Modeling interaction between CO2, brine and chalk reservoir rock including temperature effect on petrophysical properties

Mahmud, Hisham Ben; Mahmud, Walid Mohamed; Al-Rubaye, Ali

doi:10.1016/j.engeos.2021.01.002

Cited by 6 publications

(6 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, Saldana et al 107 developed a reactive transport model based on Passarella's flow experiment to evaluate the feasibility of long-term CO 2 storage under hightemperature conditions. Mahmud et al 108 simulated the impact of CO 2 −brine systems on cores at 65−95 °C, and the results showed that the temperature had little effect on porosity but significantly increased permeability as a result of the enhancement of CO 2 −rock chemical reactions at high temperatures. Yu et al 109 reported that CO 2 injection did not cause significant CO 2 −rock−water reactions in the short term and that core pores did not change significantly, but the numerical simulation process resulted in the precipitation of kaolinite and quartz.…”

Section: Storage Sitesmentioning

confidence: 99%

Recent Advances in Geological Storage: Trapping Mechanisms, Storage Sites, Projects, and Application of Machine Learning

Feng

et al. 2023

Energy Fuels

View full text Add to dashboard Cite

A significant amount of carbon dioxide (CO2) is being released into the atmosphere as a result of the acceleration of industrialization and increased energy consumption, which are causing a rise in world temperatures. Despite the fact that nations all over the world have actively participated in CO2 storage projects, there is still not enough to moderate global temperatures. Therefore, there is an urgent need for the development of CO2 sequestration technologies. The main geological storage trapping mechanisms are discussed in this work along with an analysis of the major influencing variables. Additionally, the benefits and drawbacks of significant storage locations and current research hotspots are explored. Storage project development across the globe is outlined. The use of machine learning for CO2 sequestration is reviewed toward the end. This extensive review reveals that the main variables affecting CO2 capture capacity are hydrodynamic and geochemical. The sequestration capability of various storage sites is significantly influenced by the reservoir characteristics and implementation methodologies. The successful implementation of the storage project is determined by local policies and public support. The development of machine learning technologies makes storage projects safer and more dependable.

show abstract

Section: Storage Sitesmentioning

confidence: 99%

Recent Advances in Geological Storage: Trapping Mechanisms, Storage Sites, Projects, and Application of Machine Learning

Feng

et al. 2023

Energy Fuels

View full text Add to dashboard Cite

show abstract

“…Zhang et al [7] Carbon capture, utilization, and storage are vital for combating the adverse effects of climate change globally. Mahmud et al [16] Low-pH carbonated-brine acidity at elevated temperatures leads to porosity and permeability enhancement. Liang et al [17] Tertiary recovery by using nanofluid alters the rock wettability, and interfacial tension enhances the oil recovery.…”

Section: Rishabh Godiwalmentioning

confidence: 99%

“…These nanoparticles can be metallic (such as iron oxide or titanium oxide), non-metallic (such as carbon nanotubes or graphene), or a combination of both. When used in EOR, nanofluids offer several potential advantages over traditional EOR methods [5,[10][11][12][13][14][15][16][17][18]. Some key benefits of using nanofluids include:…”

Section: Nanofluids In Eormentioning

confidence: 99%

See 1 more Smart Citation

Modeling of Enhanced Oil Recovery Using Nanofluid

Godiwal,

Mandal

2023

Chem Eng & Technol

View full text Add to dashboard Cite

Nanofluid flow in porous media was modeled for enhanced oil recovery. The effects of parameters such as the matrix porosity, nanoparticles, and diffusion coefficients on the oil recovery factor were reported. The velocity, temperature, and oil saturation contours were examined. The study showed that the oil recovery and heat transfer were enhanced by the use of a nanofluid. A 30 % and 10 % increase in the oil recovery factor were found using the Al2O3‐water nanofluid as compared to water and the polystyrene‐water nanofluid, respectively. The temperature in the porous matrix was significantly reduced by the Al2O3‐water nanofluid as compared to the polystyrene‐water nanofluid and water. In the future, this model could be used to screen the performance of other chemical agents and eventually lead to a more efficient and sustainable oil extraction process.

show abstract

“…For example, simulation has shown that the permeability of chalk increases substantially due to chemical reactions [20].…”

Section: Introductionmentioning

confidence: 99%

Influence of Various Rock Types on the Recovery of Heavy Hydrocarbons by Supercritical Carbon Dioxide

Spirov,

Rudyk

2024

Preprint

View full text Add to dashboard Cite

This study explores pressure, miscibility, and pore medium effects on heavy hydrocarbon recovery up to 65 MPa from four rock types: sand, tight sandstone, cavernous limestone, and oil sand. Results reveal MMP at 50 MPa, with peak recovery at 93% (56 MPa). Interestingly, recovery trends counter traditional expectations, notably decreasing in tight sandstone (42-56 MPa) and oil sand (50-65 MPa). Varied recoveries in cavernous limestone (25-56 MPa) highlight porosity and vug influence. Higher pressures hinder recovery due to SC-CO2's density and viscosity, favoring the immiscible process for efficient heavy hydrocarbon extraction.

show abstract

Modeling interaction between CO2, brine and chalk reservoir rock including temperature effect on petrophysical properties

Cited by 6 publications

References 35 publications

Recent Advances in Geological Storage: Trapping Mechanisms, Storage Sites, Projects, and Application of Machine Learning

Recent Advances in Geological Storage: Trapping Mechanisms, Storage Sites, Projects, and Application of Machine Learning

Modeling of Enhanced Oil Recovery Using Nanofluid

Influence of Various Rock Types on the Recovery of Heavy Hydrocarbons by Supercritical Carbon Dioxide

Contact Info

Product

Resources

About