Prediction of Sandstone Porosity based on Machine Learning
Year: 2024
Type: article
Abstract: Porosity is a critical property of sandstone, influencing its ability to store and transmit fluids. Accurate prediction of porosity is essential for various applications, including hydrocarbon exploration, groundwater management, and civil engineering. Traditional methods for porosity estimation often involve labor-intensive and time-consuming laboratory tests. However, with the advent of machine learning (ML) techniques, there is potential for more efficient and accurate prediction of sandstone porosity. This paper explores the application of machine learning models to predict sandstone porosity using various geological and petrophysical features.
DOI: 10.54097/tgwhkf56
Author: Yinliang Cheng
Institution: Henan Polytechnic University
Language: English
Subfield: Mechanics of Materials
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4401795715