Porosity and Density Determination from Well Log Data: Machine Learning and Simulation Approaches

Authors

  • A.S.M. Mannafi Department of Petroleum and Mining Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka-1216, Bangladesh
  • Md Tauhidur Rahman Department of Petroleum and Mining Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka-1216, Bangladesh
  • K. M. Haidarul Alam Department of Petroleum and Mining Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka-1216, Bangladesh
  • Md Niamul Quader Department of Electrical Engineering and Computer Science, South Dakota School of Mining & Technology; Rapid City, SD 57701, United States of America
  • Khairul Habib Department of Mechanical Engineering, Universiti Teknologi PETRONAS, 32610 Seri Iskandar, Perak, Malaysia
  • Tamanna Zafrin Orin Department of Petroleum and Mining Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka-1216, Bangladesh

DOI:

https://doi.org/10.37934/araset.51.1.116128

Keywords:

Artificial intelligence, Well log, Reservoir characterization, Machine learning, Simulation, Petrophysical properties

Abstract

Reservoir characterization is vital for petroleum exploration, largely relies on well log data analysis. Machine Learning (ML) empowers analysis of complex datasets quickly and more easily in a cost-effective way. ML allows deeper insights into reservoir properties such as porosity, permeability, water saturation, resistivity and many more. This study focuses on Reservoir characterization using ML approach (Python). Investigating reservoir behaviours involves intricate inverse problems; ML tackles this challenge. Integration of ML improves understanding, optimizing petroleum industry practices. This study used data from well logs to evaluate porosity, density, and gamma ray log. Through Petrel-based simulations, the findings were verified and validated.

Downloads

Download data is not yet available.

Author Biographies

A.S.M. Mannafi, Department of Petroleum and Mining Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka-1216, Bangladesh

mannafiasm@gmail.com

Md Tauhidur Rahman, Department of Petroleum and Mining Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka-1216, Bangladesh

tauhidur.pme@gmail.com

K. M. Haidarul Alam, Department of Petroleum and Mining Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka-1216, Bangladesh

haidar.alam7188@gmail.com

Md Niamul Quader, Department of Electrical Engineering and Computer Science, South Dakota School of Mining & Technology; Rapid City, SD 57701, United States of America

mdniamulquader@gmail.com

Khairul Habib, Department of Mechanical Engineering, Universiti Teknologi PETRONAS, 32610 Seri Iskandar, Perak, Malaysia

khairul.habib@utp.edu.my

Tamanna Zafrin Orin, Department of Petroleum and Mining Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka-1216, Bangladesh

tamannaorin2017@gmail.com

Published

2024-09-04

Issue

Section

Articles

Most read articles by the same author(s)