Application of non-linear tomography technology to gas hydrate imaging in the Qiongdongnan area

SHUAI Qingwei; XU Yunxia; WEN Pengfei; SHA Zhibin; WAN Xiaoming

doi:10.16562/j.cnki.0256-1492.2020040301

2020 Vol. 40, No. 3

Article Contents

Article navigation > Marine Geology & Quaternary Geology > 2020 > 40(3): 206-213

Next Article Previous Article

SHUAI Qingwei, XU Yunxia, WEN Pengfei, SHA Zhibin, WAN Xiaoming. Application of non-linear tomography technology to gas hydrate imaging in the Qiongdongnan area[J]. Marine Geology & Quaternary Geology, 2020, 40(3): 206-213. doi: 10.16562/j.cnki.0256-1492.2020040301

Citation:

SHUAI Qingwei, XU Yunxia, WEN Pengfei, SHA Zhibin, WAN Xiaoming. Application of non-linear tomography technology to gas hydrate imaging in the Qiongdongnan area[J]. Marine Geology & Quaternary Geology, 2020, 40(3): 206-213. doi: 10.16562/j.cnki.0256-1492.2020040301

Application of non-linear tomography technology to gas hydrate imaging in the Qiongdongnan area

1.
Key Laboratory of Mineral Resources, Ministry of Natural Resources, Guangzhou 510075, China
2.
Guangzhou Marine Geological Survey, China Geology Survey, Guangzhou 510760, China

Received Date: 03 April 2020

Revised Date: 17 April 2020

Publish Date: 25 June 2020

Abstract

Abstract

There are a substantial amount of gas-bearing sediments occurred in the Qiongdongnan area. Geophysical features, such as in-phase axial pulling down and velocity changes are commonly observed. Therefore, the images of sediments below the gas hydrate layer are always blurring. In this paper, a method based on non-linear tomographic depth offset is adopted to enhance the accuracy and resolution of imaging. The method of full 3D tomography inversion is used to establish the velocity model in depth domain, and the kinematic invariants are calculated by picking up the RMO of depth offset gathers and reverse deflection. Based on the mixed model under the constraints of skeleton information, such as horizons and inclination angles, kinematic invariants are used for velocity tomography to minimize RMO for model updating. This method can avoid multiple iteration PSDM processing while updating velocity and greatly improve the tomographic efficiency. Then the high precision velocity model can be obtained by making full use of the profile skeleton and inclination information. The effect of gas on stratigraphic formation is effectively eliminated in the practical application of hydrate data in the Qiongdongnan area, and high precision depth imaging results are obtained.
- Non-linear tomography /
- hybrid model /
- kinematic invariant /
- PSDM

FullText(HTML)

