4D SUBSURFACE DENSITY INVERSION MODELING FOR HYBRID GRAVITY DATA USING GENETIC ALGORITHM APPROACH

• 主要作者: Gunawan, Indra
• 格式: Dissertations
• 語言: Indonesia
• 在線閱讀: https://digilib.itb.ac.id/gdl/view/54669

Using borehole gravity as a complement of surface gravity is believed to increase the subsurface inversion results, but the processing method for this kind of hybrid data remains challenging. This dissertation reports several notes regarding the effect of position and number of boreholes on the inversion results using a genetic algorithm approach. The inversion objective is to find the boundaries of the object area and background, where one bit of the chromosome represents the densities. We tested the inversion method using synthetic data and a water injection field model in Prudhoe, Alaska, to ensure that the calculation method can model actual field conditions. This research shows that borehole gravity data can increase the inversion's success rate by 13.33% in the synthetic model and 4.39% in the field model if it is placed in a good position. The most suitable location for obtaining the best results is in the most symmetrical position concerning the object density's geometry. This study also shows that adding borehole gravity data does not necessarily increase the inversion's success rate. The research results provide the recommendations for laying positions or selecting boreholes that will be used as a location for taking gravity data to obtain optimal subsurface inversion results. Thus, to obtain a more effective subsurface investigation result, a 4D surface gravity survey must be performed before specifying the borehole position. The 4D surface gravity survey aims to determine the object symmetry of the horizontal section