{"id":{"repo_id":"colo-mines","oai_identifier":"oai:repository.mines.edu:11124/15380"},"canonical_url":"https://search.dev.ndltd.org/etd/colo-mines/oai:repository.mines.edu:11124/15380","repository":{"repo_id":"colo-mines","name":"Colorado School of Mines","base_url":"https://repository.mines.edu/server/oai/request"},"display":{"title":"Elastic time-reverse imaging and transmission tomography for microseismic and DAS VSP data","abstract":"Wavefield migration and tomography are considered to be state-of-the-art methodologies used for subsurface geological characterization. Seismic tomography produces accurate velocity models that commonly serve as input into seismic migration algorithms that produce high-quality passive-source (e.g., microseismic) images or structural images of geological interfaces constructed using controlled-source energy (e.g., vibroseis truck or dynamite). Most existing wavefield migration and tomography techniques employed in the oil and gas industry are well-developed under the acoustic assumption. One of the main shortcomings of this assumption is that conventional acoustic imaging algorithms generally use single-component P-wave data and thus do not account for multicomponent elastic (P- and S-mode) data that can provide additional subsurface information such as fracture distributions and elastic properties. To account for more accurate wave physics in passive and active seismic scenarios, I propose a suite of novel full-wavefield methods for imaging and multiparameter (i.e., P- and S-wave) model estimation in elastic media. Passive-style image-domain elastic tomography operates with multicomponent P- and S-wave first-arrival waveforms of a microseismic event and optimizes the background velocity model by improving the quality of source images constructed by a procedure called time-reverse imaging (TRI). To formulate a robust image-domain inversion framework, I develop a 3D extended imaging condition for surface-recorded microseismic data based on the correlation of individual P- and S-wavefield energy as well as the energy norm. The proposed PS energy imaging condition not only effectively locates microseismic events for complex isotropic/anisotropic models but also provides useful information about P- and S-wave velocity model as well as anisotropy parameter $[\\epsilon,\\delta,\\gamma]$ accuracy. Based on the kinetic energy term of the PS energy imaging condition, I propose an image-domain elastic wavefield tomography framework to build plausible P- and S-wave velocity models that improve the quality of microseismic event images. I present synthetic numerical experiments to demonstrate that the estimated model parameters result in enhanced source images, which greatly reduce event mispositioning errors. Finally, I apply the developed image-domain elastic inversion method on an active-source distributed acoustic sensing 3D vertical seismic profiling data set acquired in the North Slope of Alaska to investigate potential methane gas hydrate reservoirs. I exploit source-receiver reciprocity to create an acquisition configuration that resembles passive-seismic surface monitoring scenarios. I first validate the accuracy of the inverted elastic velocity models using a TRI-based source location analysis. Next, I construct numerous 3D structural images of the area of interest through elastic reverse time migration (RTM). The elastic RTM results exhibit coherent reflectivity associated with a complex near-surface ice-bearing permafrost zone, as well as two gas hydrate reservoirs that satisfactorily match the existing log data in well-ties due to the improved velocity model estimates.","abstract_html":"Wavefield migration and tomography are considered to be state-of-the-art methodologies used for subsurface geological characterization. Seismic tomography produces accurate velocity models that commonly serve as input into seismic migration algorithms that produce high-quality passive-source (e.g., microseismic) images or structural images of geological interfaces constructed using controlled-source energy (e.g., vibroseis truck or dynamite). Most existing wavefield migration and tomography techniques employed in the oil and gas industry are well-developed under the acoustic assumption. One of the main shortcomings of this assumption is that conventional acoustic imaging algorithms generally use single-component P-wave data and thus do not account for multicomponent elastic (P- and S-mode) data that can provide additional subsurface information such as fracture distributions and elastic properties. To account for more accurate wave physics in passive and active seismic scenarios, I propose a suite of novel full-wavefield methods for imaging and multiparameter (i.e., P- and S-wave) model estimation in elastic media. Passive-style image-domain elastic tomography operates with multicomponent P- and S-wave first-arrival waveforms of a microseismic event and optimizes the background velocity model by improving the quality of source images constructed by a procedure called time-reverse imaging (TRI). To formulate a robust image-domain inversion framework, I develop a 3D extended imaging condition for surface-recorded microseismic data based on the correlation of individual P- and S-wavefield energy as well as the energy norm. The proposed PS energy imaging condition not only effectively locates microseismic events for complex