超大型卢拉油田储层特征地质统计反演面临的挑战与对策

E. Kneller, L. Teixeira, B. Hak, N. Cruz, Teresa Oliveira, J. M. Cruz, R. Cunha
{"title":"超大型卢拉油田储层特征地质统计反演面临的挑战与对策","authors":"E. Kneller, L. Teixeira, B. Hak, N. Cruz, Teresa Oliveira, J. M. Cruz, R. Cunha","doi":"10.3997/2214-4609.201902176","DOIUrl":null,"url":null,"abstract":"Summary The creation of reservoir model properties has become an art of bringing together hard and soft data, gathering ideas of geologists and geophysicists, constraining them with measured values in- and outside wells. Through lifecycle of the oil field the information coverage is growing - new wells are being drilled, new seismic acquisitions are performed, and new geological concepts are developed. The Brazilian pre-salt fields are no exception. However, these fields experience additional challenges, where the carbonates show significant lateral and vertical variability and the salt layer limits illumination and penetration of the seismic signal. In this paper, we investigate performance of three techniques on the Lula field: simulation, which \"propagates\" properties between wells; deterministic inversion, which transforms seismic amplitudes into elastic properties; and geostatistical inversion, which combines simulation and seismic-driven inversion. We demonstrate that geostatistical inversion brings together the best of both techniques and helps address the challenges of characterization of pre-salt carbonates.","PeriodicalId":186806,"journal":{"name":"Petroleum Geostatistics 2019","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Challenges and Solutions of Geostatistical Inversion for Reservoir Characterization of the Supergiant Lula Field\",\"authors\":\"E. Kneller, L. Teixeira, B. Hak, N. Cruz, Teresa Oliveira, J. M. Cruz, R. Cunha\",\"doi\":\"10.3997/2214-4609.201902176\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary The creation of reservoir model properties has become an art of bringing together hard and soft data, gathering ideas of geologists and geophysicists, constraining them with measured values in- and outside wells. Through lifecycle of the oil field the information coverage is growing - new wells are being drilled, new seismic acquisitions are performed, and new geological concepts are developed. The Brazilian pre-salt fields are no exception. However, these fields experience additional challenges, where the carbonates show significant lateral and vertical variability and the salt layer limits illumination and penetration of the seismic signal. In this paper, we investigate performance of three techniques on the Lula field: simulation, which \\\"propagates\\\" properties between wells; deterministic inversion, which transforms seismic amplitudes into elastic properties; and geostatistical inversion, which combines simulation and seismic-driven inversion. We demonstrate that geostatistical inversion brings together the best of both techniques and helps address the challenges of characterization of pre-salt carbonates.\",\"PeriodicalId\":186806,\"journal\":{\"name\":\"Petroleum Geostatistics 2019\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Petroleum Geostatistics 2019\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3997/2214-4609.201902176\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Petroleum Geostatistics 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3997/2214-4609.201902176","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

储层模型属性的创建已经成为一门艺术,它将硬数据和软数据结合在一起,收集地质学家和地球物理学家的想法,并用井内和井外的测量值来限制它们。在油田的整个生命周期中,信息覆盖范围不断扩大——新井正在钻探,新的地震采集正在进行,新的地质概念正在发展。巴西盐下油田也不例外。然而,这些油田面临着额外的挑战,其中碳酸盐岩显示出显著的横向和垂直变化,盐层限制了地震信号的照明和穿透。在本文中,我们研究了三种技术在卢拉油田的性能:模拟,它在井之间“传播”属性;确定性反演,将地震振幅转化为弹性性质;地质统计反演,将模拟与地震驱动反演相结合。我们证明,地质统计反演结合了这两种技术的优点,有助于解决盐下碳酸盐岩表征的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges and Solutions of Geostatistical Inversion for Reservoir Characterization of the Supergiant Lula Field
Summary The creation of reservoir model properties has become an art of bringing together hard and soft data, gathering ideas of geologists and geophysicists, constraining them with measured values in- and outside wells. Through lifecycle of the oil field the information coverage is growing - new wells are being drilled, new seismic acquisitions are performed, and new geological concepts are developed. The Brazilian pre-salt fields are no exception. However, these fields experience additional challenges, where the carbonates show significant lateral and vertical variability and the salt layer limits illumination and penetration of the seismic signal. In this paper, we investigate performance of three techniques on the Lula field: simulation, which "propagates" properties between wells; deterministic inversion, which transforms seismic amplitudes into elastic properties; and geostatistical inversion, which combines simulation and seismic-driven inversion. We demonstrate that geostatistical inversion brings together the best of both techniques and helps address the challenges of characterization of pre-salt carbonates.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信