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석유자료 DB를 위한 중합 전 구조보정기술 개발
Development of Prestack Migration for Petroleum Database

  • 사업명

    (연구회소관출연기관)한국지질자원연구원<공공>(에특)

  • 과제명

    석유자료 DB를 위한 중합 전 구조보정 기술개발

  • 주관연구기관

    한국지질자원연구원
    Korea Institute of Geoscience and Mineral Resources

  • 연구책임자

    장성형

  • 참여연구자

    고재홍   김현태   황인걸  

  • 보고서유형

    1단계보고서

  • 발행국가

    대한민국

  • 언어

    한국어

  • 발행년월

    2009-12

  • 과제시작년도

    2009

  • 주관부처

    지식경제부

  • 사업 관리 기관

    산업기술연구회

  • 등록번호

    TRKO201000000112

  • 과제고유번호

    1415101943

  • 키워드

    석유탐사.DB.중합 전 구조보정.탄성파 속도.클러스터링.seimsic.DB.prestack migration.seismic velocity.clustering.

  • DB 구축일자

    2013-04-18

  • 초록 


    The object of this study is development of parallel seismic data processing technology for huge seismic data set. In the area of ...

    The object of this study is development of parallel seismic data processing technology for huge seismic data set. In the area of seismic data processing technology, we would like to develop 3D parallelized seismic depth migration. The technology of seismic data processing, which is one of the required technology for petroleum exploration (acquisition, processing, and interpretation), is needed to interprets deep geological structures and to decide for proper drilling sites. Since seismic data set are huge and require heavy computer power, it could be hard to apply depth migration in the past. However, it is possible to apply prestack depth migration due to the developing computer technology, Changes of seismic data processing environment make possible to develops parallel processing technology and we would like to study parallel depth migration among various seismic data processing technology. Petroleum exploration technology has been developed in the advanced countries and it is the best method to image the subsurface of the potential oil and gas fields such as stratigraphic structures, thrustbelts, and oil trap structures. The acquired seismic data set can be turned geological images with careful seismic data processing and it can be possible to interpret the geological structures, In the Korean continental shelf seismic data set for oil, gas and gas-hydrate have been acquired by the KIGAM technology since 1998, but the data set have been processed by foreign seismic processing packages and the most of the processing results are in time section. So we need not only domestic data processing software technology but also parallel processing technology for huge seismic data set. The parallel processing technology for seismic exploration is good for processing huge data set and for making depth section. This is one of good tools for us to image precisely the subsurface and to use for the basic data for deciding a drilling site. And this parallel processing technology is also important for energy resources exploration in the Korean continental shelf such as gas-hydrate and is useful for preparing the basic data which is needed for mapping the subsurface stratigraphic structures and continental sedimentary channel structures. The content for the research objects includes to parallelize depth migration, to develope 3D velocity model and analysis of seismic data. The first content is to develops 3D parallel codes for the phase-shift-plus-interpolation (PSPI), which is one of the prestack depth migration and popular method in frequency-wavenumber domain seismic migration. The second one is to develops tools for parallel processing system since this technology is needed for transferring data between nodes according as the seismic data set are getting huge. The third one is analysis techniques of seismic data in the offshore, the East Sea of Korea. For the 3D prestack depth migration, we are going to develops the prestack depth migration with MPI_PSPI, which is one of the seismic data processing technology, and then we will verify the parallelized codes with a field data set. In this study we had conducted to design an basic module over 3D prestack migration and made web-based manual. For the application to the field data set, we had processed 3D seismic data in the East Sea of Korea. During the 3D processing, we had conducted making geometry with source and receiver positions and basic preprocessing such as amplitude recovery, deconvolution, bandpass filtering, velocity picking, NMO correction, and 3D stack. The results of the processed is displayed in-line and x-line images. The velocity model will be used as a input data for prestack depth migraton when we apply the 3D prestack migration to the field data set. The clustering machine with 33 nodes cluster and 5 TB file server is running by the seismic data processing group (SDP) of KIGAM and the SDP group is developing the tools for the massive and high performance processing system. For monitering the cluster system we developed a load view tool, "mloadv", which display the multiple processes load view while each computing nodes is running. For the analysis of seismic data we developed time-frequency analysis to find out geophysical anomalies in the stacked image and applied to the synthetic and field data of the East Sea. We chose a seismic line of potential gas and applied this technology to a stacked image and made a time-frequency image over the stacked image. The results of analysis of the time-frequency shows that the 75 Hz frequency gather would be used to locate the position of the high amplitude. The developed techniques are going to be applied to not only the developing gas and gas-hydrate of East sea but also to seismic data processing for the petroleum exploration of offshore Korea and overseas, It will be applied to a decision for proper drilling site, petroleum data processing system/ the investigating analysis for developing petroleum resources, exploration for submarine resources of offshore Korea, and economic evaluation for the shallow gas of offshore Korea.


