Geological Sequestration of Carbon Dioxide in a Depleted Oil Reservoir

Krumhansl, J. A.; Pawar, Rajesh J.; Grigg, R.; Westrich, Henry R.; Warpinski, N.R.; Zhang, D.; Jové-Colón, Carlos F.; Lichtner, Peter C.; Lorenz, John C.; Svec, Robert; Stubbs, Bruce; Cooper, Scott P.; Bradley, C. R.; Rutledge, James; Byrer, C.W.

doi:10.2118/75256-ms

Cited by 11 publications

(2 citation statements)

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“…Numerical reservoir simulators are the conventional tools used to perform the aforementioned tasks. [16][17][18][19][20][21] In order to have a comprehensive study of a CCS project, hundreds to thousands of realizations with different reservoir characteristics and operational conditions are required. Although using a numerical reservoir simulator gives accurate results, it is highly time-consuming and computationally expensive.…”

Section: Introductionmentioning

confidence: 99%

Application of Artificial Intelligence and Data Mining Techniques for Fast Track Modeling of Geologic Sequestration of Carbon Dioxide – Case Study of SACROC Unit

Shahkarami¹,

Mohaghegh

Gholami

et al. 2015

SPE Digital Energy Conference and Exhibition

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The complexities involved in the available reservoir simulation model for the geologic CO2 sequestration study at SACROC Unit, lead to a high computational cost nearly impractical for different types of reservoir studies. In this study, as an alternative to the full-field reservoir simulation model, we develop and examine the application of a new technology (Surrogate Reservoir Model -SRM) for fast track modeling of pressure and phase saturation distributions in the injection and post-injection time periods.The SRM is developed based on a few realizations of full-field reservoir simulation model, and it is able to generate the outputs in a very short time with reasonable accuracy. The SRM is developed using the pattern recognition capabilities of Artificial Intelligence and Data Mining (AI&DM) techniques. The SRM is trained based on the provided examples of the system and then verified using additional samples.The intricacy of simulating multiphase flow, having large number of time steps required to study injection and post-injection periods of CO2 sequestration, highly heterogeneous reservoir, and a large number of wells have led to a highly complicated reservoir simulation model for SACROC Unit. A single realization of this model takes hours to run. An in-depth understanding of CO2 sequestration process requires multiple realizations of the reservoir model. Consequently, using a conventional numerical simulator makes the computational cost of the analysis too high to be practical.On the other hand, the developed SRM for this case study runs in a matter of seconds. The comparison between the results of SRM and simulator, during training and verification steps of SRM development, demonstrates the ability of SRM in mimicking the behavior of numerical simulation model. The results of this study are intended to prove the potential of AI&DM based reservoir models, like SRM, to ease the obstacles involved in the conventional CO2 sequestration modeling.

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Section: Introductionmentioning

confidence: 99%

Application of Artificial Intelligence and Data Mining Techniques for Fast Track Modeling of Geologic Sequestration of Carbon Dioxide – Case Study of SACROC Unit

Shahkarami¹,

Mohaghegh

Gholami

et al. 2015

SPE Digital Energy Conference and Exhibition

View full text Add to dashboard Cite

show abstract

“…Consequently, the following tasks must be thoroughly accomplished: quality control of candidate underground storage, keeping track of CO 2 plume conditions, and simulating the reservoir behavior (such as reservoir pressure, which is an appropriate indicator of potential leakage). Numerical reservoir simulators are the conventional tools used to perform the aforementioned tasks …”

Section: Introductionmentioning

confidence: 99%

Modeling pressure and saturation distribution in a CO₂storage project using a Surrogate Reservoir Model (SRM)

