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DAS Signal Analysis with Autoencoders, Strainmeter Comparisons, and Near-Surface Tomography
DAS Signal Analysis with Autoencoders, Strainmeter Comparisons, and Near-Surface Tomography
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202105121
- ISBN
- 9798293884827
- DDC
- 550
- 서명/저자
- DAS Signal Analysis with Autoencoders, Strainmeter Comparisons, and Near-Surface Tomography
- 발행사항
- [Sl] : University of California, San Diego, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 131 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-03, Section: B.
- 주기사항
- Advisor: Gerstoft, Peter.
- 학위논문주기
- Thesis (Ph.D.)--University of California, San Diego, 2025.
- 초록/해제
- 요약This dissertation demonstrates the potential of Distributed Acoustic Sensing (DAS) for advancing seismological studies through applications in seismic monitoring, calibration, and near-surface imaging.Chapter 2 applies unsupervised machine learning to seismic data recorded during hydraulic stimulation at the Frontier Observatory for Research in Geothermal Energy (FORGE) in Utah. A borehole DAS array captured signals during fluid injection in April and May 2019. Spectrograms of detected events were compressed into a nine-dimensional latent feature space using a deep autoencoder, and Gaussian mixture model clustering classified signals into seven categories. Spatiotemporal analysis revealed a bimodal depth distribution, with shallow detections between 250--500 m and deeper signals near 750 m. Two dominant classes showed weak or no correlation with injection activity, demonstrating the ability to rapidly identify, categorize, and explore seismic signals for insights into source mechanisms.Chapter 3 addresses the calibration of DAS strain measurements by comparing them with Optical Fiber Strainmeters (OFSs) and seismometer-derived strain. A dark-fiber cable spanning Whidbey and Camano Islands in Washington recorded strain using both DAS and OFS Michelson interferometers. Teleseismic earthquake data showed strong agreement between summed DAS channels and OFS measurements, though amplitude discrepancies revealed imperfect cable coupling. A piezoelectric cylinder experiment provided ground-truth strain, highlighting reduced DAS amplitudes at lower frequencies. Additionally, underwater DAS signals correlated with tidal current velocity, and coherence analysis with OFS data enabled source localization. These results underscore the need for amplitude calibration and demonstrate the environmental sensitivity of DAS.Chapter 4 presents a high-resolution near-surface seismic tomography of coastal Del Mar, California, using a 14.7 km buried DAS array that recorded train-induced vibrations. Cross-correlation between DAS channels and beamforming of the correlated signals produced 1D shear-wave velocity profiles along the fiber, which were combined into a 2D tomographic model. Low-velocity zones in the San Dieguito Valley and Los Penasquitos Lagoon correspond to thick alluvial and lagoonal sediments, and two low-Vs30 regions along the coastal bluff coincide with sand-rich or artificial fill deposits. Diurnal DAS strain variations further indicate temperature sensitivity and potential fiber spool locations.These chapters show that DAS enables automated seismic monitoring, quantitative strain calibration, and high-resolution subsurface imaging, providing a versatile and cost-effective tool for geophysical research.
- 일반주제명
- Geophysics
- 키워드
- Autoencoders
- 키워드
- Strainmeter
- 키워드
- Seismology
- 기타저자
- University of California, San Diego Scripps Institution of Oceanography
- 기본자료저록
- Dissertations Abstracts International. 87-03B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
008260126s2025 us c eng d■001000017359456
■00520260202105121
■006m o d
■007cr#unu||||||||
■020 ▼a9798293884827
■035 ▼a(MiAaPQ)AAI32238343
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a550
■1001 ▼aChien, Chih-Chieh.
■24510▼aDAS Signal Analysis with Autoencoders, Strainmeter Comparisons, and Near-Surface Tomography
■260 ▼a[Sl]▼bUniversity of California, San Diego▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a131 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-03, Section: B.
■500 ▼aAdvisor: Gerstoft, Peter.
■5021 ▼aThesis (Ph.D.)--University of California, San Diego, 2025.
■520 ▼aThis dissertation demonstrates the potential of Distributed Acoustic Sensing (DAS) for advancing seismological studies through applications in seismic monitoring, calibration, and near-surface imaging.Chapter 2 applies unsupervised machine learning to seismic data recorded during hydraulic stimulation at the Frontier Observatory for Research in Geothermal Energy (FORGE) in Utah. A borehole DAS array captured signals during fluid injection in April and May 2019. Spectrograms of detected events were compressed into a nine-dimensional latent feature space using a deep autoencoder, and Gaussian mixture model clustering classified signals into seven categories. Spatiotemporal analysis revealed a bimodal depth distribution, with shallow detections between 250--500 m and deeper signals near 750 m. Two dominant classes showed weak or no correlation with injection activity, demonstrating the ability to rapidly identify, categorize, and explore seismic signals for insights into source mechanisms.Chapter 3 addresses the calibration of DAS strain measurements by comparing them with Optical Fiber Strainmeters (OFSs) and seismometer-derived strain. A dark-fiber cable spanning Whidbey and Camano Islands in Washington recorded strain using both DAS and OFS Michelson interferometers. Teleseismic earthquake data showed strong agreement between summed DAS channels and OFS measurements, though amplitude discrepancies revealed imperfect cable coupling. A piezoelectric cylinder experiment provided ground-truth strain, highlighting reduced DAS amplitudes at lower frequencies. Additionally, underwater DAS signals correlated with tidal current velocity, and coherence analysis with OFS data enabled source localization. These results underscore the need for amplitude calibration and demonstrate the environmental sensitivity of DAS.Chapter 4 presents a high-resolution near-surface seismic tomography of coastal Del Mar, California, using a 14.7 km buried DAS array that recorded train-induced vibrations. Cross-correlation between DAS channels and beamforming of the correlated signals produced 1D shear-wave velocity profiles along the fiber, which were combined into a 2D tomographic model. Low-velocity zones in the San Dieguito Valley and Los Penasquitos Lagoon correspond to thick alluvial and lagoonal sediments, and two low-Vs30 regions along the coastal bluff coincide with sand-rich or artificial fill deposits. Diurnal DAS strain variations further indicate temperature sensitivity and potential fiber spool locations.These chapters show that DAS enables automated seismic monitoring, quantitative strain calibration, and high-resolution subsurface imaging, providing a versatile and cost-effective tool for geophysical research.
■590 ▼aSchool code: 0033.
■650 4▼aGeophysics
■653 ▼aAutoencoders
■653 ▼aStrainmeter
■653 ▼aDistributed Acoustic Sensing
■653 ▼aSeismology
■690 ▼a0373
■690 ▼a0467
■71020▼aUniversity of California, San Diego▼bScripps Institution of Oceanography.
■7730 ▼tDissertations Abstracts International▼g87-03B.
■790 ▼a0033
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17359456▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
