Heat supply pipeline detection based on temperature gradient data of shallow ground

Abstract

Heat supply pipelines are a critical component of urban infrastructure, with numerous underground projects relying on this crucial and often concealed system. In cases where blueprints are unavailable, it is crucial to determine the precise location and depth of heat supply pipelines. One of the most straightforward methods for detecting these pipelines is measuring underground temperature. Temperature gradient data is less sensitive to environmental temperature changes for detecting shallow heat sources than temperature data. This paper presents an extension of the correlation imaging method to handle temperature gradient data. This method can accurately determine the horizontal center position and the depth of the heat source. This temperature tomographic approach is reliable and has a high resolution, as evidenced by both synthetic and field examples.