Mud volcanoes in Grobogan are referred as the Grobogan Mud Volcanoes Complex in Central Java where there is evidence of oil seepages. This comprehensive research is to determine the characteristics and hydrocarbon potential of the mud volcanoes in the Central Java region as a new opportunity for hydrocarbon exploration. The Grobogan Mud Volcano Complex consists of eight mud volcanoes that have its characteristics based on the study used the geological surface data and seismic literature as supporting data on eight mud volcanoes. The determination of geological surface characteristics is based on geomorphological analysis, laboratory analysis such as petrography, natural gas geochemistry, water analysis, mud geochemical analysis and biostratigraphy. Surface data and subsurface data are correlated, interpreted, and validated to make mud volcano system model. The purpose of making the mud volcanoes system model is to identify the hydrocarbon potential in Grobogan. This research proved that each of the Grobogan Mud Volcanoes has different morphological forms. Grobogan Mud Volcanoes materials are including muds, rock fragments, gas, and water content with different elemental values. Based on this research result, there are four mud volcano systems models in Central Java, they are Bledug Kuwu, Maesan, Cungkrik, and Crewek type. The source of the mud is from Ngimbang and Tawun Formation (Middle Eocene to Early Miocene) from biostratigraphy data and it been correlated with seismic data. Grobogan Mud Volcanoes have potential hydrocarbons with type III kerogen of organic matter (gas) and immature to early mature level based on TOC vs HI cross plot. The main product are thermogenic gas and some oil in relatively small quantities. Water analysis shows that it has mature sodium chloride water. This analysis also shows the location was formed within formations that are deposited in a marine environment with high salinity. Research of mud volcanos is rarely done in general. However, this comprehensive research shows the mud volcano has promising hydrocarbon potential and is a new perspective on hydrocarbon exploration.
Fast modeling of gravity gradients from topographic surface data using GPU parallel algorithm
