High-Resolution Fiber-Optic Sensing System for 4D Mapping, Detection, and Characterization, and Integrity Assessment of Legacy Wellbores for Carbon Storage
- Intelligent FIber Optic Systems Corporation (IFOS)
Purpose of the Research Underground carbon dioxide (CO2) storage is increasingly seen as one of the promising solutions in the efforts on mitigating the adverse effects of climate change due to greenhouse gas emissions. Subsurface CO2 is stored in a supercritical fluid state, which requires deep insertion into porous basement rocks. If the CO2 works its way towards the surface, into lower pressure areas, it can return to gaseous state and escape into the atmosphere. Therefore, prior to implementation of a major underground carbon storage project, it is imperative to determine and assess risks associated with both the detection and integrity of legacy wellbores of the target site, and if economically feasible, substantially mitigate these risks. The objective or this assessment is to determine if the site is suitable for reliable carbon storage, with negligible odds of CO2 leakage into the atmosphere. In this connection, it is important to identify “legacy wellbores” of target storage sites and assess their hydraulic, structural, and mechanical integrity. Conventional methods cannot reliably and satisfactorily detect “unknown legacy wellbores” and assess their integrity. To address this gap, DOE is seeking development of new advanced high resolution sensors, technologies, tools, and methods that enable detection of “legacy wellbores that lack a steel surface casing” (“undetectable legacy wellbores”), and/or assessment of “the integrity of legacy wells in which conventional logging tools cannot provide the needed information” ( “insufficiently documented legacy wellbores”), together with uncertainties of their integrity, including structural defects in the cement, casing, and plug. General Statement of How this Problem is Being Addressed In response to DOE’s needs, IFOS is developing an innovative and high-resolution fiber-optic (FO)-based 4D (spatial and temporal) quasi-distributed acoustic sensing (Q-DAS), detection, and imaging system – Well*SenseTM Q-DAS - that will enable detection of “undetectable legacy wellbores.” These high- resolution 4D images will be combined with artificial intelligence (AI) and machine learning (ML) algorithms, probability models, and data analytics to assess and quantify the uncertainties of the integrity of these legacy wellbores at high confidence levels, hence reducing costs associated with these risks. The Well*SenseTM Q-DAS platform provides an excellent dynamic range through IFOS’ innovative high signal-to-noise-ratio (SNR) architecture, advanced photonic sensors, and a verified measurement resolution equivalent to a pressure change of 0.00013 psi. Well*SenseTM Q-DAS is differentiated from Rayleigh scattering-based DAS (R-DAS) systems through its innovative use of multiplexed fiber Bragg grating (FBG) sensors configured in IFOS’ novel Q-DAS configuration, which reduces back-end data processing burden and eliminates the need for time averaging. The Well*SenseTM Q-DAS platform is ultimately envisioned to be a wireless and battery powered system, deployed in a special networked grid, both on the surface and sub-surface through a few wellbores, in combination with proven non-intrusive seismic techniques. It will complement conventional methods and will address their gaps. Research Carried Out: Phase I Results In Phase I, IFOS and University of Texas, Austin (UTA) demonstrated feasibility of proof-of-concept Well*SenseTM Q-DAS prototype sensing systems and collected experimental data. Modeling and simulation confirmed the benefits of IFOS’ AI/ML-enabled analytic approach to provide actionable information for carbon storage site selection. Phase I work included construction and benchtop and lab testing of Well*SenseTM Q-DAS, including the FBG sensors in a simulated carbon storage environment. Our proof-of-concept Well*SenseTM Q-DAS prototype had a large number of FBG sensors per FO Cable (66 sensors) and included IFOS’ innovative optoelectronic I*Sense® broadband FBG interrogator. Potential Applications of the Research IFOS’ Well*SenseTM Q-DAS system is a photonic distributed acoustic sensing (DAS) and imaging solution that will enable low-risk data-driven site selection for reliable underground CO2 storage by detecting “undetectable legacy wellbores”. In addition, it will enable assessing the integrity of the “undetectable and insufficiently documented legacy wellbores”. IFOS’ solution will increase the reliability and safety of carbon storage sites, which can reduce investment risks and deliver significant cost and time savings. After site selection, Well*SenseTM Q-DAS could be adapted and used to monitor the site, which will maximize asset utilization and return on the investment. Leveraging IFOS’ advanced photonic sensors, photonic-spectral-processing (PSP) and high-performance Photonic Integrated Circuit (PIC)-based optoelectronic wide-band interrogator technology, Well*SenseTM Q-DAS will culminate in a reliable, high accuracy, cost-effective, robust, scalable, and high-speed distributed acoustic sensing system. The system will have numerous spin-off applications in traditional oil & gas and geothermal industries.
- Research Organization:
- Intelligent Fiber Optic Systems Corporation (IFOS)
- Sponsoring Organization:
- USDOE Office of Fossil Energy (FE), Clean Coal and Carbon Management
- DOE Contract Number:
- DE-SC0021778
- OSTI ID:
- 2228333
- Type / Phase:
- SBIR (Phase I)
- Report Number(s):
- IFOS-Carbon-Storage-I-FR
- Country of Publication:
- United States
- Language:
- English
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