Abstract:Because of the key software architecture requirements of middleware in the field of geological intelligence in big data, big computing, and big models, this paper designs and implements a new petroleum valuation distributed file system (PetroV DFS).PetroV DFS adopts a two-level data storage mechanism including local spatial database storage under ST-based KIDA metadata modeling and distributed data chunk file storage based on geographic meshing and geological information coding.The storage kinds of distributed chunk file include spatial index chunk for basin-level geological mapping (two-dimensional digital cores), octree branch chunk for three-dimensional volume data (seismic data, three-dimensional digital cores), and spatial key-value pairs for conventional, imaging log data storage.Following the geographical mesh subdivision algorithm, PetroV DFS supports the storage of different data types from the global geographic scale to single well or even smaller scales, and there is no upper allocation limits on the number of data chunk files.Especially, if there are no any constraints in the case of scale-out inexpensive servers from different regions (e.g., different local data center), it is no upper limits on the amount of data stored.PetroV DFS ensures that "geographically close and storage location close", namely, data from the same geographic area are stored in the same rack of the same data center.For the segmentation of 440G prestack seismic data files and the calculation of the full-time frequency-amplitude attributes, the generic programming of PetroV DFS can be effectively deployed on the commodity computers, and gets almost the same calculation effects preserved ever by high-performance computers in addition to significantly improving the professional data management.
盛秀杰, 金之钧, 彭成, 景妍. PetroV分布式文件系统的设计与实现[J]. 石油地球物理勘探, 2019, 54(3): 641-649.
SHENG Xiujie, JIN Zhijun, PENG Cheng, JING Yan. Design and implementation of the PetroV distributed file system based on geographic meshing and geological information coding. Oil Geophysical Prospecting, 2019, 54(3): 641-649.
盛秀杰, 金之钧, 彭成, 等.PetroV软件架构设计中的一些思考与实现[J].石油地球物理勘探, 2015, 50(4):766-774.SHENG Xiujie, JIN Zhijun, PENG Cheng, et al.Some ideas in PetroV architecture design and development[J].Oil Geophysical Prospecting, 2015, 50(4):766-774.
[2]
盛秀杰, 金之钧, 彭成, 等.PetroV分布式数据存储与分析框架设计[J].石油地球物理勘探, 2017, 52(4):875-883.SHENG Xiujie, JIN Zhijun, PENG Cheng, et al.The design of distributed data storage and analytics framework of PetroV[J].Oil Geophysical Prospecting, 2017, 52(4):875-883.
[3]
孟小峰, 慈祥.大数据管理:概念、技术与挑战[J].计算机研究与发展, 2013, 50(1):146-164.MENG Xiaofeng, CI Xiang.Big data management:Concepts, techniques and challenges[J].Journal of Computer Research and Development, 2013, 50(1):146-164.
[4]
赵长海, 晏海华, 王宏琳, 等.面向地震数据处理的并行与分布式编程框架[J].石油地球物理勘探, 2010, 45(1):147-152.ZHAO Changhai, YAN Haihua, WANG Honglin, et al.Seismic data processing oriented parallel and distributed programming framework[J].Oil Geophysical Prospecting, 2010, 45(1):147-152.
[5]
王珊, 萨师煊.数据库系统概论(第4版)[M].北京:高等教育出版社, 2005.WANG Shan, SA Shixuan.Database System Concepts(4th)[M].Higher Education Press, Beijing, 2005.
[6]
McKusick K, Quinlan S.GFS:Evolution on fast-forward[J].Communication of the ACM, 2010, 53(3):42-49.
[7]
Dean J and Ghemawat S.Map reduce:simplified data processing on large clusters[J].Communication of the ACM, 2008, 51(3):107-113.
[8]
王宏琳, 罗国安.国产地震处理解释软件的发展[J].石油地球物理勘探, 2013, 48(2):325-331.WANG Honglin, LUO Guoan.Seismic data processing and interpretation software progress in China[J].Oil Geophysical Prospecting, 2013, 48(2):325-331.
[9]
熊翥.我国物探技术的进步及展望[J].石油地球物理勘探, 2003, 38(5):565-578.XIONG Zhu. Progress and prospect of geophysical prospecting technology in China[J].Oil Geophysical Prospecting, 2003, 38(5):565-578.
[10]
Brewer E A. Towards robust distributed systems[J].Proceedings of the Nineteenth Annual ACM Symposium on Principles of Distributed Computing, New York, 2000.
[11]
成景旺, 毛宁波, 吕晓春, 等.非分裂完全匹配层边界存储时间域全波形反演[J].石油地球物理勘探, 2018, 53(4):754-764.CHENG Jingwang, MAO Ningbo, LYU Xiaochun, et al.Time-domain full waveform inversion with CFS-NPML boundary storage[J].Oil Geophysical Prospecting, 2018, 53(4):754-764.
[12]
邓世广, 王淑艳, 赵文津, 等.基于OpenMP并行计算的匹配追踪时频分析方法[J].石油地球物理勘探, 2018, 53(3):454-461.DENG Shiguang, WANG Shuyan, ZHAO Wenjin, et al.A matching pursuit time-frequency analysis me-thod based on OpenMP parallel computing[J].Oil Geophysical Prospecting, 2018, 53(3):454-461.
[13]
亢永敢, 赵改善, 魏嘉, 等.基于Hadoop的Kirchhoff叠前时间偏移并行算法[J].石油地球物理勘探, 2015, 50(6):1213-1218.KANG Yonggan, ZHAO Gaishan, WEI Jia, et al.Pa-rallel algorithms of Kirchhoff prestack time migration based on Hadoop[J].Oil Geophysical Prospecting, 2015, 50(6):1213-1218.
[14]
张丰麒, 金之钧, 盛秀杰, 等.贝叶斯三参数低频软约束同步反演[J].石油地球物理勘探, 2016, 51(5):965-975.ZHANG Fengqi, JIN Zhijun, SHENG Xiujie, et al.Bayesian prestack three-term inversion with soft Low-frequence constraint[J].Oil Geophysical Prospecting, 2016, 51(5):965-975.
[15]
张丰麒, 金之钧, 盛秀杰, 等.基于低频软约束的叠前AVA稀疏层反演[J].石油地球物理勘探, 2017, 52(4):770-782.ZHANG Fengqi, JIN Zhijun, SHENG Xiujie, et al.AVA sparse layer inversion with the soft-low frequency constraint[J].Oil Geophysical Prospecting, 2017, 52(4):770-782.
张丰麒, 金之钧, 盛秀杰, 等.基于基追踪-BI_Zoeppritz方程广义线性脆性指数直接反演方法[J].地球物理学报, 2017, 60(10):3954-3968.ZHANG Fengqi, JIN Zhijun, SHENG Xiujie, et al.A direct inversion for brittleness index based on GLI with basic-pursuit decomposition[J].Chinese Journal of Geophysics, 2017, 60(10):3954-3968.