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 …

Prediction of well production event using machine learning algorithms

Y Alatrach, C Mata, P Shoeibi Omrani… - Abu Dhabi …, 2020 - onepetro.org
In this paper, a new approach was identified and tested to detect abnormal events in
producing wells when a labeled dataset is unavailable or the number of instances are below …

[图书][B] Reinforcement learning for well location optimization

K Dawar - 2021 - search.proquest.com
The strategic placement of exploratory wells during the process of hydrocarbon production is
critical for both the determination of the reservoir properties and the eventual profitability of …

An automated diagnostic analytics workflow for the detection of production events-application to mature gas fields

J Poort, P Shoeibi Omrani, AL Vecchia… - Abu Dhabi …, 2020 - onepetro.org
Detection of production and well events is crucial for planning of production and operational
strategies. Event detection is especially challenging in mature fields in which various off …

Application of machine learning algorithms for managing well integrity in gas lift wells

AMS Ragab, MS Yakoot, O Mahmoud - SPE Asia Pacific Oil and Gas …, 2021 - onepetro.org
Well integrity (WI) impairments in oil and gas (O&G) wells are one of the most formidable
challenges in the petroleum industry. Managing WI for different groups of well services …

Chemical Sand Consolidation Design in Jasmine Field: Lessons Learned and Critical Success Factors from an Operator Point of View

S Dachanuwattana, P Prasongtham… - Abu Dhabi …, 2020 - onepetro.org
The Jasmine oil field, in the Gulf of Thailand, has several pools of unconsolidated sandstone
reservoirs. Multi-zone completion is usually deployed in these reservoirs, however, sand …

Reservoir engineering

YN Pandey, A Rastogi, S Kainkaryam… - Machine Learning in the …, 2020 - Springer
The oil and gas industry has been solving problems related to automation and optimization
from the very beginning. Modern technology and data-driven algorithms have provided the …

Tidlig kick deteksjon og utvikling av en simulator for generering av data for maskinlæringsformål

KG Haug - 2021 - uis.brage.unit.no
En av de mest skadelige hendelsene med hensyn til sikkerhet, økonomiske tap og miljø
skader som kan oppstå under boring er en utblåsing som skyldes et kick som oppnås av en …

Application of Deep Learning for Understanding Dynamic Well Connectivity

S Kareepadath Sajeev - 2020 - oaktrust.library.tamu.edu
Artificial intelligence and machine learning have transformed many industries. However, the
oil and gas industry is lagging in AI adaption. Currently, with the low oil prices and a …

[PDF][PDF] Artificial lift selection methods in conventional and unconventional wells: a summary and review from old techniques to machine learning applications.

MAA Mahdi, M Amish… - … journal of innovative …, 2024 - rgu-repository.worktribe.com
Artificial lift (AL) selection is an important process in enhancing oil and gas production from
reservoirs. This article explores the old and current states of AL selection in conventional …