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

Abstract

Accurate determination of the Principal Slip Zone (PSZ) of earthquake fault zones is a key task of earthquake Fault Scientific 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 Scientific Drilling project-hole 1 (WFSD-1) difficult. 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 Bayesian discriminant classification, we derive a new algorithm for computing the PSZ possibility using a Bayesian Discrimination function (PSZP-BDF) based on the simplified model, and set up a mode to determine the PSZ directly using machine learning of well logging. For the verification of WFSD-1, the fault gouges are successfully identified 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 scientific drilling data.