Casing Well Logging Signal Processing Methods

Cased-hole logging can obtain information of both casing damage and geological reservoir beyond casing, therefore providing important basis for inspecting of casing damage, searching for the remaining oil and understanding of reservoir conditions corresponding to environmental damage. This paper mainly investigate the the perspective of signal processing for cased-hole logging, including the cased-hole logging signal noise suppression, data curve fitting and data imaging.This paper firstly introduces the transient electromagnetic logging method (TEM) based cased-hole logging technique and establishes the corresponding model The receiving signal model is also derived by using the Maxwell equations. Based on this, this paper mainly focuses on the signal processing methods of cased-hole logging techniques. The wavelet filtering based cased-hole logging signal processing noise suppression method and the the method of depth correction is presented, respectively. Furthermore, this paper also investigates the curve fitting and artificial neural networks based methods for cased-hole logging signal interpretation and imaging. Simulation results show that the proposed methods can suppress the noise effectively and can achieve the cased-hole logging image.Finally, this paper designs the LabVIEW communication and data processing software based on dual serial port, and carries out a large number of system simulations, indoor, outdoor and underground experiments. Simulation and experimental results show that the proposed image noise suppression, curve fitting and data interpolation such as casing well signal processing methods can effectively reduce the influences of electromagnetic radiation, noise and signal transmission error, which would make important foundation for cased-hole logging data inversion and interpretation.