressure drop prediction in geothermal well is very important to get an optimum production strategy. This study presents an Artificial Neural Network (ANN) model for predicting the fast and accuratepressure drop in geothermal well. ANN model was built using 659 real data. These data sets were divide...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/21396 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Pressure drop prediction in geothermal well is very important to get an optimum production strategy. This study presents an Artificial Neural Network (ANN) model for predicting the fast and accuratepressure drop in geothermal well. ANN model was built using 659 real data. These data sets were divided into training, testing, and validation sets. The best ANN model to predict bottom hole pressure is 13-5-1 and to predict wellhead pressure is 13-10-1. The result of 13-5-1 model showed high accuracy with R in testing data set is 0.99084 and AE mean is 0.658719. And result of 13-10-1 model showed high accuracy with R in testing data set is 0.994914 and AE mean is 0.260328. |
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