Direction change detection from noisy data and application to mud logging data processing

Motivated by mud logging data processing in petrol exploitation, the detection of changes in data line direction is studied in this paper. Because of noise corruption to all measured variables, the classical regression model is not suitable to this problem. After the formulation of an appropriate model, the problem of noise covariance matrix estimation is first considered, then a particular generalized likelihood ratio test is derived for direction change detection. Examples of its application to mud logging data processing are presented for illustration.