Stochastic inversion of thermal data in a sedimentary basin: resolving spatial variability

Abstract

The concept of spatial stochastic processes and the techniques of geostatistics and stochastic inversion are presented as a means for evaluating the spatial variability of thermal properties and temperature in sedimentary basins. Data from the Uinta Basin of NE Utah are used to demonstrate the analysis. Bottom hole temperatures from oil and gas wells provide the best opportunity for a spatial analysis because of the large number and wide distribution of data. Errors in bottom hole temperatures are not too large to preclude their use and stochastic inversion provides an optimum method for removing random noise while retaining spatial resolution. Corrected bottom hole temperatures from 235 wells in the Uinta Basin are used to estimate: (a) average geothermal gradient as a function of position in the basin and (b) temperature gradients in individual formations, also as a function of position in the basin. The latter analysis yields a high-resolution estimate of temperature gradient and temperature throughout the basin. The temperature field shows variations of up to 50°C at a depth of 4 km and is estimated to be accurate to better than 5°C. This variation in temperature is consistent with conductive and advective mechanisms of heat transfer in a heterogeneous medium.