Hydrocarbon microseepage is a common phenomenon occurring in areas with the presence of onshore oil and gas reservoirs, characterized by the abnormal natural surface spectral landscape characteristics of mineral alteration features and geobotanic anomalies that can be detected by satellite imagery. Therefore, this study aims to find spatial models of oil and gas reservoirs through detection approaches of hydrocarbon microseepage and its relation with the physical condition of study area by utilized the satellite imagery. The parameters used in are alteration symptoms of clay-carbonate, ferric iron, and ferrous iron minerals, geobotanic anomaly symptoms, geology characteristic, and geomorphology characteristic. A multispectral satellite imagery of Sentinel 2 was used as an input for the directed principal component analysis (DPCA) method and vegetation index, to detect mineral alteration phenomenon and geobotanic anomaly, respectively. Then each parameter was integrated using fuzzy logic method giving a result of the distribution of hydrocarbon microseepage area. As a results, this study indicates the presence of hydrocarbon microseepage phenomenon in the research area with the extent of 488,3 Ha or 1,46% of the total of research area. The distribution of hydrocarbon microseepage is distributed in area around oil and gas field, and also linear distributed around Merang River. The distribution of hydrocarbon microseepage in study area also agglomerated in Kasai Formation, area near fault, and the area with lacustrine landform characteristics.