isotropic/anisotropic models but also provides useful information about P- and S-wave velocity model as well as anisotropy parameter <span class=\"etd-inline-math\">[&epsilon;,&delta;,&gamma;]</span> accuracy. Based on the kinetic energy term of the PS energy imaging condition, I propose an image-domain elastic wavefield tomography framework to build plausible P- and S-wave velocity models that improve the quality of microseismic event images. I present synthetic numerical experiments to demonstrate that the estimated model parameters result in enhanced source images, which greatly reduce event mispositioning errors. Finally, I apply the developed image-domain elastic inversion method on an active-source distributed acoustic sensing 3D vertical seismic profiling data set acquired in the North Slope of Alaska to investigate potential methane gas hydrate reservoirs. I exploit source-receiver reciprocity to create an acquisition configuration that resembles passive-seismic surface monitoring scenarios. I first validate the accuracy of the inverted elastic velocity models using a TRI-based source location analysis. Next, I construct numerous 3D structural images of the area of interest through elastic reverse time migration (RTM). The elastic RTM results exhibit coherent reflectivity associated with a complex near-surface ice-bearing permafrost zone, as well as two gas hydrate reservoirs that satisfactorily match the existing log data in well-ties due to the improved velocity model estimates.","abstract_has_math":true,"creators":["Oren, Can"],"institution":"Colorado School of Mines. Arthur Lakes Library","degree_name":"Doctor of Philosophy (Ph.D.)","degree_level":"Doctoral","degree_discipline":"Geophysics","degree_department":null,"school":null,"contributors":[],"advisors":["Shragge, Jeffrey"],"committee_chairs":[],"committee_members":["Sava, Paul C.","Bozdag, Ebru","Ganesh, Mahadevan","Walton, Gabriel"],"year":2022,"date_issued":"2022","date_published":"2022","updated_at":"2026-07-24T01:43:31Z","subjects":["computational seismology","distributed acoustic sensing","elastic wave propagation","microseismic","seismic imaging","seismic tomography"],"languages":["eng","English"],"rights":["Copyright of the original work is retained by the author."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["T 9297"],"render_values":[{"text":"T 9297","href":null,"code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/11124/15380","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Shragge, Jeffrey"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Sava, Paul C.","Bozdag, Ebru","Ganesh, Mahadevan","Walton, Gabriel"]},{"key":"dc:creator","label":"Author","values":["Oren, Can"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-10-06T17:28:15Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-10-06T17:28:15Z"]},{"key":"dc:date.issued","label":"Date","values":["2022"]},{"key":"dc:publisher","label":"Institution","values":["Colorado School of Mines. 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Seismic tomography produces accurate velocity models that commonly serve as input into seismic migration algorithms that produce high-quality passive-source (e.g., microseismic) images or structural images of geological interfaces constructed using controlled-source energy (e.g., vibroseis truck or dynamite). Most existing wavefield migration and tomography techniques employed in the oil and gas industry are well-developed under the acoustic assumption. One of the main shortcomings of this assumption is that conventional acoustic imaging algorithms generally use single-component P-wave data and thus do not account for multicomponent elastic (P- and S-mode) data that can provide additional subsurface information such as fracture distributions and elastic properties. To account for more accurate wave physics in passive and active seismic scenarios, I propose a suite of novel full-wavefield methods for imaging and multiparameter (i.e., P- and S-wave) model estimation in elastic media. Passive-style image-domain elastic tomography operates with multicomponent P- and S-wave first-arrival waveforms of a microseismic event and optimizes the background velocity model by improving the quality of source images constructed by a procedure called time-reverse imaging (TRI). To formulate a robust image-domain inversion framework, I develop a 3D extended imaging condition for surface-recorded microseismic data based on the correlation of individual P- and S-wavefield energy as well as the energy norm. The proposed PS energy imaging condition not only effectively locates microseismic events for complex isotropic/anisotropic models but also provides useful information about P- and S-wave velocity model as well as anisotropy parameter $[\\epsilon,\\delta,\\gamma]$ accuracy. Based on the kinetic energy term of the PS energy imaging condition, I propose an image-domain elastic wavefield tomography framework to build plausible P- and S-wave velocity models that improve the quality of microseismic event images. I present synthetic numerical experiments to demonstrate that the estimated model parameters result in enhanced source images, which greatly reduce event mispositioning errors. Finally, I apply the developed image-domain elastic inversion method on an active-source distributed acoustic sensing 3D vertical seismic profiling data set acquired in the North Slope of Alaska to investigate potential methane gas hydrate reservoirs. I exploit source-receiver reciprocity to create an acquisition configuration that resembles passive-seismic surface monitoring scenarios. I first validate the accuracy of the inverted elastic velocity models using a TRI-based source location analysis. Next, I construct numerous 3D structural images of the area of interest through elastic reverse time migration (RTM). The elastic RTM results exhibit coherent reflectivity associated with a complex near-surface ice-bearing permafrost zone, as well as two gas hydrate reservoirs that satisfactorily match the existing log data in well-ties due to the improved velocity model estimates."]