A systematic review of data science and machine learning applications to the oil and gas industry

Z Tariq, MS Aljawad, A Hasan, M Murtaza… - Journal of Petroleum …, 2021 - Springer
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 …

Addressing diverse petroleum industry problems using machine learning techniques: literary methodology─ spotlight on predicting well integrity failures

AM Salem, MS Yakoot, O Mahmoud - ACS omega, 2022 - ACS Publications
Artificial intelligence (AI) and machine learning (ML) are transforming industries, where low-
cost, big data can utilize computing power to optimize system performance. Oil and gas …

Experimental evaluation and optimization of improved conductivity of gelling acid etched fractures in deep, low-permeability reservoirs

X Kong, B Liu, X Wan, S Li, Z Liu, M Chen, J Shen - Fuel, 2023 - Elsevier
Stimulation technology is the key to efficient development of deep low-permeability
carbonate reservoirs. For such reservoirs, where the porosity and permeability are low, or …

Comparative study of fracture conductivity in various carbonate rocks treated with GLDA chelating agent and HCl acid

Z Tariq, A Hassan, R Al-Abdrabalnabi… - Energy & …, 2021 - ACS Publications
Acid fracturing is applied to increase the productivity of carbonate formations. The acid
creates rough fracture surfaces and channels that keep the fractures open after closure. This …

Fracture identification in reservoirs using well log data by window sliding recurrent neural network

S Dong, L Wang, L Zeng, X Du, C Ji, J Hao… - Geoenergy Science and …, 2023 - Elsevier
Detecting fractures using well logs can be difficult due to the complex response of
conventional logs. To address this issue, a novel method called Fracture Identification by …

An advanced long short-term memory (LSTM) neural network method for predicting rate of penetration (ROP)

H Ji, Y Lou, S Cheng, Z Xie, L Zhu - ACS omega, 2022 - ACS Publications
Rate of penetration (ROP) is an essential factor in drilling optimization and reducing the
drilling cycle. Most of the traditional ROP prediction methods are based on building physical …

An artificial intelligence-based model for performance prediction of acid fracturing in naturally fractured reservoirs

A Hassan, MS Aljawad, M Mahmoud - ACS omega, 2021 - ACS Publications
Acid fracturing is one of the most effective techniques for improving the productivity of
naturally fractured carbonate reservoirs. Natural fractures (NFs) significantly affect the …

Data-driven models for forecasting failure modes in oil and gas pipes

N Elshaboury, A Al-Sakkaf, G Alfalah, EM Abdelkader - Processes, 2022 - mdpi.com
Oil and gas pipelines are lifelines for a country's economic survival. As a result, they must be
closely monitored to maximize their performance and avoid product losses in the …

Experimental investigations of acid fracturing in layered carbonate rocks utilizing chelating agents

R Al-Abdrabalnabi, MS Aljawad, M Al Ramadan… - Energy & …, 2023 - ACS Publications
One of the methods to improve carbonate formation productivity is acid fracturing. The acid
injection creates dissolution along the fracture, which improves fracture conductivity. This …

Identifying balls feature in a large-scale laser point cloud of a coal mining environment by a multiscale dynamic graph convolution neural network

Z Xing, S Zhao, W Guo, X Guo, Y Wang, Y Bai… - ACS …, 2022 - ACS Publications
In the process of coal mining, a certain amount of gas will be produced. Environmental
perception is very important to realize intelligent and unmanned coal mine production and …