A systematic review of data science and machine learning applications to the oil and gas industry
This study offered a detailed review of data sciences and machine learning (ML) roles in
different petroleum engineering and geosciences segments such as petroleum exploration …
different petroleum engineering and geosciences segments such as petroleum exploration …
Machine learning approach to model rock strength: prediction and variable selection with aid of log data
Comprehensive knowledge and analysis of in situ rock strength and geo-mechanical
characteristics of rocks are crucial in hydrocarbon and mineral exploration stage to …
characteristics of rocks are crucial in hydrocarbon and mineral exploration stage to …
Predictive models and feature ranking in reservoir geomechanics: A critical review and research guidelines
MI Miah - Journal of Natural Gas Science and Engineering, 2020 - Elsevier
Comprehensive investigation and accurate models of geo-mechanical properties are crucial
to maintain wellbore stability and optimize the hydraulic fracturing process. This review …
to maintain wellbore stability and optimize the hydraulic fracturing process. This review …
Machine learning-based intelligent prediction of elastic modulus of rocks at thar coalfield
NM Shahani, X Zheng, X Guo, X Wei - Sustainability, 2022 - mdpi.com
Elastic modulus (E) is a key parameter in predicting the ability of a material to withstand
pressure and plays a critical role in the design of rock engineering projects. E has broad …
pressure and plays a critical role in the design of rock engineering projects. E has broad …
Investigating average infrared radiation temperature characteristics during shear and tensile cracks in sandstone under different water contents
Shear loading and water contents can accelerate rock deformation and fracturing during
loading and mining activities. The prediction of the crack patterns in rocks under shear …
loading and mining activities. The prediction of the crack patterns in rocks under shear …
An Experimental Study and Machine Learning Modeling of Shale Swelling in Extended Reach Wells When Exposed to Diverse Water-Based Drilling Fluids
Shale swelling poses considerable challenges for companies involved in extended-reach
well drilling, particularly when it comes to maintaining wellbore stability. Despite the …
well drilling, particularly when it comes to maintaining wellbore stability. Despite the …
Predicting angle of internal friction and cohesion of rocks based on machine learning algorithms
The safe and sustainable design of rock slopes, open-pit mines, tunnels, foundations, and
underground excavations requires appropriate and reliable estimation of rock strength and …
underground excavations requires appropriate and reliable estimation of rock strength and …
Digital rock physics combined with machine learning for rock mechanical properties characterization
B Saad, A Negara, S Syed Ali - Abu Dhabi International Petroleum …, 2018 - onepetro.org
Rock mechanical properties is essential for several geomechanical applications such as
wellbore stability analysis, hydraulic fracturing design, and sand production management …
wellbore stability analysis, hydraulic fracturing design, and sand production management …
Hybrid machine learning approach for accurate prediction of the drilling rock index
NM Shahani, X Zheng, X Wei, J Hongwei - Scientific reports, 2024 - nature.com
The drilling rate index (DRI) of rocks is important for optimizing drilling operations, as it
informs the choice of appropriate methods and equipment, ultimately improving the …
informs the choice of appropriate methods and equipment, ultimately improving the …
Oilfield chemical-formation interaction and the effects on petrophysical properties: a review
Oil and gas recovery may cause formation damage during drilling, completion, and
production phases. As a result of fundamental chemical, thermal, mechanical, and biological …
production phases. As a result of fundamental chemical, thermal, mechanical, and biological …