A new subsampling methodology to optimize the characterization of two-dimensional bedrock fracture networks

dc.contributor.authorOvaskainen Nikolas
dc.contributor.authorNordbäck Nicklas
dc.contributor.authorSkyttä Pietari
dc.contributor.authorEngström Jon
dc.contributor.organizationfi=geologia|en=Geology |
dc.contributor.organization-code1.2.246.10.2458963.20.72020864681
dc.contributor.organization-code2606902
dc.converis.publication-id68845913
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/68845913
dc.date.accessioned2022-10-26T15:22:49Z
dc.date.available2022-10-26T15:22:49Z
dc.description.abstract<p><br></p><p>This paper introduces a new subsampling method to determine the empirical relationships between the areal sampling coverage and the topological-geometric parameters resulting from characterization of two-dimensional outcrop <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/fracture-network" title="Learn more about fracture networks from ScienceDirect's AI-generated Topic Pages">fracture networks</a>. We further developed these relationships into correlations between the total sampling coverage and variance of the characterization result, hence providing insight to the objective uncertainties related to fracture network characterization. The analyses were conducted using two new open-source Python packages: fractopo and fractopo-subsampling, designed for fracture network analysis and subsampling, respectively. We conducted the study on the well-exposed crystalline outcrops of Getaberget, Åland Islands, Finland, where a total of 42499 fracture traces were manually digitized from 13 circular target areas. For the purposes of subsampling, we conducted fracture network characterization for randomly located and sized subsample areas, which locate within the larger target areas.</p><p>Based on our subsampling results we provide recommendations for the preliminary optimization of areal coverage used in outcrop fracture sampling and the use of our subsampling method for assessing the precision related to the areal fracture network characterization in other previously uncharacterized areas. As an example, we recommend using a total sampling area of 8000</p><p>with 8 circular sampling areas to define the power-law exponents of fracture traces when conducting outcrop fracture network characterization with drone-based methodology done with similar initial sampling setup in comparable geological environments, as this coverage has shown an acceptable level of precision.</p>
dc.identifier.eissn1873-1201
dc.identifier.jour-issn0191-8141
dc.identifier.olddbid171729
dc.identifier.oldhandle10024/154823
dc.identifier.urihttps://www.utupub.fi/handle/11111/29224
dc.identifier.urlhttps://doi.org/10.1016/j.jsg.2022.104528
dc.identifier.urnURN:NBN:fi-fe2022021619363
dc.language.isoen
dc.okm.affiliatedauthorOvaskainen, Nikolas
dc.okm.affiliatedauthorNordbäck, Nicklas
dc.okm.affiliatedauthorSkyttä, Pietari
dc.okm.discipline113 Computer and information sciencesen_GB
dc.okm.discipline1171 Geosciencesen_GB
dc.okm.discipline113 Tietojenkäsittely ja informaatiotieteetfi_FI
dc.okm.discipline1171 Geotieteetfi_FI
dc.okm.internationalcopublicationnot an international co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherElsevier Ltd
dc.publisher.countryUnited Kingdomen_GB
dc.publisher.countryBritanniafi_FI
dc.publisher.country-codeGB
dc.relation.articlenumber104528
dc.relation.doi10.1016/j.jsg.2022.104528
dc.relation.ispartofjournalJournal of Structural Geology
dc.relation.volume155
dc.source.identifierhttps://www.utupub.fi/handle/10024/154823
dc.titleA new subsampling methodology to optimize the characterization of two-dimensional bedrock fracture networks
dc.year.issued2022

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