A systematic review of big data analytics for oil and gas industry 4.0

T Nguyen, RG Gosine, P Warrian - IEEE access, 2020 - ieeexplore.ieee.org
Big data (BD) analytics is one of the critical components in the digitalization of the oil and
gas (O&G) industry. Its focus is managing and processing a high volume of data to improve …

A Comprehensive review of data-driven approaches for forecasting production from unconventional reservoirs: best practices and future directions

H Rahmanifard, I Gates - Artificial Intelligence Review, 2024 - Springer
Prediction of well production from unconventional reservoirs is a complex problem given an
incomplete understanding of physics despite large amounts of data. Recently, Data …

A review on application of data-driven models in hydrocarbon production forecast

C Cao, P Jia, L Cheng, Q Jin, S Qi - Journal of Petroleum Science and …, 2022 - Elsevier
The accurate estimation of production is the bottleneck technique that constraints the
efficient development of oil and gas fields. However, such multivariate and asymmetric …

Modelling oil and gas flow rate through chokes: A critical review of extant models

OE Agwu, EE Okoro, SE Sanni - Journal of Petroleum Science and …, 2022 - Elsevier
Oil and gas metering is primarily used as the basis for evaluating the economic viability of oil
wells. Owing to the economic implications of oil and gas metering, the subject of oil and gas …

[HTML][HTML] Multi-horizon well performance forecasting with temporal fusion transformers

E Maldonado-Cruz, MJ Pyrcz - Results in Engineering, 2024 - Elsevier
Forecasting fluid flow in subsurface resources such as groundwater, geothermal, and oil and
gas is essential to maximize project economics and maximize resource recovery. We …

Workflow to predict wellhead choke performance during multiphase flow using machine learning

SA Alarifi - Journal of Petroleum Science and Engineering, 2022 - Elsevier
Multiphase flow metering in oil and gas production wells is essential for monitoring the
production performance from oil and gas reservoirs. Accurate measurements of multiphase …

Using Machine Learning Method to Optimize Well Stimulation Design in Heterogeneous Naturally Fractured Tight Reservoirs

H Liu, L Cui, Z Liu, C Zhou, M Yao, H Ma… - SPE Canadian Energy …, 2022 - onepetro.org
The reservoirs in Kuqa foreland area of Tarim Basin in China are ultra-deep HTHP (High
Temperature and High Pressure) naturally fractured sandstone reservoirs. Due to low …

[HTML][HTML] Cloud-based virtual flow metering system powered by a hybrid physics-data approach for water production monitoring in an offshore gas field

RH Nemoto, R Ibarra, G Staff, A Akhiiartdinov… - Digital Chemical …, 2023 - Elsevier
This work presents a cloud-based Virtual Flow Metering (VFM) system powered by a hybrid
physics-data approach to estimate the water production per well in a gas field. This hybrid …

Gas Production Prediction Model of Volcanic Reservoir Based on Data-Driven Method.

H Zhang, J Pu, L Zhang, H Deng, J Yu… - Energies …, 2024 - search.ebscohost.com
Based on on-site construction experience, considering the time-varying characteristics of
gas well quantity, production time, effective reservoir thickness, controlled reserves, reserve …

A Computational Model for Wells' Performance Analysis

O Edet Ita, D Appah - SPE Nigeria Annual International Conference …, 2021 - onepetro.org
The ability to identify underperforming wells and recover the remaining oil in place is a
cornerstone for effective reservoir management and field development strategies. As …