Improving Prediction of Wireline Data Using Artificial Neural Network
This paper is dedicated to investigate the capabilities of artificial neural network (ANN) to improve prediction of petrophysical properties. Furthermore, this project is intended to test capability of network to predict the logging tools readings based on other tools readings. For petrophysical da...
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IRC
2015
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| 在線閱讀: | http://utpedia.utp.edu.my/16682/1/eline_data_for_Dulang_field_with_Artificial_Neural_Network2%20%281%29.pdf http://utpedia.utp.edu.my/16682/ |
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my-utp-utpedia.166822017-01-25T09:35:55Z http://utpedia.utp.edu.my/16682/ Improving Prediction of Wireline Data Using Artificial Neural Network Aly Rafaat, Ahmed Mohamad Essam T Technology (General) This paper is dedicated to investigate the capabilities of artificial neural network (ANN) to improve prediction of petrophysical properties. Furthermore, this project is intended to test capability of network to predict the logging tools readings based on other tools readings. For petrophysical data prediction, it will be limited to predicting values of porosity by comparing predicted values from different models and values obtained from core data. Data obtained for core is considered to be the most accurate representation of petrophysical data. Hence, it is used as a reference data for testing capabilities of the model and training ANN networks. IRC 2015-01 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/16682/1/eline_data_for_Dulang_field_with_Artificial_Neural_Network2%20%281%29.pdf Aly Rafaat, Ahmed Mohamad Essam (2015) Improving Prediction of Wireline Data Using Artificial Neural Network. IRC, Universiti Teknologi PETRONAS. (Submitted) |
| institution |
Universiti Teknologi Petronas |
| building |
UTP Resource Centre |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Teknologi Petronas |
| content_source |
UTP Electronic and Digitized Intellectual Asset |
| url_provider |
http://utpedia.utp.edu.my/ |
| language |
English |
| topic |
T Technology (General) |
| spellingShingle |
T Technology (General) Aly Rafaat, Ahmed Mohamad Essam Improving Prediction of Wireline Data Using Artificial Neural Network |
| description |
This paper is dedicated to investigate the capabilities of artificial neural network (ANN) to improve prediction of petrophysical properties. Furthermore, this project is intended to test capability of network to predict the logging tools readings based on other tools readings.
For petrophysical data prediction, it will be limited to predicting values of porosity by comparing predicted values from different models and values obtained from core data.
Data obtained for core is considered to be the most accurate representation of petrophysical data. Hence, it is used as a reference data for testing capabilities of the model and training ANN networks. |
| format |
Final Year Project |
| author |
Aly Rafaat, Ahmed Mohamad Essam |
| author_facet |
Aly Rafaat, Ahmed Mohamad Essam |
| author_sort |
Aly Rafaat, Ahmed Mohamad Essam |
| title |
Improving Prediction of Wireline Data Using Artificial Neural Network |
| title_short |
Improving Prediction of Wireline Data Using Artificial Neural Network |
| title_full |
Improving Prediction of Wireline Data Using Artificial Neural Network |
| title_fullStr |
Improving Prediction of Wireline Data Using Artificial Neural Network |
| title_full_unstemmed |
Improving Prediction of Wireline Data Using Artificial Neural Network |
| title_sort |
improving prediction of wireline data using artificial neural network |
| publisher |
IRC |
| publishDate |
2015 |
| url |
http://utpedia.utp.edu.my/16682/1/eline_data_for_Dulang_field_with_Artificial_Neural_Network2%20%281%29.pdf http://utpedia.utp.edu.my/16682/ |
| _version_ |
1739832289834041344 |
| score |
13.251813 |