<![CDATA[Gravity data inversion requires a good initial mesh model to generate a good subsurface model. Ambiguities in gravity data can be reduced by Euler deconvolution’s point cluster result that show its position and depth. These point cluster can give an additional information to shape the initial mesh model for inversion. The purpose of the study was to determine the influence of Euler deconvolution to the inversion. Inversion was done by the steepest descent algorithm. Euler deconvolution method and inversion algorithm were tested on synthetic models and showed good results that Euler deconvolution able to construct actual density distribution. These methods were applied to the gravity data on the "B24” geothermal field. Residual anomaly map has a value of -12 to 24 mGal. The geothermal field is estimated that it has a major fault which mainly striking in northwest-southeast direction. These estimates are supported by the results of Euler deconvolution which indicate the presence of fault and graben structure. Euler deconvolution and inversion method were applied perpendicularly to the main structure at the southwest-northeast direction. The results of this study are the Euler deconvolution method is able to provide information for a mesh geometry for inversion. From the inversion result, “B24” geothermal field is estimated has a high-low-high density distribution dominated by andesite and tuff. To improve the results of the research, it needs a measurement point addition, additional modeling area, geological and geochemical data to strengthen the interpretation.Keywords: density, Euler deconvolution, gravity inversion, geothermal]]>
