According to different regions, conditions and requirements, the cross-fault measurement specifications is allowed to measure at different resurvey periods, and resulted in unequal interval observation data. The unequal interval observation data is a common phenomenon data, the difference on both sides of the fault is observed by geological investigation, historical record, artificial observation, simulated record, digital sampling, encrypted observation before and after the event, change of observation equipment, change of observation environment, human factors, etc, and the unequal interval observation data is obtained. The characteristics of the unequal interval observation data is not only shown in time, but also in space. The unequal interval observation data is usually preprocessed into equal interval data by some kind of algorithm chosen before the subsequent complex calculation. In the data processing of cross-fault measurement, the unequal interval observation data is usually preprocessed into equal interval data, and then calculated, which leads to a series of new problems, such as time calculation, synchronization, master-slave relationship, comparability and so on. In view of unequal interval observation data in cross-fault measurement, some new problems are tried to solve in unequal interval data matching calculation by using conventional methods combined with some algorithm requirements, data characteristics and practical experience, and their adaptability in various algorithms is investigated in this paper. These works contribute to the improvement and development of cross-fault survey data processing methods, and enhance the role of cross-fault survey data in earthquake protection and disaster reduction.