    $\circ$ 연구의 내용
    - 3차원 중합 전 구조보정 모듈설계
    - 탄성파 속도 분석 및 속도 단면도 제작
    - 33 노드 탄성파 자료처리 병렬시스템 운영기술 개발
    - 동해 대륙붕 시추공 및 ...

    $\circ$ 연구의 내용
    - 3차원 중합 전 구조보정 모듈설계
    - 탄성파 속도 분석 및 속도 단면도 제작
    - 33 노드 탄성파 자료처리 병렬시스템 운영기술 개발
    - 동해 대륙붕 시추공 및 탄성파 자료 분석
    $\circ$ 연구의 범위
    - 3D PSPI 심도 구조보정 병렬코드 개발
    - 3차원 속도모델 구축
    - 3차원 탄성파자료 심도구조보정 현장자료 적용
    - 3차원 탄성파 단면도 제작
    - 동해 대륙붕 시추공 및 탄성파 자료 분석 결과 석유정보 DB 기초자료제공


  • 목차(Contents) 

    1. 제 1 장 연구개발과제의 개요 ...14
    2. 제 2 장 국내외 기술개발 현황 ...15
    3. 제 3 장 연구개발 수행내용 및 결과 ...17
    4. 제 1 절 서론 ...17
    5. 제 2 절 3D 탐사자료 처리 개요 ...19
    6. 1. 탐사자료의 특성 ...19
    7. 2. 구조보정...
    1. 제 1 장 연구개발과제의 개요 ...14
    2. 제 2 장 국내외 기술개발 현황 ...15
    3. 제 3 장 연구개발 수행내용 및 결과 ...17
    4. 제 1 절 서론 ...17
    5. 제 2 절 3D 탐사자료 처리 개요 ...19
    6. 1. 탐사자료의 특성 ...19
    7. 2. 구조보정을 위한 여유측선 ...20
    8. 3. 수진기 및 측선간격 ...21
    9. 4. 격자크기 결정 ...24
    10. 5. CMP 빈링 ...24
    11. 가. 동적빈링 ...24
    12. 나. 정적빈링 ...25
    13. 다. 플렉스블빈링 ...26
    14. 제 3 절 3D 구조보정 ...26
    15. 1. 3D PSPI 이론식 ...26
    16. 2. 3D PSPI 모듈설계 ...29
    17. 3. 3D PSPI 알고리즘 ...30
    18. 제 4 절 병렬컴퓨터 구조 ...32
    19. 1. 분산처리시스템 ...32
    20. 2. 병렬처리방식 ...33
    21. 3. 병렬처리소프트웨어 ...34
    22. 4. 클러스터 시스템 ...34
    23. 5. 클러스터 시스템 운영 ...35
    24. 가. mloadv ...35
    25. 나. ganglia ...36
    26. 다. 구조보정 프로세스 모니터링 ...37
    27. 제 5 절 3D 기본자료처리 및 속도분석 ...38
    28. 1. 현장자료준비 ...38
    29. 2. 기본탐사자료처리 ...42
    30. 3. 속도분석 ...49
    31. 4. 속도단면도구축 ...53
    32. 가. 구간속도의 공간분포분석 ...53
    33. (1) 공간적 상관관계 ...54
    34. (2) 적합모델 ...54
    35. (3) 크리깅 ...56
    36. 나. 2차원 속도모델 크리깅 해석 ...58
    37. 다. 현장자료에 대한 속도함수 공간분포 ...60
    38. 제 6 절 동해대륙붕 탄성파 자료분석 ...62
    39. 1. 시간-주파수 분석 ...62
    40. 가. 인공자료에 대한 시간-주파수 변환 ...63
    41. 나. 동해 탄성파탐사자료 시간-주파수 분석 ...64
    42. 2. 동해 시추공자료분석 ...69
    43. 제 7 절 결론 ...69
    44. 제 4 장 목표달성도 및 관련분야에의 기여도 ...71
    45. 제 5 장 연구개발결과의 활용계획 ...72
    46. 제 6 장 연구개발과정에서 수집한 해외과학기술정보 ...73
    47. 제 7 장 참고문헌 ...74
    48. 부록 1: A usage for 3D PSPI ...76
    49. 부록 2: A list of module for viewing multiple process load ...82
    50. 그림목차
    51. Fig. 2-1. The 3D aperture window ...21
    52. Fig. 2-2. Deviation of the threshold frequency for spatial aliasing. Spatial alia occures when he time difference between the arrivals at receivers A and B is one-half period (T/2) apar. ...22
    53. Fig. 2-3. Determination of optimum line spacing. ...23
    54. Fig. 2-4. When feather angle is 10, midpoint associated with the receivers. ...25
    55. Fig. 2-5. Cable feathering as a result of currents smears depth point coverage. ...26
    56. Fig. 3-1. A usage of prestack 3D PSPI migration. ...30
    57. Fig. 3-2. Basic algorithm for psm3d. ...32
    58. Fig. 4-1. Distributed memory system. ...33
    59. Fig. 4-2. Shared memory computer system. ...33
    60. Fig. 4-3. Domain decomposition problem. ...34
    61. Fig. 4-4. The result of "top". ...36
    62. Fig. 4-5. The result of "mloadv" module. ...36
    63. Fig. 4-6. A cluster monitering tool using ganglia. ...37