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["born digital","doctoral dissertations"]},{"key":"dc:title","label":"Title","values":["Elastic time-reverse imaging and transmission tomography for microseismic and DAS VSP data"]}]}],"canonical_facts":{"dc:contributor.advisor":["Shragge, Jeffrey"],"dc:contributor.committeemember":["Sava, Paul C.","Bozdag, Ebru","Ganesh, Mahadevan","Walton, Gabriel"],"dc:creator":["Oren, Can"],"dc:date.accessioned":["2022-10-06T17:28:15Z"],"dc:date.available":["2022-10-06T17:28:15Z"],"dc:date.issued":["2022"],"dc:description":["Includes bibliographical references.","2022 Spring."],"dc:description.abstract":["Wavefield migration and tomography are considered to be state-of-the-art methodologies used for subsurface geological characterization. Seismic tomography produces accurate velocity models that commonly serve as input into seismic migration algorithms that produce high-quality passive-source (e.g., microseismic) images or structural images of geological interfaces constructed using controlled-source energy (e.g., vibroseis truck or dynamite). Most existing wavefield migration and tomography techniques employed in the oil and gas industry are well-developed under the acoustic assumption. One of the main shortcomings of this assumption is that conventional acoustic imaging algorithms generally use single-component P-wave data and thus do not account for multicomponent elastic (P- and S-mode) data that can provide additional subsurface information such as fracture distributions and elastic properties. To account for more accurate wave physics in passive and active seismic scenarios, I propose a suite of novel full-wavefield methods for imaging and multiparameter (i.e., P- and S-wave) model estimation in elastic media. Passive-style image-domain elastic tomography operates with multicomponent P- and S-wave first-arrival waveforms of a microseismic event and optimizes the background velocity model by improving the quality of source images constructed by a procedure called time-reverse imaging (TRI). To formulate a robust image-domain inversion framework, I develop a 3D extended imaging condition for surface-recorded microseismic data based on the correlation of individual P- and S-wavefield energy as well as the energy norm. The proposed PS energy imaging condition not only effectively locates microseismic events for complex isotropic/anisotropic models but also provides useful information about P- and S-wave velocity model as well as anisotropy parameter $[\\epsilon,\\delta,\\gamma]$ accuracy. Based on the kinetic energy term of the PS energy imaging condition, I propose an image-domain elastic wavefield tomography framework to build plausible P- and S-wave velocity models that improve the quality of microseismic event images. I present synthetic numerical experiments to demonstrate that the estimated model parameters result in enhanced source images, which greatly reduce event mispositioning errors. Finally, I apply the developed image-domain elastic inversion method on an active-source distributed acoustic sensing 3D vertical seismic profiling data set acquired in the North Slope of Alaska to investigate potential methane gas hydrate reservoirs. I exploit source-receiver reciprocity to create an acquisition configuration that resembles passive-seismic surface monitoring scenarios. I first validate the accuracy of the inverted elastic velocity models using a TRI-based source location analysis. Next, I construct numerous 3D structural images of the area of interest through elastic reverse time migration (RTM). The elastic RTM results exhibit coherent reflectivity associated with a complex near-surface ice-bearing permafrost zone, as well as two gas hydrate reservoirs that satisfactorily match the existing log data in well-ties due to the improved velocity model estimates."],"dc:format.medium":["born digital","doctoral dissertations"],"dc:identifier":["Oren_mines_0052E_12345.pdf","T 9297"],"dc:identifier.uri":["https://hdl.handle.net/11124/15380"],"dc:language":["English"],"dc:language.iso":["eng"],"dc:publisher":["Colorado School of Mines. Arthur Lakes Library"],"dc:rights":["Copyright of the original work is retained by the author."],"dc:subject":["computational seismology","distributed acoustic sensing","elastic wave propagation","microseismic","seismic imaging","seismic tomography"],"dc:title":["Elastic time-reverse imaging and transmission tomography for microseismic and DAS VSP data"],"dc:type":["Text"],"thesis:degree_discipline":["Geophysics"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["Doctor of Philosophy (Ph.D.)"],"thesis:institution_name":["Colorado School of Mines"]},"updated_at":"2026-07-24T01:43:31Z"}