Slickline-deployed instruments are commonly used to perform measurement and service operations in oilwells. In order to accurately determine,the downhole position of a suspended instrument, a device known as an electro-mechanical casing collar locator (EMCL?',is sometimes used. The device is first lowered into a well; and then. slowly withdrawn. When a casing collar is encountered, the EMCL device causes changes in the line tension.,.These changes in line tension, which are measured at the surface, are correlated to collar locations, and hence, instrument deptti. Like many other applications, noise from different sources during slickline jobs may add contaminating noise' or cause destructive interference in the monitored of tension:signals. In this paper, a method of using an adaptive neural network to filter the tension signal to remove unwanted noise is described. A theoretical discussion and the review of results of experimental testing are presented