Study of CO2 injection in a depleted oil reservoir using geomechanically coupled and non-coupled simulation models

Author(s):  
Pushpa Sharma ◽  
Sayantan Ghosh ◽  
Akshay Tandon
2021 ◽  
Author(s):  
Vil Syrtlanov ◽  
Yury Golovatskiy ◽  
Ivan Ishimov

Abstract In this paper the simplified way is proposed for predicting the dynamics of liquid production and estimating the parameters of the oil reservoir using diagnostic curves, which are a generalization of analytical approaches, partially compared with the results of calculations on 3D simulation models and with actual well production data.


Author(s):  
Jiahui Ye ◽  
Mohamad Mahmoudi ◽  
Kubra Karayagiz ◽  
Luke Johnson ◽  
Raiyan Seede ◽  
...  

Abstract Modeling and simulation for additive manufacturing (AM) are critical enablers for understanding process physics, conducting process planning and optimization, and streamlining qualification and certification. It is often the case that a suite of hierarchically linked (or coupled) simulation models is needed to achieve the above task, as the entirety of the complex physical phenomena relevant to the understanding of process-structure-property-performance relationships in the context of AM precludes the use of a single simulation framework. In this study using a Bayesian network approach, we address the important problem of conducting uncertainty quantification (UQ) analysis for multiple hierarchical models to establish process-microstructure relationships in laser powder bed fusion (LPBF) AM. More significantly, we present the framework to calibrate and analyze simulation models that have unmeasurable variables, which are quantities of interest predicted by an upstream model and necessary for the downstream model in the chain that are difficult or impossible to observe experimentally. We validate the framework using a case study on predicting the microstructure of binary nickel-niobium alloys processed using LPBF as a function of processing parameters. Our framework is shown to be able to predict segregation of niobium with up to 94.3% prediction accuracy in test data.


2011 ◽  
Author(s):  
Valerio Parasiliti Parracello ◽  
Martin Bartosek ◽  
Michela De Simoni ◽  
Carolina Mallardo

2011 ◽  
Author(s):  
Valerio Parasiliti Parracello ◽  
Martin Bartosek ◽  
Michela De Simoni ◽  
Carolina Mallardo

2019 ◽  
Vol 5 (1) ◽  
pp. 4 ◽  
Author(s):  
Yen Adams Sokama-Neuyam ◽  
Jann Rune Ursin ◽  
Patrick Boakye

Deep saline reservoirs have the highest volumetric CO2 storage potential, but drying and salt precipitation during CO2 injection could severely impair CO2 injectivity. The physical mechanisms and impact of salt precipitation, especially in the injection area, is still not fully understood. Core-flood experiments were conducted to investigate the mechanisms of external and internal salt precipitation in sandstone rocks. CO2 Low Salinity Alternating Gas (CO2-LSWAG) injection as a potential mitigation technique to reduce injectivity impairment induced by salt precipitation was also studied. We found that poor sweep and high brine salinity could increase salt deposition on the surface of the injection area. The results also indicate that the amount of salt precipitated in the dry-out zone does not change significantly during the drying process, as large portion of the precipitated salt accumulate in the injection vicinity. However, the distribution of salt in the dry-out zone was found to change markedly when more CO2 was injected after salt precipitation. This suggests that CO2 injectivity impairment induced by salt precipitation is probably dynamic rather than a static process. It was also found that CO2-LSWAG could improve CO2 injectivity after salt precipitation. However, below a critical diluent brine salinity, CO2-LSWAG did not improve injectivity. These findings provide vital understanding of core-scale physical mechanisms of the impact of salt precipitation on CO2 injectivity in saline reservoirs. The insight gained could be implemented in simulation models to improve the quantification of injectivity losses during CO2 injection into saline sandstone reservoirs.


2020 ◽  
pp. 3252-3265
Author(s):  
Nagham Jasim ◽  
Sameera M. Hamd-Allah ◽  
Hazim Abass

Increasing hydrocarbon recovery from tight reservoirs is an essential goal of oil industry in the recent years. Building real dynamic simulation models and selecting and designing suitable development strategies for such reservoirs need basically to construct accurate structural static model construction. The uncertainties in building 3-D reservoir models are a real challenge for such micro to nano pore scale structure. Based on data from 24 wells distributed throughout the Sadi tight formation. An application of building a 3-D static model for a tight limestone oil reservoir in Iraq is presented in this study. The most common uncertainties confronted while building the model were illustrated. Such as accurate estimations of cut-off permeability and porosity values. These values directly affect the calculation of net pay thickness for each layer in the reservoir and consequently affect the target of estimating reservoir initial oil in place (IOIP). Also, the main challenge to the static modeling of such reservoirs is dealing with tight reservoir characteristics which cause major reservoir heterogeneity and complexities that are problematic to the process of modeling reservoir simulation. Twenty seven porosity and permeability measurements from Sadi/Tanuma reservoir were used to validate log interpretation data for model construction. The results of the history matching process of the constructed dynamic model is also presented in this paper, including data related to oil production, reservoir pressure, and well flowing pressure due to available production.


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