Coupled numerical simulation of multi-layer reservoir developed by lean-stratified water injection

Gao, Dapeng; Ye, Jigen; Liu, Yuewu; Pan, Songqi; Hu, Yunpeng; He, Yumei

doi:10.1007/s13202-016-0238-6

Cited by 7 publications

(1 citation statement)

References 6 publications

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“…The technique of DCA can roughly characterize the variation of reservoir production, but can’t consider the influence of development measures on oil and gas production. Numerical reservoir simulation is to simulate the underground oil and water flow by establishing and solving the reservoir geological and numerical models, and giving the distribution of oil and water at a certain time to predict the reservoir dynamics (Gao et al, 2016; Yang et al, 2021; Zhang and Awotunde, 2016). If the accuracy of numerical simulation to predict production is high, it often needs to invest considerable time and effort.…”

Section: Introductionmentioning

confidence: 99%

Forecasting of oil production driven by reservoir spatial–temporal data based on normalized mutual information and Seq2Seq-LSTM

Cui,

Qian,

et al. 2023

Energy Exploration & Exploitation

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Traditional machine learning methods are difficult to accurately forecast oil production when development measures change. A method of oil reservoir production prediction based on normalized mutual information and a long short-term memory-based sequence-to-sequence model (Seq2Seq-LSTM) was proposed to forecast reservoir production considering the influence of liquid production and well spacing density. First, the marine sandstone reservoirs in the Y basin were taken as the research object to establish the sample database. Then, the feature selection was carried out according to the normalized mutual information, and liquid production, production time, equivalent well spacing density, fluidity and original formation pressure were determined as input features. Finally, a Seq2Seq-LSTM model was established to forecast reservoir production by learning the interaction from multiple samples and multiple sequences, and mining the relationship between oil production and features. The research showed that the model has a high accuracy of production prediction and can forecast the change of production when the liquid production and well spacing density change, which can provide scientific recommendations to help the oilfield develop and adjust efficiently.

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Section: Introductionmentioning

confidence: 99%

Forecasting of oil production driven by reservoir spatial–temporal data based on normalized mutual information and Seq2Seq-LSTM

Cui,

Qian,

et al. 2023

Energy Exploration & Exploitation

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Terahertz-dependent evaluation of water content in high-water-cut crude oil using additive-manufactured samplers

Limei

Zhan

Miao

et al. 2017

Sci. China Phys. Mech. Astron.

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Integrated wellbore-reservoir modeling based on 3D Navier–Stokes equations with a coupled CFD solver

Ahammad,

Rahman,

Butt

et al. 2024

J Petrol Explor Prod Technol

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The occurrence of fluid flow near a wellhead is the major concern of the petroleum industry, as pressure drop, loss of formation, and other variables of interest are mostly affected in this region. The fluid flows from the hydrocarbon reservoir to the wellbore can be characterized as laminar to turbulent; thus, it is important to model this phenomenon with the integrated wellbore-reservoir model. Using 3D Navier–Stokes equations, an integrated wellbore-reservoir model is created in this study, and it incorporates the formation damage zone. For the porous-porous and porous-fluid interfaces, the General Grid Interface (GGI) approach is applied in conjunction with the conservative mass flux interface model. Model equations are solved using a velocity-pressure coupling solver that is pressure-based. For reliable and quick results, the system of equations is solved using an algebraic multigrid approach. The pressure diffusivity equation’s analytical solution under steady-state flow circumstances is used to validate the model. The integrated wellbore-reservoir model is applied to different reservoir scenarios, for example, different production rates, formation zones, and reservoir formation conditions. The results indicate that the present Computational Fluid Dynamics (CFD) model can be extended to simulate the real field scale model. integrated wellbore-reservoir modeling based on 3D Navier–Stokes equations with efficient computational techniques can lead the field of petroleum industries to advance current knowledge.

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Coupled numerical simulation of multi-layer reservoir developed by lean-stratified water injection

Cited by 7 publications

References 6 publications

Forecasting of oil production driven by reservoir spatial–temporal data based on normalized mutual information and Seq2Seq-LSTM

Forecasting of oil production driven by reservoir spatial–temporal data based on normalized mutual information and Seq2Seq-LSTM

Terahertz-dependent evaluation of water content in high-water-cut crude oil using additive-manufactured samplers

Integrated wellbore-reservoir modeling based on 3D Navier–Stokes equations with a coupled CFD solver

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