Long (horizontal) completion intervals typically show a wide variation in the inflow distribution along their length due to either formation heterogeneity or (frictional) flow pressure losses. Monitoring of the inflow profiles in such wells is an important step in efficient reservoir management. Accurate temperature measurements (using distributed temperature sensors, permanent downhole gauges or other forms of production logging) have become more widely available in recent years. Many published papers describe temperature sensing and its phenomenological interpretation; but few attempts have been made recently to develop a comprehensive mathematical basis for the analysis of downhole temperature behaviour.This paper presents a holistic, analytical, mathematical model for calculation of the temperature profile in horizontal wells producing liquids for reservoirs where thermal recovery methods are not being employed. The model presented in this paper rigorously accounts for (1) the Joule-Thomson effect, (2) convection, (3) transient fluid expansion and (4) time-dependent heat loss to the surrounding layers.A synthetic horizontal well model has been built using a commercial, scientific simulator as a test-bed to provide the data to allow a rigorous evaluation of the efficacy of our novel analytical methods. Asymptotic, analytical solutions have also been found for transient and steady-state flow. It has also been found possible, in addition to these constant flow rate solutions, to apply the well known pressure analysis solution techniques for the estimation of (1) thermal properties and (2) inflow profiling.The methods proposed here can be applied to a wide variety of well completion types, flow conditions and system properties. They form the basis for the calculation of oil and water flow phase cuts and distributions based purely on temperature measurements. Their use will further increase the potential applications of the modern downhole monitoring and control capabilities currently being installed in wells. As such, they will form an essential element of the "digital oil field".