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Author - Cristina

Description of the material. In this paper a novel methodology for the estimation of the formation permeability, based on the integration of resistivity modeling and near wellbore modeling, is presented. Results obtained from the application to a real case is shown and discussed. The well log interpretation process provides a reliable estimation of the main petrophysical parameters such as porosity, fluid...


The paper provides an overview of the several scientific and technical issues and challenges to be addressed for underground storage of carbon dioxide, hydrogen and mixtures of hydrogen and natural gas. The experience gained on underground energy systems and materials is complemented by new competences to adequately respond to the new needs raised by transition from fossil fuels to renewables. The experimental...


The storage of natural gas in underground geological formations (UGS) has been widely adopted to guarantee a real-time response to the market requests as well as to ensure National “strategic” reserves. In the recent past, the UGS and related technologies have been approached with increasing interest also in terms of CO2 sequestration and of large-scale storage of chemical energy, with the...


In this paper, we discuss how to describe the geomechanical behavior of geological formations used for underground fluid storage through the application of the Virtual Element Method (VEM) on conforming polyhedral meshes for the solution of stress-strain equilibrium equations. Under the assumption of small deformations, the solution algorithm for an Isotropic Linear Elastic (ILE) constitutive law coupled...

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ISSN 1121-9041

CiteScore:
2020: 3.8
CiteScore measures the average citations received per peer-reviewed document published in this title.
CiteScore values are based on citation counts in a range of four years (e.g. 2016-2019) to peer-reviewed documents (articles, reviews, conference papers, data papers and book chapters) published in the same four calendar years, divided by the number of these documents in these same four years (e.g. 2016 —19).
Source Normalized Impact per Paper (SNIP):
2019: 1.307
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR)
2019: o.657
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal's impact.
Journal Metrics: CiteScore: 1.0 , Source Normalized Impact per Paper (SNIP): 0.381 SCImago Journal Rank (SJR): 0.163

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