    64. Fig. 4-7. The monitering view of running migration over each shot gather. ...37
    65. Fig. 5-1. Source location map for survey area. ...39
    66. Fig. 5-2. Attribute analysis for CDP fold and bin coverage to 10 survey lines be flexible binning. Maximum CDP fold is 60. ...41
    67. Fig. 5-3. Attribute analysis for CDP fold and bin coverage to 10 survey lines flexible binning. Maximum CDP fold is 60. ...41
    68. Fig. 5-4. A flowchart for processing. ...43
    69. Fig. 5-5. Shotgathers for a single shot. ...44
    70. Fig. 5-6. Preprocessed shotgathers. ...44
    71. Fig. 5-7. The results of near trace gathers when In-line is 10, 20, and 30. ...45
    72. Fig. 5-8. The results of amplitude correction. ...46
    73. Fig. 5-9. The results of gain recovery. ...47
    74. Fig. 5-10. The results of the deconvolution. ...47
    75. Fig. 5-11. The results of band pass filtering. ...48
    76. Fig. 5-12. Velocity analysis and NMO corrected supergather. ...50
    77. Fig. 5-13. Stack image at Inline 6. ...51
    78. Fig. 5-14. Stack image at Inline 7. ...51
    79. Fig. 5-15. Stack image at Inline 8. ...52
    80. Fig. 5-16. Stack image at Inline 9. ...52
    81. Fig. 5-17. Stack image at Inline 10. ...53
    82. Fig. 5-18. Construction of variogram in l-dimension space. ...54
    83. Fig. 5-19. Spherical model function. ...55
    84. Fig. 5-20. Schematic view of variogram relationships for point Kriging. ...57
    85. Fig. 5-21. Schematic view of variogram relationships for block Kriging. ...58
    86. Fig. 5-22. 2-dimension data location map of permeability samples. ...59
    87. Fig. 5-23. The velocity distribution of 2-dimension reservoir. ...60
    88. Fig. 5-24. Velocity picking points and the results of semblance analysis, (b) is the RMS velocity functions and (c) is the results of applying velocity corridor. ...61
    89. Fig. 5-25. 3D velocity grid and NMO velocity cube after applying Kriging. (a) is the results of velocity analysis and (b) is the 3D NMO velocity model. ...61
    90. Fig. 5-26. (a) is the average of NMO velocity model and (b) is the interval velocity model. ...62
    91. Fig. 6-1. Synthetics waveform created by different source wavelets at different locations of reflectivity and its time-frequency spectrum. ...64
    92. Fig. 6-2. An original shot gather and its preprocessed result. ...65
    93. Fig. 6-3. Stack image. ...66
    94. Fig. 6-4. Velocity spectrum at shot point #5574. ...67
    95. Fig. 6-5. Time-frequency spectrum of the single trace at shot point #5574. ...67
    96. Fig. 6-6. Time-frequency spectrum to the stack image at 75 Hz. ...68
    97. Fig. 6-7. The results of wireline logging data. ...69
    98. 표목차
    99. Table 5-1. Field data acquisition parameters ...39
    100. Table 5-2. Result of Binning ...40
    101. Table 5-3. Preprocessing modules and parameters ...42
    102. Table 5-4. Velocity sample data of 2-dimension space ...59
    103. Table 6-1. Acquisition parameters of the seismic survey ...65
    104. Table 6-2. Preprocessing parameters ...65
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