| Title | Preliminary Results of Elaborating a Methodology for Determining the Thermal Conductivity of Clastic Sediments Using Well Logs in Hungary |
|---|---|
| Authors | János MIHÃLYKA, Petra PARÓCZI, László LENKEY, DezsÅ‘ DRAHOS, László BALÃZS |
| Year | 2020 |
| Conference | World Geothermal Congress |
| Keywords | well log interpretation, Bayes-inversion, thermal conductivity |
| Abstract | The thermal conductivity of rocks can be deduced from available data of exploration wells such as core samples, cuttings, lithological descrptions and geophysical well logs. 70% of Hungary’s surface is covered by Neogene and Quaternary clastic sediments. The average sediment thickness is 1-2 km, but in the deepest troughs it reaches 5-8 km. As the thermal conductivity of clastic sediments is lower than the conductivity of the crystalline basement, the sediments have a significant influence on the temperature distribution and heat flow density. By this time in Hungary most of the temperature measurements were carried out in clastic sediments. Furthermore, the thermal conductivity of more than 300 sediment core samples were measured using the Transient Line Source technique in laboratory conditions. We present a methodology for determining the thermal conductivity of clastic sediments using geophysical well logs and thermal conductivity data measured in laboratory. In general, the method determining thermal conductivity from well logs bears large significance in geothermal studies in Hungary, because orders of more thermal conductivity data can be obtained than presently available. The thermal conductivities determined by high resolution in wells can be interpolated between the boreholes by statistical methods and 3D numerical thermal models can be constructed. Here we present our preliminary results based on the data of 3 exploration wells. Several well log combinations and thermal conductivity measurements from 96 core samples were used to work out the method. The lithological composition consisting of shale, sand, marl and water were identified and the volumetric fractions of these components were derived from wireline logging data such as natural gamma ray, resistivity, bulk density and neutron porosity logs. The lithological composition is determined with Bayes-inversion applying the weighted least squares method. The effective thermal conductivity was computed with applying an appropriate mixing law using the thermal conductivity values of the lithological components. The thermal conductivity derived from well logs were tested using the temperature and pressure corrected archive thermal conductivity measurements of core samples. This work was supported by the Hungarian Scientific Research Fund (OTKA) in the framework of project No. K 129279, and it is part of the ENeRAG project that has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 810980. |