Application Of Blind Deconvolution In Processing Of Electrical Logging Data

The process of high-resolution electrical logging data which is based on deconvolution is a widely used important way to deal with logging data. Linear approximation is used to establish deconvolution model, so error signal which has the feature of uncertainty is brought into processing result. Blind deconvolution is intended to be applied and developed to deal with the error signal in order to improve the result of data processing of electrical logging. The main contents of this paper is as following.Firstly, in this paper, the process of high-resolution electrical logging data is analyzed and summarized. A research thought in which blind deconvolution is used to deal with electrical logging data is proposed in order to deal with problems in process of high-resolution electrical logging data, then a system model of blind deconvolution is established.Secondly, application of blind deconvolution in process of high-resolution electrical logging data is studied. Based on study of related features of high order statistics, the logic and principle of blind signal process is concretely analysed, then the basic principle and application of J _{r ,m} norm which is based on high order statistics is studied.Finally, for further process, J_{2 ,3}norm and J_{4 ,5}norm is used to deal with electrical logging data in order to deal with problems in process of high-resolution electrical logging data. Principles of J_{2 ,3}norm and J_{4 ,5}norm which belong to J _{r ,m}norm are introduced concretely, then applications of the two norms are studied. This article used some examples to compare performance of the two norms. At last, an approach of deconvolution is used to verify that the J _{r ,m} norm can be used to deal with noncausal logging data and improve the result of electrical logging data.