Lithology identification method based on feature contribution degree and PSO-Catboost
The invention discloses a lithology identification method based on a characteristic contribution degree and PSO-Catboost, and the method is characterized in that the method comprises the steps: collecting well logging and logging data of a drilled well; defining different digital tags for different...
Saved in:
Main Authors | , , , , , , , , , , , |
---|---|
Format | Patent |
Language | Chinese English |
Published |
26.09.2023
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | The invention discloses a lithology identification method based on a characteristic contribution degree and PSO-Catboost, and the method is characterized in that the method comprises the steps: collecting well logging and logging data of a drilled well; defining different digital tags for different lithologies, dividing sample data into a training set and a test set, and setting operation iteration times and particle quantity parameters of a PSO algorithm; optimizing a random forest algorithm by using a PSO algorithm; and inputting the optimized features into a Catboost model, and automatically optimizing hyper-parameters of the Catboost model through a PSO algorithm to obtain a model with an optimal lithology recognition effect. According to the method, the catboost model is applied to the lithology identification field, and compared with a traditional integrated model based on a decision-making tree, a sorting lifting strategy is provided to solve the problems of gradient deviation and prediction offset exi |
---|---|
Bibliography: | Application Number: CN202310541962 |