Shahkarami

Mohaghegh

Gholami

et al. 2014

Greenhouse Gas Sci Technol

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Capturing carbon dioxide (CO2) from large point sources and depositing it in a geological formation is an efficient way of decreasing CO2 concentration in the atmosphere. A comprehensive study is required to perform a safe and efficient CO2 capture and storage (CCS) project. The study includes different steps, such as selecting proper underground storage and keeping track of CO2 behavior in the storage environment. Numerical reservoir simulators are the conventional tools used to implement such an analysis. The intricacy of simulating multiphase flow, having a large number of time steps required to study injection and post‐injection periods of CO2 sequestration, a highly heterogeneous reservoir, a large number of wells, etc., will lead to a complicated reservoir model. A single realization for such a reservoir takes hours to run. Additionally, a thorough understanding of the CO2 sequestration process requires multiple realizations of the reservoir model. Consequently, using a conventional numerical simulator makes the computational cost of the analysis too high to be practical. In this paper, we examine the application of a relatively new technology, the Surrogate Reservoir Model (SRM), as an alternative tool to solve the aforementioned problems. SRM is a replica of full‐field reservoir simulation models. It can generate outputs in a very short time with reasonable accuracy. These characteristics make SRM a unique tool in CO2 sequestration modeling. This paper proposes developing an SRM for a CO2 sequestration project ongoing in the SACROC unit to model pressure behavior and phase saturation distributions during different time steps of the CO2 storage process.

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The effect of CO2-enriched water salinity on enhancing oil recovery and its potential formation damage: an experimental study on shaly sandstone reservoirs

Sadati

Sahraei

Rahnema

et al. 2020

J Petrol Explor Prod Technol

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Many experimental investigations on carbonated water injection (CWI) have shown an increase in oil recovery which CWI is defined as the process of injecting CO 2-saturated water in oil reservoirs as a displacing fluid. In every enhanced oil recovery method, the potential formation damage of the injected fluid is considered. This is due to the fact that the injection of incompatible fluids often causes clay swelling and fines migration and thus impairs the formation permeability. Permeability reduction by clay particles mostly depends on its distribution which can be pore lining, pore bridging, dispersed or combination of these causing pore blocking or pore-throat diameter reduction. Besides, fine migration is considered as an important mechanism of recovery improvement during injection of low-salinity water in sandstone oil reservoirs. The present paper investigates the impact of injection of carbonated water and brines with the different salt concentrations on oil recovery and formation damage focusing on permeability variation. The investigation has been done on 12 relatively homogeneous claycontaining sandstone cores, while the compositions of the injection water were varied from 40,000 to 1000 ppm, at 176° F and 2000 psi. The amount of recovery improvement and permeability drop recorded in all tests and the fine effluent of two experiments were analysed using XRD, one for CWI and one for WF (water flooding). In all salinities, CWI has shown more oil recovery improvement than conventional water. CWI of 40,000 ppm showed the minimum permeability reduction of 6 percent, while the highest permeability was obtained by injection of water with 1000 ppm. Maximum ultimate oil recoveries of 61.2% and 42% were achieved by 1000 ppm both for CWI and WF, respectively. In comparison with brine injection, CWI resulted in more permeability drop in salinity above critical salt concentration (CSC), while below CSC, WF has caused more formation damage than CWI. Experimental results also showed that fine migration was the main reason behind formation damage. It was also revealed that permeability was significantly reduced due to fine production in the effluent.

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Geological Sequestration of Carbon Dioxide in a Depleted Oil Reservoir

Cited by 11 publications

References 1 publication

Application of Artificial Intelligence and Data Mining Techniques for Fast Track Modeling of Geologic Sequestration of Carbon Dioxide – Case Study of SACROC Unit

Application of Artificial Intelligence and Data Mining Techniques for Fast Track Modeling of Geologic Sequestration of Carbon Dioxide – Case Study of SACROC Unit

Modeling pressure and saturation distribution in a CO₂storage project using a Surrogate Reservoir Model (SRM)

The effect of CO2-enriched water salinity on enhancing oil recovery and its potential formation damage: an experimental study on shaly sandstone reservoirs

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Geological Sequestration of Carbon Dioxide in a Depleted Oil Reservoir

Cited by 11 publications

References 1 publication

Application of Artificial Intelligence and Data Mining Techniques for Fast Track Modeling of Geologic Sequestration of Carbon Dioxide – Case Study of SACROC Unit

Application of Artificial Intelligence and Data Mining Techniques for Fast Track Modeling of Geologic Sequestration of Carbon Dioxide – Case Study of SACROC Unit

Modeling pressure and saturation distribution in a CO2storage project using a Surrogate Reservoir Model (SRM)

The effect of CO2-enriched water salinity on enhancing oil recovery and its potential formation damage: an experimental study on shaly sandstone reservoirs

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Modeling pressure and saturation distribution in a CO₂storage project using a Surrogate Reservoir Model (SRM)