Recent Advances in Downhole Fiber Optics Modeling & Analytics: Case Studies

Abstract In recent years, the upstream oil and gas industry has witnessed significant breakthroughs in developing and deploying permanent, on-demand, and distributed temperature (DTS) and acoustic (DAS) fiber-optic monitoring systems to optimize well completions and enhance production. Beyond steady advances in hardware, challenges associated with the analysis of distributed optical data are being addressed to enable delivery of value-driven answer solutions and services. Such solutions are often nontrivial and must be driven by scientific workflows in which data-driven models, advanced analytics and most importantly, physics-based models are applied at the right scale to correlate the data to downhole events. In this study, we present a methodology for integrating state-of-the-art intelligent completion and production tools together with a robust modeling and analytics framework for the efficient development of data interpretation services for complex downhole environments. The answer product platform discussed is built on fast computational models, robust data-driven analytics, cloud-based data streaming and management services, and real-time reporting delivery systems. Several case-studies demonstrate how our fiber-optics solutions and analysis are leveraged for applications such as leak detection, fluid injection profiling, acid placement, sand detection, and water ingress. For each case-history, we discuss the operational workflow for the downhole intelligent assembly, procedures for acquiring high-resolution DTS/DAS data, and the use of advanced fast physics or data driven models used to deliver the solution. Some of the application examples (e.g. water ingress and sand detection) also demonstrate how simultaneous measurements of DTS and DAS data are often critical to detecting and devising a strategy for mitigating well-specific issues. The case-studies presented in this study demonstrate how vast amounts of data can be acquired by fiber-optic interrogation systems and subsequently interpreted in real-time, or near real-time. Such a process is enabling oil and gas operators to make data-driven decisions that drive optimized reservoir performance and proactively mitigate operational risk such as NPT due to equipment failure.