Horizontal-Steam-Injection-Flow Profiling Using Fiber Optics
- Mahdy Shirdel (Chevron) | Richard S. Buell (Chevron) | Mike J. Wells (Chevron) | Cece Muharam (Chevron) | Jackie C. Sims (Chevron)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- April 2019
- Document Type
- Journal Paper
- 431 - 451
- 2019.Society of Petroleum Engineers
- Horizontal Well, Distributed Temperature Sensing, Fiber Optics, Steam Injection, Distributed Acoustic Sensing
- 28 in the last 30 days
- 139 since 2007
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Steam-conformance control in horizontal injectors is important for efficient reservoir-heat management in heavy-oil fields. Suboptimal conformance and nonuniform heating of the reservoir can substantially affect the economics of the field development and oil-production response and result in nonuniform steam breakthrough. To achieve the required control, it is essential to have an appropriate well-completion architecture and robust surveillance.
Five fiber-optic systems, each with a unique steam-conformance-control-completion configuration, have been installed in two horizontal steam injectors to help mature steam-injection-flow profiling and conformance-control solutions. These fiber-optic systems have used custom-designed fiber-optic bundles of multimode and single-mode fibers for distributed-temperature sensing (DTS) and distributed-acoustic sensing (DAS), respectively. Fiber-optic systems were also installed in a steam-injection-test-flow loop. All the optical fibers successfully acquired data in the wells and flow loop, measuring temperature and acoustic energy.
A portfolio of algorithms and signal-processing techniques was developed to interpret the DTS and DAS data for quantitative steam-injection-flow profiling. The heavily instrumented flow-loop environment was used to characterize DTS and DAS response in a design-of-experiment (DOE) matrix to improve the flow-profiling algorithms. These algorithms are dependent on independent physical principles derived from multiphase flow, thermal hydraulic models, acoustic effects, large-data-array processing, and combinations of these methods for both transient and steady-state steam flow. A high-confidence flow profile is computed using the convergence of the algorithms. The flow-profiling-algorithm results were further validated using 11 short-offset injector observation wells wells in the reservoir that confirmed steam movement near the injectors.
|File Size||2 MB||Number of Pages||21|
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