A Holistic Approach to Data Interpretation Combines the Strengths of Ultra-Deep Electromagnetic Tools with Shallow Logging While Drilling Data to Improve Reservoir Understanding

K. Riofrio, N. Clegg, L. Rawsthorne, S. Kolsto, J. Mouatt, A. Bang, A. Chatterjee
{"title":"A Holistic Approach to Data Interpretation Combines the Strengths of Ultra-Deep Electromagnetic Tools with Shallow Logging While Drilling Data to Improve Reservoir Understanding","authors":"K. Riofrio, N. Clegg, L. Rawsthorne, S. Kolsto, J. Mouatt, A. Bang, A. Chatterjee","doi":"10.2118/215519-ms","DOIUrl":null,"url":null,"abstract":"\n Understanding the geological setting and architecture in which a well is drilled is key to achieving optimal well placement, enhancing reservoir production and for future reservoir exploitation with the planning of additional wells. The planning of production wells is accomplished using different data sets with different resolutions, but understanding the subsurface geology is key to linking the data sources. During drilling operations LWD tools, which have greater resolution than seismic, are deployed to aid in decision making and optimise well placement. Focusing on the data sources in isolation can lead to successful wells, but placing this data in a geological context allows for more sophisticated decision making and leads to greater reservoir understanding for improved reservoir exploitation.\n Key to linking the near wellbore measurements with the geological models derived from seismic interpretation are ultra-deep electromagnetic (EM) tools. Applying geophysical inversion processes to the ultra-deep resistivity data generates models that enhance the reservoir interpretation. Formation boundary identification and definition of thin layers in the vertical plane can be achieved with 1D EM inversion. Combining these results with a Gauss-Newton-based 3D inversion provides better identification of the reservoir lateral variability. Recently the introduction of inverting the 3D EM inversion for anisotropy as well as resistivity, permits the identification of isotropic and anisotropic intervals allowing lithological and fluid identification at greater distances from the borehole. The geological models derived from the inversion data can provide a good representation of the subsurface but are more useful for decision making when correlated with other LWD data and azimuthal images, for example density and gamma ray. These tools have a much shallower range of detection but provide more detail which can be critical when placed in its geological context.\n Combining all available technologies to improve reservoir understanding of different depositional environments is a more effective approach. Interpretation of the 1D, 3D and 3D anisotropy inversions both allows identification of complex oil water contacts which is vital for hydrocarbon reserves calculation and in certain environments, identification of intra-reservoir thin shale layers that can act as a baffle of fluid movement. Refining these models with the information available from density/neutron, gamma and deep EM data provides a greater level of detail which can also play an important role in the completion design process.\n The improved reservoir understanding derived when combining the interpretation of these diverse methodologies can provide a better understanding of the geological scenarios and allows the identification of elements that play a role in well and field production. Identifying these trends during the drilling operations allows for both optimization of the well placement and completion installation. Further analysis post well allows improved reservoir exploitation and planning of new wells.","PeriodicalId":178397,"journal":{"name":"Day 4 Fri, September 08, 2023","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 4 Fri, September 08, 2023","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/215519-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Understanding the geological setting and architecture in which a well is drilled is key to achieving optimal well placement, enhancing reservoir production and for future reservoir exploitation with the planning of additional wells. The planning of production wells is accomplished using different data sets with different resolutions, but understanding the subsurface geology is key to linking the data sources. During drilling operations LWD tools, which have greater resolution than seismic, are deployed to aid in decision making and optimise well placement. Focusing on the data sources in isolation can lead to successful wells, but placing this data in a geological context allows for more sophisticated decision making and leads to greater reservoir understanding for improved reservoir exploitation. Key to linking the near wellbore measurements with the geological models derived from seismic interpretation are ultra-deep electromagnetic (EM) tools. Applying geophysical inversion processes to the ultra-deep resistivity data generates models that enhance the reservoir interpretation. Formation boundary identification and definition of thin layers in the vertical plane can be achieved with 1D EM inversion. Combining these results with a Gauss-Newton-based 3D inversion provides better identification of the reservoir lateral variability. Recently the introduction of inverting the 3D EM inversion for anisotropy as well as resistivity, permits the identification of isotropic and anisotropic intervals allowing lithological and fluid identification at greater distances from the borehole. The geological models derived from the inversion data can provide a good representation of the subsurface but are more useful for decision making when correlated with other LWD data and azimuthal images, for example density and gamma ray. These tools have a much shallower range of detection but provide more detail which can be critical when placed in its geological context. Combining all available technologies to improve reservoir understanding of different depositional environments is a more effective approach. Interpretation of the 1D, 3D and 3D anisotropy inversions both allows identification of complex oil water contacts which is vital for hydrocarbon reserves calculation and in certain environments, identification of intra-reservoir thin shale layers that can act as a baffle of fluid movement. Refining these models with the information available from density/neutron, gamma and deep EM data provides a greater level of detail which can also play an important role in the completion design process. The improved reservoir understanding derived when combining the interpretation of these diverse methodologies can provide a better understanding of the geological scenarios and allows the identification of elements that play a role in well and field production. Identifying these trends during the drilling operations allows for both optimization of the well placement and completion installation. Further analysis post well allows improved reservoir exploitation and planning of new wells.
一种全面的数据解释方法将超深电磁工具的优势与浅层随钻测井数据相结合,以提高对储层的理解
了解井的地质环境和结构是实现最佳井位、提高油藏产量和未来油藏开发计划的关键。生产井的规划是使用不同分辨率的数据集完成的,但了解地下地质是连接数据源的关键。在钻井作业中,随钻测井工具的分辨率比地震测井工具更高,可用于辅助决策和优化井位。专注于孤立的数据源可以带来成功的井,但将这些数据放在地质环境中可以做出更复杂的决策,并有助于更好地了解储层,从而提高储层的开发效率。超深电磁(EM)工具是将近井测量与地震解释得出的地质模型联系起来的关键。将地球物理反演过程应用于超深电阻率数据,可以生成增强储层解释的模型。利用一维电磁反演可以实现垂直平面上薄层的地层边界识别和定义。将这些结果与基于高斯-牛顿的三维反演相结合,可以更好地识别储层横向变异性。最近,引入了反演各向异性和电阻率的三维电磁反演技术,可以识别各向同性和各向异性区间,从而在距离井眼更远的地方进行岩性和流体识别。由反演数据导出的地质模型可以很好地反映地下情况,但当与其他随钻测井数据和方位角图像(如密度和伽马射线)相关联时,对决策更有用。这些工具的探测范围要小得多,但可以提供更多的细节,这在地质环境中是至关重要的。结合所有可用的技术来提高对不同沉积环境的储层认识是更有效的方法。对1D、3D和3D各向异性反演的解释都可以识别复杂的油水界面,这对油气储量计算至关重要,在某些环境下,还可以识别储层内薄页岩层,后者可能会阻碍流体运动。利用密度/中子、伽马和深部电磁数据提供的信息来完善这些模型,可以提供更高层次的细节,这些细节在完井设计过程中也发挥着重要作用。结合这些不同方法的解释,提高了对储层的认识,可以更好地了解地质情况,并可以识别在油井和油田生产中起作用的因素。在钻井作业中识别这些趋势,可以优化井位和完井装置。井后进一步分析可以改进油藏开发和新井规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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:604180095
Book学术官方微信