Article

Machine-Learning-Driven Formation Damage Classification Based on SEM Images and Petrophysical Data

2026-05-12

Abstract excerpt

<title>Abstract</title> <p>Oil and gas recovery is significantly reduced by formation damage caused by improper drilling, completion, and production operations. Conventional evaluation methods rely on core sample analysis, well-logging assessments, and interpretation of production data, which require greater human effort and are susceptible to human error. This study presents an innovative automated category fram...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: c2e480ba-5cb8-5024-9ac0-94bfc9852830
DOI: 10.21203/rs.3.rs-9430254/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Machine-Learning-Driven Formation Damage Classification Based on SEM Images and Petrophysical DataDOI 10.21203/rs.3.rs-9430254/v1Read

Improvement of Generalization Performance of Diagnostic System for Drill Bit Abnormality in Rotary Percussion Drilling with Grad-CAMSemantic proximity Read

Landslide Risk Assessment of Geological Hazards in Bengbu City Based on Hyperband-CatBoost and SHAP Interpretability FrameworkSemantic proximity Read

A Comparative Study of TabNet and Classical Machine Learning Models for Landslide PredictionSemantic proximity Read

Ensemble Machine Learning and GIS-Based Landslide Susceptibility Modeling: Insights from Fuyuan CountySemantic proximity Read

Landslide susceptibility assessment in the Central Yunnan Plateau by assembling optimized statistical and machine learning modelsSemantic proximity Read

Navigating the Complexity Trap: Deep Learning Optimization for Mapping Historic Surface Mines in Appalachian TerrainSemantic proximity Read

Data-Driven Prediction of LNG Tank Thermal Stratification and Boil-Off Gas Generation Using Ensemble Machine Learning with Uncertainty Quantification: An Experimental and Mechanistic StudySemantic proximity Read

Optimal Surface Defect Detector Design Based on Deep Learning for 3D GeometrySemantic proximity Read

Research on Early Interpretation Techniques for Potential Landslide Terrain Based on Deep Generative Adversarial Reinforcement LearningSemantic proximity Read

A Study on an Explainable Causal-Enhanced LLM Agent for Predicting the Forming Quality of Automotive Component MaterialsSemantic proximity Read

Next-Gen Forest Fire Management: Integrating Deep Learning with GIS and Earth Observation for Early Warning SystemsSemantic proximity Read

A Two-Stage Deep Learning Framework for Automated Corrosion Detection and Severity Estimation in High-Resolution SEM ImagesSemantic proximity Read