Estimating In-Situ Thermal Conductivity from Log Data

Abstract

Hole 857C, drilled in Middle Valley, northern Juan de Fuca Ridge, during Leg 139 of the Ocean Drilling Program, penetrated about 470 m of turbidite sediments. Below the sediments the hole intersected a series of basaltic sills interbedded with sediments. Hole 857C is located south of an active hydrothermal vent field in an area where seafloor heat flow measurements show values exceeding 0.8 W/m 2 . This hole was successfully logged with the seismic and lithodensity tool string. Open-hole temperatures at a depth of 480 mbsf are as high as 222°C. The porosity profile of Hole 857C, based on log-derived wet-bulk densities, forms the basis for the calculation of a thermal conductivity profile using a binary mixture of sediment grains and seawater and a geometric mean model. The thermal conductivity of the grains is assumed to be 2.6 W/m-K (Davis and Seeman, this volume). High temperatures encountered in Hole 857C require that temperature effects on the thermal conductivity must be included. The variation of the thermal conductivity of seawater is well known. The decrease of the thermal conductivity of the grains with increasing temperature is calculated after Sass et al. (1992) and Chapman et al. (1984). A purely conductive vertical heat flow is assumed to allow the iterative modeling procedure caused by the nonlinear nature of the problem. The model calculations show that the results of a simple model with constant thermal parameters are similar to those of a model that includes a temperature-dependent seawater thermal conductivity and temperature coefficient of the grain thermal conductivity after Sass et al. (1992). This surprising result is a consequence of the competing effects of decreasing porosity with depth, decreasing thermal conductivity of the grains with depth (and temperature), and the variation of the thermal conductivity of seawater with temperature. Results based on temperature corrections of Chapman et al. (1984) give unrealistically high temperatures at the base of the sediments. Varying the grain thermal conductivity between 2.6 and 3.2 W/m-K results in a range of thermal conductivity profiles that predict temperatures that are in agreement with observed vent fluid temperatures.

Heat Flow and Hydrologic Characteristics at the AND-1B borehole, ANDRILL McMurdo Ice Shelf Project, Antarctica

“…Substituting these values of λ b and Φ into Equations (3) and (4) yields estimates for the grain thermal conductivity, λ g , that range from 2.8 to 3.2 W/mK and are mainly a function of quartz content. These values are in good agreement with those reported by Villinger et al (1994) for marine sediments, where values of λ g between 2.6 and 3.2 W/mK were found to predict temperature profi les accurately. Consequently, we use this range of values for the grain thermal conductivity (2.8 -3.2 W/mK) in our computation of bulk thermal conductivity for AND-1 sedimentary rocks.…”

Physical and thermal properties of mud-dominant sediment from the Joetsu Basin in the eastern margin of the Japan Sea

“…Empirical formulae for relationships between thermal properties and the porosity and volume fraction of constituent minerals for marine sediments have also been investigated (Kinoshita 1994;Villinger et al 1994;Goto and Matsubayashi 2009). Because these relationships are each expressed by a simple formula, they are useful for estimating unknown properties from known properties.…”

“…We suggest that the grain density, grain thermal conductivity, and grain thermal diffusivity depend In addition, the thermal conductivity of marine sediment has been predicted from its mineral composition. This has been performed using the relationship between the thermal conductivity of marine sediment and the porosity and volume fraction of the constituent minerals of the sediment (Kinoshita 1994;Villinger et al 1994;Goto and Matsubayashi 2009).…”

Using neural networks to predict thermal conductivity from geophysical well logs

“…under 0.6 W m −1 K −1 , which is the thermal conductivity of pure water). This is not a surprising result, as porosity is the main factor that controls thermal conductivity of medium-high porosity sediments (Villinger et al 1994). This slightly improves the predictions accuracy of both the MLP and the MLR, while holding the clear superiority of the former over the latter method (Table 2 [bottom]).…”

“…Consequently large areas of major interest such as passive margins have been scarcely investigated and their thermal regime remains poorly known (Lucazeau et al 2004). A mixing law-most often a geometric mean (Woodside & Messmer 1961a,b)-is then applied to deduce the global thermal conductivity (Brigaud et al 1990(Brigaud et al , 1992Della Vedova & Von Herzen 1987;Demongodin et al 1991;Hartmann et al 2005;Vasseur et al 1995;Villinger et al 1994;Williams et al 1988). Several types of temperature measurements are routinely available, such as bottom-hole temperatures (BHT), or fluid temperatures acquired during reservoir tests (drillstem tests, DST), with uncertainties around 5-10 • C after correction (Brigaud 1989).…”