Geological Susceptibility to Hydraulic Fracturing-Induced Seismicity in the Montney Formation

dc.contributor.advisorEaton, David WS
dc.contributor.authorWozniakowska, Paulina Gabriela
dc.contributor.committeememberGilbert, Hersh Joseph
dc.contributor.committeememberTrad, Daniel Osvaldo
dc.contributor.committeememberPedersen, Per Kent
dc.contributor.committeememberChen, Zhangxing
dc.contributor.committeememberEberhardt, Erik
dc.date2022-06
dc.date.accessioned2022-06-02T19:43:14Z
dc.date.available2022-06-02T19:43:14Z
dc.date.issued2022-05
dc.description.abstractThis thesis focuses on induced (anthropogenic) seismicity related to hydraulic fracturing operations in the Montney Formation - a geological unit of Triassic age located in the Western Canada Sedimentary Basin. Originally a conventional oil and gas play, the Montney Formation is currently one of the most prolific unconventional resource plays worldwide. Documented cases of induced seismicity in the Montney play occur in distinct clusters, indicative of local variability of factors influencing the seismic activation potential (SAP). Notably, virtually all induced seismicity related to hydraulic fracturing, to date, has occurred in British Columbia despite similar levels of industrial activity in Alberta. This implies that geological trends may have a more significant impact on SAP than operational factors. This thesis presents several new methodologies for investigating the complex interplay between subsurface conditions and induced seismicity distribution. Three independent workflows, based on machine learning-based analysis, structural interpretation, and statistical inference, respectively, were developed to evaluate hypotheses regarding the influence of geological, geomechanical and structural controls of hydraulic fracturing-induced seismicity in the Montney Formation. First, a machine learning model was used to identify areas within the Montney that are characterized by the highest geological susceptibility to induced seismicity. The results suggest that distance to the Cordilleran deformation front and injection depth are the most important factors influencing the observed seismicity trends. Next, a multi-step workflow based on trend-surface analysis combined with geophysical data interpretation allowed major structural trends (structural corridors) to be delineated throughout the Montney play. The results of machine learning and structural interpretation were used to formulate hypotheses regarding geological factors influencing observed cluster characteristics of seismicity in the Montney. These hypotheses were independently tested using SimSeis – a newly developed tool for statistical inference based on a stochastic simulation approach. Using this tool, sets of synthetic catalogs are generated according to assumed spatial relationship(s) between geological susceptibility and/or mapped structural corridors and further compared against a Null hypothesis, corresponding to a random spatial association of induced seismicity with hydraulically fractured wells. While each of the alternative models performed significantly better than the Null hypothesis, a machine-learning model based on geological susceptibility achieved the best results. SimSeis is customizable and can be applied to investigate mechanisms that influence the distribution of induced seismicity distribution in other unconventional plays and thus enhance currently existing seismic-risk mitigation strategies.en_US
dc.identifier.citationWozniakowska, P. G. (2022). Geological susceptibility to hydraulic fracturing-induced seismicity in the Montney Formation (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/39805
dc.identifier.urihttp://hdl.handle.net/1880/114702
dc.language.isoengen_US
dc.publisher.facultyScienceen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectinduced seismicityen_US
dc.subjecthydraulic fracturingen_US
dc.subjectstatistical analysisen_US
dc.subjectmachine learningen_US
dc.subjectMontney Formationen_US
dc.subject.classificationGeologyen_US
dc.subject.classificationGeophysicsen_US
dc.titleGeological Susceptibility to Hydraulic Fracturing-Induced Seismicity in the Montney Formationen_US
dc.typedoctoral thesisen_US
thesis.degree.disciplineGeoscienceen_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameDoctor of Philosophy (PhD)en_US
ucalgary.item.requestcopytrueen_US
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