Muflich, Laili (2016) Prediksi Tekanan Pori Dan Identifikasi Zona Geopressure Menggunakanmarkov Chain Monte Carlo. Undergraduate thesis, Institut Teknologi Sepuluh Nopember Surabaya.
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Abstract
Prediksi tekanan pori digunakan untuk menentukan berat lumpur yang digunakan dalam proses pengeboran, desain casing lubang sumur dan mencegah bencana pengeboran. Prediksi tekanan pori ini dilakukan menggunakan data log sonic dan resistivitas melalui pendekatan Eaton dan ekuivalen kedalaman untuk estimasi kurva Normal Compaction Trend (NCT). Baik data log sonic dan resistivitas umumnya terkontaminasi noise dari berbagai sumber dengan karakter yang belum diketahui secara pasti, oleh karena itu estimasi kurva NCT menggunakan algoritma Markov chain Monte Carlo (MCMC) dengan memanfaatkan prinsip generalized likelihood uncertainty estimation (GLUE). Hasil process ini menunjukkan bahwa metode ini robust terhadap noise-noise pada log sonic dan log resistivitas. Selanjutnya, parameter pertrofisika ini digunakan untuk memprediksi tekanan pori. Hasil prediksi tekanan pori terbesar menggunakan data log sonic pada sumur #XX, #YY, #ZZ secara berurutan ialah 6990.79 psi, 6901 psi, 10068 psi, sedangkan berdasarkan log resistivitas masing-masing sebesar 6375.18 psi, 7780 psi, dan 9990 psi. Berdasarkan hasil ini, dapat
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diketahui juga bahwa sumur #XX merupakan sumur normal sedangkan sumur #YY dan #ZZ merupakan sumur overpressure pada masing-masing kedalaman 2585.9 meter dan 2083.8 meter. Overpressure pada kedua sumur ini secara berurutan disebabkan oleh proses loading (undercompaction) dan unloading
==========================================================================================Pore pressure prediction used to determine mud weight that would be used in a drilling processing, casing design well-bore, and to prevent drilling hazard. Pore pressure prediction can be done using sonic log and resistivity log through Eaton’s approximation and equivalent depth method to estimate Normal Compaction Trend (NCT) Curve. Both of methods generally effected by noise from some unknown source. Thats why, NCT curve estimation using Markov Chain Monte Carlo (MCMC) Algorithm with generalized likelihood uncertainty estimation (GLUE) principle. This process shows that this method is robust for noise in both sonic log and resistivity log in result. And then, this petrophysics parameter used to predicting pore pressure. This prediction has a result that the largest pore pressure using sonic log in well #XX, #YY, and #ZZ respectively are 6990.79 psi, 6901 psi, 10068 psi, whereas using by resistivity log in same wells respectively are 6375.18 psi, 7780 psi, and 9990 psi. From this result, known that well #XX is a normal well, whereas well #YY and #ZZ is an overpressure well in depth 2585.9 meter and 2083.8 meter. Cause of overpressure in both wells respectively are loading (undercompaction) and unloading process.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSFi 622.338 2 Muf p |
| Uncontrolled Keywords: | Data Well-Log, Geopressure, GLUE, MCMC, Normal Compaction Trend, Tekanan Pori |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) > TA660.T34 Tanks. Pressure vessels |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Physics > 45201-(S1) Undergraduate Thesis |
| Depositing User: | EKO BUDI RAHARJO |
| Date Deposited: | 01 Apr 2020 02:19 |
| Last Modified: | 01 Apr 2020 02:19 |
| URI: | http://repository.its.ac.id/id/eprint/75628 |
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