Method for identifying environmental effects in downhole data for hydrocarbon saturation estimation

Abstract

Methods and systems for drilling a well into a subsurface formation are configured for performing a downhole measurement to generate measured logging-while-drilling (LWD) data; retrieving a machine learning model that is trained using labeled LWD data, the labeled LWD data representing one or more environmental effects each causing a respective data signature in the LWD data, each respective data signature being associated with a corresponding label identifying the environmental effect; inputting the LWD data into the machine learning model; generating, by the machine learning model based on the inputting, a classification output representing at least one environmental effect represented in the LWD data; and generating, based on the classification output, corrected LWD data that removes a change to the LWD data caused by the environmental effect. The systems and methods are configured for drilling a well into the subsurface based on the corrected LWD data.