Muhammad Ali

About Muhammad Ali

Muhammad Ali, With an exceptional h-index of 12 and a recent h-index of 12 (since 2020), a distinguished researcher at China University of Geosciences Wuhan, specializes in the field of Well Logging, Petrophysics, Rock Physics, Seismic Inversion, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Data-driven lithofacies prediction in complex tight sandstone reservoirs: a supervised workflow integrating clustering and classification models

Reservoir rock typing assessment in a coal-tight sand based heterogeneous geological formation through advanced AI methods

Improved prediction of thin reservoirs in complex structural regions using post-stack seismic waveform inversion: a case study in the Junggar Basin

Knowledge-based machine learning for mineral classification in a complex tectonic regime of Yingxiu-Beichuan fault zone, Sichuan basin

Classification of reservoir quality using unsupervised machine learning and cluster analysis: Example from Kadanwari gas field, SE Pakistan

Reservoir characterization through comprehensive modeling of elastic logs prediction in heterogeneous rocks using unsupervised clustering and class-based ensemble machine learning

Quantitative characterization of shallow marine sediments in tight gas fields of middle indus basin: a rational approach of multiple rock physics diagnostic models

Machine learning-a novel approach to predict the porosity curve using geophysical logs data: An example from the Lower Goru sand reservoir in the Southern Indus Basin, Pakistan

Muhammad Ali Information

University

Position

___

Citations(all)

564

Citations(since 2020)

564

Cited By

28

hIndex(all)

12

hIndex(since 2020)

12

i10Index(all)

13

i10Index(since 2020)

13

Email

University Profile Page

China University of Geosciences Wuhan

Google Scholar

View Google Scholar Profile

Muhammad Ali Skills & Research Interests

Well Logging

Petrophysics

Rock Physics

Seismic Inversion

Machine Learning

Top articles of Muhammad Ali

Title

Journal

Author(s)

Publication Date

Data-driven lithofacies prediction in complex tight sandstone reservoirs: a supervised workflow integrating clustering and classification models

Geomechanics and Geophysics for Geo-Energy and Geo-Resources

Muhammad Ali

Peimin Zhu

Ren Jiang

Ma Huolin

Umar Ashraf

...

2024/12

Reservoir rock typing assessment in a coal-tight sand based heterogeneous geological formation through advanced AI methods

Scientific Reports

Umar Ashraf

Wanzhong Shi

Hucai Zhang

Aqsa Anees

Ren Jiang

...

2024/3/7

Improved prediction of thin reservoirs in complex structural regions using post-stack seismic waveform inversion: a case study in the Junggar Basin

Canadian Geotechnical Journal

Muhammad Ali

Peimin Zhu

Ren Jiang

Ma Huolin

Umar Ashraf

2024/3/6

Knowledge-based machine learning for mineral classification in a complex tectonic regime of Yingxiu-Beichuan fault zone, Sichuan basin

Geoenergy Science and Engineering

Jar Ullah

Huan Li

Umar Ashraf

Pan Heping

Muhammad Ali

...

2023/10/1

Classification of reservoir quality using unsupervised machine learning and cluster analysis: Example from Kadanwari gas field, SE Pakistan

Geosystems and Geoenvironment

Nafees Ali

Jian Chen

Xiaodong Fu

Wakeel Hussain

Muhammad Ali

...

2023/2/1

Reservoir characterization through comprehensive modeling of elastic logs prediction in heterogeneous rocks using unsupervised clustering and class-based ensemble machine learning

Applied Soft Computing

Muhammad Ali

Peimin Zhu

Ren Jiang

Ma Huolin

Muhsan Ehsan

...

2023/11/1

Quantitative characterization of shallow marine sediments in tight gas fields of middle indus basin: a rational approach of multiple rock physics diagnostic models

Processes

Muhammad Ali

Umar Ashraf

Peimin Zhu

Huolin Ma

Ren Jiang

...

2023/1/18

Machine learning-a novel approach to predict the porosity curve using geophysical logs data: An example from the Lower Goru sand reservoir in the Southern Indus Basin, Pakistan

Journal of Applied Geophysics

Wakeel Hussain

Miao Luo

Muhammad Ali

Syed Mumtaz Hussain

Sajid Ali

...

2023/7/1

The assessment of reservoir potential of Permian to Eocene reservoirs of Minwal-Joyamair fields, upper Indus basin, Pakistan

Heliyon

Muhammad Ali Umair Latif

Muhsan Ehsan

Muhammad Ali

Abid Ali

Armel Zacharie Ekoa Bessa

...

2023/6/1

A novel machine learning approach for detecting outliers, rebuilding well logs, and enhancing reservoir characterization

Natural Resources Research

Muhammad Ali

Peimin Zhu

Ma Huolin

Heping Pan

Khizar Abbas

...

2023/6

Контролируемый техпроцесс для прогнозирования литофаций в сложных неоднородных плотных песчаных коллекторах: Основанный на данных подход с использованием моделей кластеризации …

Вестник Пермского университета. Геология

Muhammad Ali

2023/12/29

Prospect evaluation of the cretaceous Yageliemu clastic reservoir based on geophysical log data: a case study from the Yakela gas condensate field, Tarim Basin, China

Energies

Wakeel Hussain

Muhsan Ehsan

Lin Pan

Xiao Wang

Muhammad Ali

...

2023/3/14

Prediction of Cretaceous reservoir zone through petrophysical modeling: Insights from Kadanwari gas field, Middle Indus Basin

Geosystems and Geoenvironment

Nafees Ali

Jian Chen

Xiaodong Fu

Wakeel Hussain

Muhammad Ali

...

2022/8/1

Measurements and determinants of extreme multidimensional energy poverty using machine learning

Energy

Khizar Abbas

Khalid Manzoor Butt

Deyi Xu

Muhammad Ali

Khan Baz

...

2022/7/15

Evaluation of unconventional hydrocarbon reserves using petrophysical analysis to characterize the Yageliemu Formation in the Yakela gas condensate field, Tarim Basin, China

Arabian Journal of Geosciences

Wakeel Hussain

Lin Pan

Xiao Wang

Muhammad Saqlain

Muhammad Ali

...

2022/11

Application of machine learning for lithofacies prediction and cluster analysis approach to identify rock type

Energies

Mazahir Hussain

Shuang Liu

Umar Ashraf

Muhammad Ali

Wakeel Hussain

...

2022/6/20

Hydrocarbon potential assessment of carbonate-bearing sediments in a meyal oil field, Pakistan: Insights from logging data using machine learning and quanti elan modeling

ACS omega

Jawad Ali

Umar Ashraf

Aqsa Anees

Sanxi Peng

Muhammad Ubaid Umar

...

2022/10/17

Evaluation of the geothermal parameters to decipher the thermal structure of the upper crust of the Longmenshan fault zone derived from borehole data

Geothermics

Jar Ullah

Miao Luo

Umar Ashraf

Heping Pan

Aqsa Anees

...

2022/1/1

Estimation of porosity and facies distribution through seismic inversion in an unconventional tight sandstone reservoir of Hangjinqi area, Ordos basin

Frontiers in Earth Science

Umar Ashraf

AQSA ANEES

Wanzhong Shi

Ren Wang

Muhammad Ali

...

2022

A core logging, machine learning and geostatistical modeling interactive approach for subsurface imaging of lenticular geobodies in a clastic depositional system, SE Pakistan

Natural Resources Research

Umar Ashraf

Hucai Zhang

Aqsa Anees

Hassan Nasir Mangi

Muhammad Ali

...

2021/3/16

See List of Professors in Muhammad Ali University(China University of Geosciences Wuhan)