Annotation of Using Borehole Time-Lapse Gravity by Genetic Algorithm Inversion for Subsurface Modeling

We present the annotation to a genetic algorithm (GA) method for an inverse synthetic subsurface density model using surface and borehole time-lapse gravity data. The objective of the inversion is to find the boundaries of the object area and background, where one bit of the chromosome represents the densities. The model that was used in this paper was a simple homogeneous body anomaly and a simplified real water mass injection model in order to argue that the code is suitable for field modeling. We show the influences of the existence of borehole gravity data and location towards the inversion, where the result indicates that an additional good borehole location could increase the success rate up to 13.33% compared to without gravity borehole data for the simple model and up to 4.39% for the field model. The inversion produced the best results when the borehole positions were placed in a state of symmetry towards the body object's mass.