Measurement of Rock Deformation Parameters - Estimation of Stacked Fusion Model of Young’s Modulus

Abstract

Rock Young’s modulus is an essential parameter for formation stress characterization and oil and gas reservoir evaluation work and plays an important role in oil drilling-related engineering type work. Aiming at the problems of doubtful confidence in Young’s modulus measurements, time-consuming computation, and high measurement cost in oil drilling, this paper proposed Young’s modulus estimation method based on the Stacking fusion model. The method first processed the downhole vibration data to obtain its time-domain feature data and then used the time-domain feature data as the input to the fusion model while used the rock Young’s modulus data as the model output. The model learner used consists of three base learners, ANN, XGBoost, and CatBoost, with MLR as the model meta-learner. The mapping relationship between the time-domain features and Young’s modulus was established by this method, and the prediction and estimation of Young’s modulus parameters of the rock were finally realized. The results showed that the average absolute error (MAE) of the fused Stacking model was 0.2502 and the goodness-of-fit (R2) was 0.9691. Compared with other single models, the fused model based on Stacking had the advantage of being able to combine each single model, which provided a new method for estimation and prediction of Young’s modulus of rocks.