Path: TopS1-Final ProjectPhysics-FMIPA2017

INTERPRETASI NUMERIK 3D GRAVITY DENGAN PENDEKATAN REGULARISASI TIKHONOV

NUMERICAL INTERPRETATION OF 3D GRAVITY WITH TIKHONOV REGULARIZATION APPROACHIMATION

Undergraduate Theses from JBPTITBPP / 2017-11-08 09:44:10
Oleh : AHMAD IDRIS NURUL ULUM (NIM 10213078), S1 - Department of Physics
Dibuat : 2017-09-22, dengan 8 file

Keyword : Anomali gaya berat, Inversi, Pemodelan forward, Regularisasi.

Gravity merupakan metode geofisika yang bersifat pasif dengan memanfaatkan sumber alami gravitasi bumi. Pada metode gravity, distribusi batuan di bawah permukaan sangat mempengaruhi besarnya nilai gravitasi di titik pengukuran, hal tersebut karena setiap batuan memiliki densitas yang berbeda – beda. Dalam melakukan pemodelan bawah permukaan, maka data hasil pengukuran harus dikoreksi untuk mendapatkan anomali bourguer. Koreksi – koreksi yang dilakukan adalah koreksi tidal, drift, lintang, udara bebas, bourguer dan koreksi medan disekitar pengukuran. Pada tugas akhir ini pemodelan bawah permukaan dilakukan dengan menggunakan metode forward modeling 3D dan juga metode inversi dengan pendekatan regularisasi tikhonov. Parameter regularisai yang digunakan sebesar 1.2 , nilai alpha sebesar 0.5 dan nilai beta sebesar 1.1 sehingga didapatkan hasil inversi mendekati model foward.

Deskripsi Alternatif :

Gravity method is one of passive geophysical methods by using Earths gravity natural source. In this method, distribution of rocks under the subsurface greatly affects the gravity value in the measurement point, is is caused by variation of any rocks density. In the modeling of subsurface, measurement data must be corrected to get Bouguer anomaly. The corrections are tidal correction, drift, latitude, free air, bourguer and terrain correction around the measurement. In this study, subsurface modeling is constucted by using 3D forward modeling and also inverse modeling. Inverse modeling is contructed by Tikhonov regularization approximation. Regularization parameter used in this study is 1.2 , 0.5 for alpha value, and 1.1 for beta value. Based on these modeling, we get the inversion result is closed to forward modeling.

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