References

[1]	杨胜雄. 南海天然气水合物成藏理论[M]. 北京: 科学出版社, 2019: 2-3. Google Scholar YANG Shengxiong. Research on Gas Hydrate Accumulation in South China Sea[M]. Beijing: Science Press, 2019: 2-3. Google Scholar
[2]	龚跃华, 杨胜雄, 王宏斌, 等. 琼东南盆地天然气水合物成矿远景[J]. 吉林大学学报: 地球科学版, 2018, 48(4):1030-1042 Google Scholar GONG Yuehua, YANG Shengxiong, WANG Hongbin, et al. Prospect of gas hydrate resources in Qiong Dongnan basin [J]. Journal of Jilin University: Earth Science Edition, 2018, 48(4): 1030-1042. Google Scholar
[3]	张伟, 何家雄, 卢振权, 等. 琼东南盆地疑似泥底辟与天然气水合物成矿成藏关系初探[J]. 天然气地球科学, 2015, 26(11):2185-2197 doi: 10.11764/j.issn.1672-1926.2015.11.2185 CrossRef Google Scholar ZHANG Wei, HE Jiaxiong, LU Zhenquan, et al. Preliminary study of the relationship between the suspected mud Diapir and natural gas hydrate in the Qiongdongnan Basin, northern South China Sea [J]. Natural Gas Geoscience, 2015, 26(11): 2185-2197. doi: 10.11764/j.issn.1672-1926.2015.11.2185 CrossRef Google Scholar
[4]	刘杰, 杨睿, 张金华, 等. 琼东南盆地华光凹陷天然气水合物成藏条件及有利区带预测[J]. 海洋地质与第四纪地质, 2019, 39(1):134-142 Google Scholar LIU Jie, YANG Rui, ZHANG Jinhua, et al. Gas hydrate accumulation conditions in the Huaguang depression of Qiongdongnan basin and prediction of favorable zones [J]. Marine Geology & Quaternary Geology, 2019, 39(1): 134-142. Google Scholar
[5]	何家雄, 苏丕波, 陆振权, 等. 南海北部琼东南盆地天然气水合物气源及运聚成藏模式预测[J]. 天然气工业, 2015, 35(8):19-29 doi: 10.3787/j.issn.1000-0976.2015.08.003 CrossRef Google Scholar HE Jiaxiong, SU Pibo, LU Zhengquan, et al. Prediction of gas sources of natural gas hydrate in the Qiongdongnan basin, northern South China Sea, and its migration, accumulation and reservoir formation pattern [J]. Natural Gas Industry, 2015, 35(8): 19-29. doi: 10.3787/j.issn.1000-0976.2015.08.003 CrossRef Google Scholar
[6]	张伟. 南海北部主要盆地泥底辟/泥火山发育演化与油气及天然气水合物成矿成藏[D]. 中国科学院广州地球化学研究所博士学位论文, 2016. Google Scholar ZHANG Wei. Research on the development and evolution of mud diapir/mud volcano and their relationship with migration and accumulation of petroleum and natrural gas-hydrate in major basins, northern South China Sea[D]. Doctor Dissertation of Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, 2016. Google Scholar
[7]	Madariaga V F R. Non-linear reflection tomography [J]. Geophysical Journal International, 1988, 95(1): 135-147. doi: 10.1111/j.1365-246X.1988.tb00456.x CrossRef Google Scholar
[8]	Clapp R G, Biondi B, Claerbout J F. Incorporating geologic information into reflection tomography [J]. Geophysics, 2004, 69(2): 533-546. doi: 10.1190/1.1707073 CrossRef Google Scholar
[9]	Evans E, Papouin M, Abedi S, et al. Southern North Sea preSDM imaging using hybrid gridded tomography[C]//Proceedings of 2005 SEG Annual Meeting. Houston, Texas: Society of Exploration Geophysicists, 2005: 2530-2534. Google Scholar
[10]	Guillaume P, Reinier M, Lambaré G, et al. Dip constrained non-linear slope tomography[C]//Proceedings of 2013 SEG Annual Meeting. Houston, Texas: Society of Exploration Geophysicists, 2013. Google Scholar
[11]	王兆旗, 庄锡进, 李立胜, 等. 非线性层析反演速度建模技术[J]. CT理论与应用研究, 2017, 26(5):543-551 Google Scholar WANG Zhaoqi, ZHUANG Xijin, LI Lisheng, et al. Non-linear tomography inversion technology for velocity modeling [J]. CT Theory and Applications, 2017, 26(5): 543-551. Google Scholar
