Publications

We present a present-day 3D lithospheric-scale thermal model covering the Sumatra area. The structural model was built based on published geological and geophysical data which resolves major sedimentary, crustal, and lithospheric mantle packages. This process allowed us to contrast the characteristics of four hydrocarbon-prone back-arc basins namely the North Sumatra Basin (NSB), Central Sumatra Basin (CSB), South Sumatra Basin (SSB), and Sunda Basin (SB) respectively. We moreover assessed variables that influence the present-day subsurface temperature and how it relates to the area tectonic setting. The modeling process began with the creation of a 3D geological model and setting up the upper and lower boundary condition. The temperature modeling was performed by constructing a forward model that consists of multiple 1-D temperatures using Basin 3D Temperature (B3T) simulation tools, which subsequently was used to build a 3D forward model. The model was iteratively calibrated by adjusting the boundary conditions and its prior thermal properties. An ensemble smoother with multiple data assimilation (ES-MDA) method was also applied to minimize the difference between model predictions and observations. A total of 147 temperature data sets from an open access Southeast Asia research group were used to assess model accuracy. The modeled temperature distribution varies in response to the imposed heterogeneous distribution of thermal properties assigned to the different units. First-order variations in the present-day thermal structure are primarily caused by the variability in the radiogenic heat produced within the different crustal compartments, variation in the lithospheric and upper crust thickness, and the thermal blanketing effect from the sedimentary layer. This study demonstrates how first-order variations in the structurally controlled distribution of thermal properties influence the regional thermal field. Both academia and industry also can use this model as the starting point for refinement of local models of a higher spatial resolution if denser data coverage is available.