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The physical properties of rocks important to know that the porosity, water saturation and permeability. The physical properties of rocks can be measured in two ways in the laboratory measurements of rock samples and well logging. Well logging is the process of measuring the physical properties of t...
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| 主要作者: | |
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| 格式: | Final Project |
| 語言: | Indonesia |
| 在線閱讀: | https://digilib.itb.ac.id/gdl/view/20650 |
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| 機構: | Institut Teknologi Bandung |
| 語言: | Indonesia |
| 總結: | The physical properties of rocks important to know that the porosity, water saturation and permeability. The physical properties of rocks can be measured in two ways in the laboratory measurements of rock samples and well logging. Well logging is the process of measuring the physical properties of the borehole to search for economically valuable fluid content beneath the earth's surface. Artificial neural networks is used to determine the relationship between the data logs, lithology and porosity. Starting with training of log data that is already known lithology and porosity values, then the model can is used to determine the lithology and porosity of the rock formations others. Log data is are used as input that is the sonic log, density and photoelectric effect on sandstone rock, limestone, dolomite, and anhydrite in porosity ranges from 0,01 to 0.4 and net of the effect of shale. Water saturation and permeability calculated after getting lithology and porosity using Archie equation and Timur equation. Lithology training stops with error reaches 0.00001, while for training porosity stopped by reaching the <br />
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maximum epoch. The training result is quite accurate with error rate of 18% to lithology and porosity has error that is 4.7746%. |
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