A survey on industry 4.0 for the oil and gas industry: upstream sector
The market volatility in the oil and gas (O&G) sector, the dwindling demand for oil due to the
impact of COVID-19, and the push for alternative greener energy are driving the need for …
impact of COVID-19, and the push for alternative greener energy are driving the need for …
Hydrocarbon production dynamics forecasting using machine learning: A state-of-the-art review
Accurate prediction of hydrocarbon production is crucial for the oil and gas industry.
However, the strong heterogeneity of underground formation, the inconsistency in oil–gas …
However, the strong heterogeneity of underground formation, the inconsistency in oil–gas …
[HTML][HTML] Artificial intelligence in oil and gas upstream: Trends, challenges, and scenarios for the future
We analyze how artificial intelligence changes a significant part of the energy sector, the oil
and gas industry. We focus on the upstream segment as the most capital-intensive part of oil …
and gas industry. We focus on the upstream segment as the most capital-intensive part of oil …
A predictive model for steady-state multiphase pipe flow: Machine learning on lab data
Engineering simulators used for steady-state multiphase flows in oil and gas wells and
pipelines are commonly utilized to predict pressure drop and phase velocities. Such …
pipelines are commonly utilized to predict pressure drop and phase velocities. Such …
Addressing diverse petroleum industry problems using machine learning techniques: literary methodology─ spotlight on predicting well integrity failures
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 …
cost, big data can utilize computing power to optimize system performance. Oil and gas …
Data-driven model for hydraulic fracturing design optimization: Focus on building digital database and production forecast
AD Morozov, DO Popkov, VM Duplyakov… - Journal of Petroleum …, 2020 - Elsevier
Growing amount of hydraulic fracturing (HF) jobs in the recent two decades resulted in a
significant amount of measured data available for development of predictive models via …
significant amount of measured data available for development of predictive models via …
Machine learning to rate and predict the efficiency of waterflooding for oil production
Waterflooding is a widely used secondary oil recovery technique. The oil and gas industry
uses a complex reservoir numerical simulation and reservoir engineering analysis to …
uses a complex reservoir numerical simulation and reservoir engineering analysis to …
Application of the artificial intelligence GANNATS model in forecasting crude oil demand for Saudi Arabia and China
SM Al-Fattah, S Aramco - Journal of Petroleum Science and Engineering, 2021 - Elsevier
This paper develops a rigorous and advanced data-driven model to describe, analyze, and
forecast the global crude oil demand. The study deploys a hybrid approach of artificial …
forecast the global crude oil demand. The study deploys a hybrid approach of artificial …
Algae development in rivers with artificially constructed weirs: Dominant influence of discharge over temperature
Algal blooms contribute to water quality degradation, unpleasant odors, taste issues, and the
presence of harmful substances in artificially constructed weirs. Mitigating these adverse …
presence of harmful substances in artificially constructed weirs. Mitigating these adverse …
AI-based estimation of hydraulic fracturing effect
We studied the applicability of a gradient-boosting machine-learning (ML) algorithm for
forecasting of oil and total liquid production after hydraulic fracturing (HF). A thorough raw …
forecasting of oil and total liquid production after hydraulic fracturing (HF). A thorough raw …