Geothermics, Vol.66, 61-72, 2017
Using seismic data to estimate the spatial distribution of rock thermal conductivity at reservoir scale
Subsurface rock thermal conductivity predictions from laboratory measurements are limited by the number of available borehole data or of analogue outcrops. A method for spatially predicting subsurface rock thermal conductivity is demonstrated by using a combination of laboratory measurements on drill cores and in-situ geophysical measurements. Continuous measurements of thermal conductivity were performed on lower Permian Rotliegend drill cores of 80 m and 60 m length, respectively. The cores originate from the prominent Messel pit, Germany. In addition to the rock core measurements, numerous seismic sections of the study area as well as borehole geophysics from the respective boreholes are available. The seismic data is used additionally to the measured thermal conductivities and porosity as a secondary trend variable for interpolation by applying kriging with external drift (RED). Seismic data and thermal conductivity are physically related, mainly due to porosity, and can correlate strongly. Seismic data fulfils the main criteria required by KED as it varies smoothly and is known at all locations of the primary data and all locations to be estimated. In a primary study thermal conductivity interpolation in 1D along one of the two boreholes is studied. Finally in 2D along one seismic profile, which strikes through both boreholes, the method is tested. Results of interpolated dry thermal conductivity and porosity in 2D are geologically reasonable. The saturated bulk-rock thermal conductivity was determined using a geometric-mean model based on the interpolated porosity and dry thermal conductivity data. Both studies prove that the result is better while seismic data is used as secondary trend variable. (C) 2016 Elsevier Ltd. All rights reserved.
Keywords:Thermal conductivity;Seismic velocity;Kriging with external drift;Ordinary kriging;Secondary variable;Geophysical borehole logs