Collaborative Web Based Platform for 3D Reservoir Characterization and Geosteering Planning on the Cloud

G. Santoso, J. Denichou, W. Al-Alqum, M. Zeidan, Mohammed Satti
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Abstract

New developments in Machine Learning and Artificial Intelligence-based interpretations are bringing a step change in the integration of multi-physic evaluations and management of reservoirs in real time. But it also requires game-changing digital developments to deliver the larger computing power required and to facilitate their access to multi-disciplinary (and sometime not co-located) team of experts and decision makers. This communication is sharing our experience of a web-based collaborative platform integrating operator's application used to produce realistic geological models and a service company's advance multi-dimension modeling and inversion supporting latest Logging While Drilling formation evaluation workflows. The system is now routinely used in case studies, allowing users to perform pre-job well placement feasibility analysis and post-job model refinement. The technology behind is a modular Web platform that hides all the complexity of the modeling and inversions algorithms. Users can; Upload their data to the application's virtual file system. Visualize 2D and 3D models, Launch modeling jobs for Ultra-Deep Azimuthal Resistivity (UDAR) and conventional formation evaluation measurements and finally monitor the inverted images unfold as the job progresses, all in the web browser. The system enables multiple users to view and edit the shared models and observe and control the same job in a collaborative way. The simulation codes are run on the remote clusters or on the cloud. We will present the application of platform and models for 3D characterization in Norwegian continental shelf wells. The examples illustrate mapping of 2D and 3D structural complexity and how the system is used to update reservoir geomodels. The platform is also used to identify optimal well position; define geosteering strategies in the pre-job planning phase, as well as to evaluate sensitivities, depth of investigation in specific scenarios and to analyze how the structural model uncertainties may be affecting the interpretation. Modeling and inversion are used to assess how structural complexities, lithological changes, oil-water contacts and saturation could be encounter in simulating future production. It is a key for quantitative robust interpretation and geomodels update. The platform allows fast deployment of latest research modeling and inversion prototypes. We finally present the latest results of full 3D modeling and various flavors of 2D imaging inversion results from multiple wells, visualized in the browser using a 3D viewer. The new digital solution improves understanding of 3D reservoir structure and fluid distribution around the wellbore.
基于协同网络的云上三维储层表征和地质导向规划平台
机器学习和基于人工智能的解释技术的新发展,为实时整合多物理体评价和油藏管理带来了重大变化。但这也需要改变游戏规则的数字发展,以提供所需的更大计算能力,并促进他们与多学科(有时不是在同一地点)的专家和决策者团队的联系。此次交流分享了我们在基于网络的协作平台上的经验,该平台集成了运营商用于生成真实地质模型的应用程序和服务公司先进的多维建模和反演技术,支持最新的随钻测井地层评价工作流程。该系统现在经常用于案例研究,允许用户进行作业前的可行性分析和作业后的模型优化。背后的技术是一个模块化的Web平台,它隐藏了建模和反转算法的所有复杂性。用户可以;将他们的数据上传到应用程序的虚拟文件系统。可视化2D和3D模型,启动超深方位角电阻率(UDAR)和常规地层评价测量的建模作业,并随着作业的进行监控反转图像的展开,所有这些都可以在web浏览器中进行。该系统允许多个用户以协作的方式查看和编辑共享模型,并对同一作业进行观察和控制。仿真代码在远程集群或云中运行。我们将介绍3D表征平台和模型在挪威大陆架井中的应用。示例说明了2D和3D结构复杂性的映射,以及如何使用该系统更新油藏地质模型。该平台还用于识别最佳井位;在作业前规划阶段确定地质导向策略,评估敏感性,在特定情况下的调查深度,并分析结构模型的不确定性如何影响解释。建模和反演用于评估在模拟未来生产时可能遇到的结构复杂性、岩性变化、油水接触面和饱和度。它是定量稳健解释和地质模型更新的关键。该平台允许快速部署最新的研究建模和反演原型。最后,我们展示了全3D建模的最新结果,以及来自多口井的各种2D成像反演结果,并使用3D查看器在浏览器中可视化。新的数字解决方案提高了对三维油藏结构和井筒周围流体分布的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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