Predicting the oil production using the novel multivariate nonlinear model based on Arps decline model and kernel method

X Ma, Z Liu - Neural Computing and Applications, 2018 - Springer
Prediction of petroleum production plays a key role in the petroleum engineering, but an
accurate prediction is difficult to achieve due to the complex underground conditions. In this …

Predicting the oil field production using the novel discrete GM (1, N) model.

X Ma, Z Liu - Journal of Grey System, 2015 - search.ebscohost.com
Abstract The discrete GM (1, N) model has been presented in this paper, which is
abbreviated as DGM (1, N) model. The modelling procedures start with deriving the basic …

Research on the Application of Integrated Learning Models in Oilfield Production Forecasting

MC Ni, XK Xin, GM Yu, Y Liu, YG Gong - ACS omega, 2023 - ACS Publications
Forecasting oil production is crucially important in oilfield management. Currently,
multifeature-based modeling methods are widely used, but such modeling methods are not …

Stimulation of oil and gas wells in carbonate formation by using supercharged nanoparticles

V Sergeev, K Tanimoto, M Abe - Abu Dhabi International Petroleum …, 2020 - onepetro.org
An article presents results of comparative analysis for evaluation of effectiveness of classical
stimulation technique and innovative technique applied in the same mature carbonate oil …

A practical integrated forecast method for estimated ultimate recovery (EUR) and well production performance after water breakthrough during waterflooding in …

K Sun, H Liu, Y Wang, J Wang, Z Kang… - Journal of Petroleum …, 2021 - Elsevier
It is both an opportunity and a challenge to develop naturally fractured reservoirs (NFRs)
effectively and efficiently, especially with waterflooding development measures. In order to …

[PDF][PDF] Проактивный блочно-факторный анализ разработки месторождений

АН Ситников, АА Пустовских… - PROНЕФТЬ …, 2022 - proneft.elpub.ru
ПРОАКТИВНЫЙ БЛОЧНО-ФАКТОРНЫЙ АНАЛИЗ РАЗРАБОТКИ МЕСТОРОЖДЕНИЙ Page
1 60 РАЗРАБОТКА И ЭКСПЛУАТАЦИЯ НЕФТЯНЫХ МЕСТОРОЖДЕНИЙ Октябрь 2016 …

Predicting Heavy Oil Production by Hybrid Data‐Driven Intelligent Models

S Qin, J Liu, X Yang, Y Li, L Zhang… - … Problems in Engineering, 2021 - Wiley Online Library
It is difficult to determine the main control factors owing to the complex geological conditions
of heavy oil reservoirs, including high viscosity, a wide range of variation of crude oil, and …

Новый подход в планировании базовой добычи с автоматизацией методики поскважинного расчета

АА Рыбаковская, ИВ Фахретдинов… - PROНЕФТЬ …, 2021 - proneft.elpub.ru
Аннотация В статье рассмотрена автоматизация методики поскважинного расчета
прогнозных показателей базовой добычи нефти, жидкости и обводненности на основе …

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 …

Predicting emissions from oil and gas operations in the Uinta Basin, Utah

J Wilkey, K Kelly, IC Jaramillo, J Spinti… - Journal of the Air & …, 2016 - Taylor & Francis
In this study, emissions of ozone precursors from oil and gas operations in Utah's Uinta
Basin are predicted (with uncertainty estimates) from 2015–2019 using a Monte-Carlo …