Approximately 70% of the drinking water in Germany (BGR) and about 50% worldwide (IGREC 2011) are abstracted from groundwater using filter wells. Their implementation, operation and maintenance are major factors contributing to the costs of drinking water production. According to an international survey (Howsam, Misstear & Jones 1995 ), 40% of worldwide used water abstraction wells work inefficiently in terms of well performance or water quality. This implies high costs and a great potential for improvement, both for the (re-) construction of new wells (capital investment) and well operation (energy consumption, maintenance needs). The main reason for inefficient well performance is so-called well ageing, i.e. the decrease in performance due to biological, chemical and / or physical processes in and around the well. Dominant factors determining type, extension and location of deposits are the geology of the exploited aquifer together with the qualitative properties of the abstracted water, the well design (dimensions and materials), construction (drilling method) and operation. The project WellMa, initiated and financed by the Berliner Wasserbetriebe (BWB) and Veolia Eau, and coordinated at the Berlin Centre of Competence for Water (KWB), aimed at improving the efficiency of drinking water abstraction wells by identifying, evaluating and testing methods of well management including design, operation and maintenance to slow down well ageing. Set into relation to ranges, in which ageing processes are known to occur, the initial data of well sites were used to differentiate a low, medium or high potential for the occurrence of well ageing and to define the monitoring needs accordingly. Well ageing processes were distinguished into six types, each of them implying different pre-requisites and site conditions and leading to different monitoring and/ or maintenance requirements. For carbonate scaling, iron ochre formation, biofouling, corrosion, colmation and sand intake pre-requisites, triggers and threshold conditions were identified and implemented in a decision support system enabling well operators to prioritize the needs for monitoring, diagnosis or maintenance action taking into account the specific well and site characteristics.