In applying Darcy's law to fluid flow in geologic formations, it is generally assumed that flow variations average to an effectively constant formation flow property. This assumption is, however, fundamentally inaccurate for the ambient crust. Well-log, wellcore, and well-flow empirics show that crustal flow spatial variations are systematically correlated from mm to km. Translating crustal flow spatial correlation empirics into numerical form for fluid flow/transport simulation requires computations to be performed on a single global mesh that supports long-range spatial correlation flow structures. Global meshes populated by spatially correlated stochastic poroperm distributions can be processed by 3D finite-element solvers. We model wellbore-logged Dm-scale temperature data due to heat advective flow into a well transecting small faults in a Hm-scale sandstone volume. Wellbore-centric thermal transport is described by Peclet number ≡ 0 V 0 / ( 0 = wellbore radius, V 0 = fluid velocity at 0 , = mean crustal porosity, and = rock-water thermal diffusivity). The modelling schema is (i) 3D global mesh for spatially correlated stochastic poropermeability; (ii) ambient percolation flow calibrated by well-core porosity-controlled permeability; (iii) advection via faultlike structures calibrated by well-log neutron porosity; (iv) flow ∼ 0.5 in ambient crust and ∼ 5 for fault-borne advection.
Heat-transfer coefficients are presented for water flowing vertically in thin rectangular channels (0.1 × 2.5 in.) 18 and 36 in. long and heated electrically around the entire periphery. The range of variables covered is: 65 to 200 psia pressure, 90 to 200 F sub-cooling, and 4 to 50 fps water velocity. Heat-transfer correlations are given for data along the narrow and wide faces of the rectangular test section. Burnout data also are reported with steam blanketing occurring first at the corner of the test section. The proposed correlating equation, valid at the narrow face of the test section, gives values considerably lower than those obtained in a circular pipe.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.