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 …

Diagnosis of sucker rod pump based on generating dynamometer cards

B Zheng, X Gao, X Li - Journal of Process Control, 2019 - Elsevier
The dynamometer cards (DC) are the data shown as closed curves collected from Sucker
Rod Pumps, which are essential evidence to monitor the working states in modern oil are …

The role of big data analytics in exploration and production: A review of benefits and applications

CI Noshi, AI Assem, JJ Schubert - SPE International Heavy Oil …, 2018 - onepetro.org
Due to the decrease in commodity prices in a constantly dynamic environment, there has
been a constant urge to maximize benefits and attain value from limited resources …

Application of deep learning methods to estimate multiphase flow rate in producing wells using surface measurements

AA Alakeely, RN Horne - Journal of Petroleum Science and Engineering, 2021 - Elsevier
In the past, the problem of predicting the multiphase flow rate in producing wells has been
tackled using the Gilbert correlation. The Gilbert correlation offers a quick solution and …

An AI-based workflow for estimating shale barrier configurations from SAGD production histories

J Zheng, JY Leung, RP Sawatzky… - Neural Computing and …, 2019 - Springer
An artificial intelligence (AI)-based workflow is deployed to develop and test procedures for
estimating shale barrier configurations from SAGD production profiles. The data employed in …

A proxy model for predicting SAGD production from reservoirs containing shale barriers

J Zheng, JY Leung… - Journal of Energy …, 2018 - asmedigitalcollection.asme.org
Artificial intelligence (AI) tools are used to explore the influence of shale barriers on steam-
assisted gravity drainage (SAGD) production. The data are derived from synthetic SAGD …

Unsupervised tumor detection in Dynamic PET/CT imaging of the prostate

E Rubinstein, M Salhov, M Nidam-Leshem, V White… - Medical image …, 2019 - Elsevier
Early detection and localization of prostate tumors pose a challenge to the medical
community. Several imaging techniques, including PET, have shown some success. But no …

Recognition of aquatic invasive species larvae using autoencoder-based feature averaging

S Chowdhury, G Hamerly - International Symposium on Visual Computing, 2022 - Springer
The spread of invasive aquatic species disrupts ecological balance, damages natural
resources, and adversely affects agricultural activity. There is a need for automated systems …

Machine learning application for wellbore damage removal in the wilmington field

RP Kellogg, W Chessum, R Kwong - SPE Western Regional Meeting, 2018 - onepetro.org
The use of acid is an important well maintenance tool in removing near wellbore damage to
restore a reservoir's natural permeability and represents one of the most economic options …

Artificial intelligence applied in sucker rod pumping wells: intelligent dynamometer card generation, diagnosis, and failure detection using deep neural networks

Y Peng - SPE Annual Technical Conference and Exhibition?, 2019 - onepetro.org
For most of the mature fields, the oil well operation and maintenance expenditures continue
to put financial pressure on the operators in the low oil price period. Digital oilfields and …