Principal Slip Zone determination in the Wenchuan earthquake Fault Scientifc Drilling project hole 1: considering the Bayesian discriminant function

Accurate determination of the Principal Slip Zone (PSZ) of earthquake fault zones is a key task of earthquake Fault Scientifc Drilling for future earthquake control. The fault zone structure of Wenchuan earthquake is complex, and there are many strong earthquakes recorded on the fault zone, which make determining the PSZ in the Wenchuan earthquake Fault Scientifc Drilling project-hole 1 (WFSD-1) difcult. At present, core analysis of whole coring is the decisive method for determining PSZ depth, and the fresh fault gouge at 589.2 m is the PSZ in WFSD-1. Abundant and comprehensive logging data can only be used as evidence to judge the PSZ. Based on the discrimination function and hyperplane equation in Bayes ian discriminant classifcation, we derive a new algorithm for computing the PSZ possibility using a Bayesian Discrimina tion function (PSZP-BDF) based on the simplifed model, and set up a mode to determine the PSZ directly using machine learning of well logging. For the verifcation of WFSD-1, the fault gouges are successfully identifed and the PSZ depth is accurately located. The algorithm objectively learns the sample data, which is naturally adaptive to the region. The calculation procedure is simple and does not require expensive coring data or heavy core tests in the well. The calculation speed is fast, using multiple physical data types. The PSZP-BDF algorithm is suitable for processing and interpreting earthquake fault scientifc drilling data.