Development of a linear predictive model for carbon dioxide sequestration in deep saline carbonate aquifers

Anbar, Sultan; Akın, Serhat

doi:10.1016/j.cageo.2011.03.010

Cited by 10 publications

(7 citation statements)

References 26 publications

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“…The corresponding maximum pore pressure developed in the cap rock interface was taken from the model for each injection pressure, and the corresponding third principle stress was calculated using Eq. [5]. The results are shown in Figure 4 and indicate that increasing the injection pressure from 15 to 23 MPa causes a continuous increment in pore pressure, such that at point A (21.5 MPa injection pressure), pore pressure exceeds the third principle stress.…”

Section: Determining the Pressures Associated With Fracture Formationmentioning

confidence: 94%

“…This was taken at the location of the injection well at the interface and s 3 at this point was calculated by Eq. [5].…”

Section: Determining the Pressures Associated With Fracture Formationmentioning

confidence: 99%

“…For such reasons, it is necessary to prevent the increasing release of carbon dioxide into the atmosphere [1]. Therefore, various CO 2 sequestration methods are being tested: (i) in depleted oil and gas reservoirs, (ii) in saline aquifers, (iii) in deep ocean beds, (iv) in deep un-mineable coal beds and (v) as mineral carbonates [2][3][4][5]. However, most of these methods have limitations.…”

Section: Introductionmentioning

confidence: 99%

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A study of safe CO₂storage capacity in saline aquifers: a numerical study

Ranjith

Perera

Khan

2012

Int. J. Energy Res.

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SUMMARY An effective way of reducing greenhouse gas content in the atmosphere is carbon dioxide (CO2) geo‐sequestration in saline aquifers. The main objective of this study is to develop a 3‐D numerical model to identify the optimum CO2 storage capacity in saline aquifers by studying the factors affecting it and the possibility of the injected CO2 back‐migrating into the atmosphere. A 1000m×1000m×184 m saline aquifer, lying 800 m below the ground surface, was therefore considered to develop a model using the COMET 3 reservoir simulator. The effects of injecting CO2 properties (injection pressure) and the aquifer's properties (depth, temperatures and salinity) on the CO2 storage capacity were examined first. According to the results of the model, CO2 storage capacity increases with increasing injection pressure and salinity and decreasing depth and temperature, and 100% variations in injection pressure, depth, temperature and salinity levels cause the CO2 storage capacity to be changed by 54%, 36%, 18% and 1.8%, respectively. The next stage of the study involved the determination of cap rock failure due to CO2 injection pressure and the identification of the factors influencing it. A detailed parametric study was conducted, with changes to the depth, temperature and salinity with respect to injection pressure, to detect the effects of these factors on the optimum CO2 injection pressure. According to the results, optimum CO2 injection pressure clearly depends on the aquifer depth and the effects of salinity and temperature are negligible. An increment of 0.8 to 1.4 km in aquifer depth causes the optimum injection pressure to be increased from 19.55 to 42 MPa, which is about 105 and 107 higher than the effects of temperature (20 to 110 °C increment) and salinity level (100,000 to 160,000 ppm increment), respectively. The model can be used effectively in field studies to safely enhance CO2 storage capacity in saline aquifers. Copyright © 2012 John Wiley & Sons, Ltd.

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Section: Determining the Pressures Associated With Fracture Formationmentioning

confidence: 94%

“…This was taken at the location of the injection well at the interface and s 3 at this point was calculated by Eq. [5].…”

Section: Determining the Pressures Associated With Fracture Formationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A study of safe CO₂storage capacity in saline aquifers: a numerical study

Ranjith

Perera

Khan

2012

Int. J. Energy Res.

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“…In statistical or predictive modeling, a model is fit to the runs obtained by experimental design (Wood et al, 2008;Anbar and Akin, 2011;Mishra et al, 2015). Numerical simulation is used as virtual experimentation to create a database of observations.…”

Section: Introductionmentioning

confidence: 99%

“…They use a combination of Box-Behnken and factorial experimental design and use linear regression for modeling. Anbar and Akin (2011) present a proxy model which can predict CO 2 storage capacity of deep saline carbonate aquifers. They use Latin Hypercube experimental design and linear regression models.…”

Section: Introductionmentioning

confidence: 99%

Statistical modeling of geopressured geothermal reservoirs

Ansari¹,

Hughes²,

White³

2017

Computers & Geosciences

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Identifying attractive candidate reservoirs for producing geothermal energy requires predictive models. In this work, inspectional analysis and statistical modeling are used to create simple predictive models for a line drive design. Inspectional analysis on the partial differential equations governing this design yields a minimum number of fifteen dimensionless groups required to describe the physics of the system. These dimensionless groups are explained and confirmed using models with similar dimensionless groups but different dimensional parameters. This study models dimensionless production temperature and thermal recovery factor as the responses of a numerical model. These responses are obtained by a Box-Behnken experimental design. An uncertainty plot is used to segment the dimensionless time and develop a model for each segment. The important dimensionless numbers for each segment of the dimensionless time are identified using the Boosting method. These selected numbers are used in the regression models. The developed models are reduced to have a minimum number of predictors and interactions. The reduced final models are then presented and assessed using testing runs. Finally, applications of these models are offered. The presented workflow is generic and can be used to translate the output of a numerical simulator into simple predictive models in other research areas involving numerical simulation.

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Permeability heterogeneity effects on density-driven CO2 natural convection and carbon sequestration efficiency

Zhang,

Xu,

Yang

et al. 2024

Fuel

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Development of a linear predictive model for carbon dioxide sequestration in deep saline carbonate aquifers

Cited by 10 publications

References 26 publications

A study of safe CO₂storage capacity in saline aquifers: a numerical study

A study of safe CO₂storage capacity in saline aquifers: a numerical study

Statistical modeling of geopressured geothermal reservoirs

Permeability heterogeneity effects on density-driven CO2 natural convection and carbon sequestration efficiency

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Development of a linear predictive model for carbon dioxide sequestration in deep saline carbonate aquifers

Cited by 10 publications

References 26 publications

A study of safe CO2storage capacity in saline aquifers: a numerical study

A study of safe CO2storage capacity in saline aquifers: a numerical study

Statistical modeling of geopressured geothermal reservoirs

Permeability heterogeneity effects on density-driven CO2 natural convection and carbon sequestration efficiency

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Product

Resources

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A study of safe CO₂storage capacity in saline aquifers: a numerical study

A study of safe CO₂storage capacity in saline aquifers: a numerical study