[12]	王兆旗, 李立胜, 叶月明, 等. 倾角约束的非线性层析反演速度建模技术[J]. 物探化探计算技术, 2018, 40(2):156-161 doi: 10.3969/j.issn.1001-1749.2018.02.03 CrossRef Google Scholar WANG Zhaoqi, LI Lisheng, YE Yueming, et al. Dip constrained non-linear tomography inversion technology for velocity modeling [J]. Computing Techniques for Geophysical and Geochemical Exploration, 2018, 40(2): 156-161. doi: 10.3969/j.issn.1001-1749.2018.02.03 CrossRef Google Scholar
[13]	Adler F, Baina R, Soudani M A, et al. Nonlinear 3D tomographic least-squares inversion of residual moveout in Kirchhoff prestack-depth-migration common-image gathers [J]. Geophysics, 2008, 73(5): VE13-VE23. doi: 10.1190/1.2956427 CrossRef Google Scholar
[14]	张凯, 李振春. 双复杂条件下层析速度反演方法研究[J]. 地球物理学进展, 2013, 28(6):3001-3006 doi: 10.6038/pg20130622 CrossRef Google Scholar ZHANG Kai, LI Zhenchun. Tomographic velocity inversion method with dual-complexity [J]. Progress in Geophysics, 2013, 28(6): 3001-3006. doi: 10.6038/pg20130622 CrossRef Google Scholar
[15]	李辉, 王华忠, 刘守伟. 基于高斯束的速度层析方法研究[J]. 石油物探, 2017, 56(1):116-125 doi: 10.3969/j.issn.1000-1441.2017.01.014 CrossRef Google Scholar LI Hui, WANG Huazhong, LIU Shouwei. A velocity tomography algorithm based on Gaussian beam [J]. Geophysical Prospecting for Petroleum, 2017, 56(1): 116-125. doi: 10.3969/j.issn.1000-1441.2017.01.014 CrossRef Google Scholar
[16]	欧阳甜子. 高斯束叠前深度偏移在普光气田的应用研究[J]. 非常规油气, 2018, 5(5):35-42 doi: 10.3969/j.issn.2095-8471.2018.05.006 CrossRef Google Scholar OUYANG Tianzi. Applied research on Gaussian beam prestack depth migration in Puguang gas field [J]. Unconventional Oil & Gas, 2018, 5(5): 35-42. doi: 10.3969/j.issn.2095-8471.2018.05.006 CrossRef Google Scholar
[17]	Jones I F, Sugrue M, Hardy P. Hybrid gridded tomography[C]//Proceedings of First Break. EAGE, 2007: 35-41. Google Scholar
[18]	Lambaré G, Guillaume P, Zhang X, et al. Multi-layer non-linear slope tomography[C]//Proceedings of 75th EAGE Conference & Exhibition incorporating SPE EUROPEC 2013. London: European Association of Geoscientists & Engineers, 2013. Google Scholar
[19]	Guillaume P, Hollingworth S, Zhang X M, et al. Multi-layer tomography and its application for improved depth imaging[C]//Proceedings of 2012 SEG Annual Meeting. Las Vegas, Nevada: Society of Exploration Geophysicists, 2012: 1-5. Google Scholar
[20]	肖艳玲, 范旭, 王晓涛, 等. 网格层析速度反演技术在齐古背斜叠前深度偏移中的应用[J]. 石油地球物理勘探, 2017, 52(S2):98-103 Google Scholar XIAO Yanling, FAN Xu, WANG Xiaotao, et al. Mesh tomographic velocity inversion for the prestack depth migration of the Qigu anticline [J]. Oil Geophysical Prospecting, 2017, 52(S2): 98-103. Google Scholar
[21]	潘兴祥, 秦宁, 曲志鹏, 等. 叠前深度偏移层析速度建模及应用[J]. 地球物理学进展, 2013, 28(6):3080-3085 doi: 10.6038/pg20130632 CrossRef Google Scholar PAN Xingxiang, QIN Ning, QU Zhipeng, et al. Tomography velocity modeling and application of prestack depth migration [J]. Progress in Geophysics, 2013, 28(6): 3080-3085. doi: 10.6038/pg20130632 CrossRef Google Scholar
[22]	王红丽. 南海复杂构造地震成像及其应用研究[D]. 中国科学院深海科学与工程研究所博士学位论文, 2018. Google Scholar WANG Hongli. Seismic imaging of complex structures and its application research in South China Sea[D]. Doctor Dissertation of Institute of Oceanology, Chinese Academy of Sciences, 2018. Google Scholar
[23]	杨振武. 海洋石油地震勘探[M]. 北京: 石油工业出版社, 2012: 126-124. Google Scholar YANG Zhenwu. Offshore Oil Seismic Exploration[M]. Beijing: Petroleum Industry Press, 2012: 121-126. Google Scholar