Research on intelligent identification technology of lithology wireless remote transmission based on element measurement

Abstract

At present, there are many deficiencies in the process of shale gas drilling traditional drilling. There are mainly backward traditional drilling technology, traditional drilling technology which cannot guarantee efficient and stable drilling of shale gas well and traditional logging method cannot effectively identify the lithology of fine rock cuttings. Furthermore, the relevant drilling model has not formed a mature system, and it is impossible to improve the working condition by rock layer judgement through drilling parameters collection. In view of the above problems, this study proposes to combine the data of element logging with the ground monitoring parameters, and transmit them to the host remotely. At the same time, a large number of historical data are used to analyse the cuttings data with the improved grey weight clustering method and entropy weight method, and an intelligent division model of rock stratum identification is constructed. At the same time Then, the functional relationship between multi parameters and strata is established to judge the possible working conditions during the drilling process. A set of formation interpretation and evaluation methods is formed according to different elements and logging parameters of different lithology. The analysis results are compared with the actual drilling conditions to verify the accuracy of the development trend analysis of the drilling conditions, and the inference engine is modified according to the results to improve the well site conditions. Using data from the deep shale layer of a well drilled in southwest, this paper makes comparison between the analysis results of several methods. The results of comparison verify the accuracy of the new method.