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2 2023

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A refractive index sensor based on micro-nano fiber with chirped fiber Bragg grating embedded for a microfluidic chip

Xie Zhanwu, Yan Haitao, Li Pengfei

Optica Applicata

2023

Vol. 53, nr 4

633--642

A refractive index (RI) sensor based on micro-nano fiber (MN-fiber) with chirped fiber Bragg grating (CFBG) Fabry–Perot cavity (FP-cavity) for a microfluidic chip has been proposed. A single-mode fiber is drawn by hydrogen flame heading come into MN-fiber. Two CFBGs are written into this MN-fiber by the ultraviolet (UV) laser mask exposure method. One is at the tapered region, another is at the micro-nano region. Then a micro-nano fiber with chirped fiber Bragg grating (MN-CFBGs) FP-cavity sensor is formed. The Bragg reflection wavelengths of two CFBGs are 1620 nm, 3-dB bandwidth are above 50 nm. The reflectance of two CFBGs are 70% and 99%, respectively. The effects of reflectivity and bandwidth of the CFBGs FP-cavity, diameter and length of MN-fiber with this sensor’s optical properties are analysed is and discussed. This sensor is embedded in a microfluidic chip and the MN-fiber region is immersion microfluid in different channels. The experimental results show that refractive index sensitivity of the sensor is –986 nm/refractive index unit (RIU), and the signal of the sensor has little noise. The CFBG-FP sensor not only has high sensitivity and lager measurement range, but also high contrast resonance signal and stability.

Combining the synchrosqueezing generalized S-transform of variational mode decomposition with the Teager-Kaiser energy operator to calculate the attenuation gradient for identifying oil and gas reservoirs

Yan Haitao, Zhou Huailai, Wang Yuanjun, Wu Nanke, Zhou Wei, Zhou Jie

Acta Geophysica

2023

Vol. 71, no. 2

795--812

Because of the limited resolution of conventional time–frequency analysis algorithms, they are also limited to calculate attenuation gradients that describe oil and gas reservoirs. We propose an advanced method for calculating the attenuation gradient that combines the synchrosqueezing generalized S-transform of variational mode decomposition with the Teager–Kaiser energy operator. SSVGST takes advantage of the synchrosqueezing generalized S-transform to focus the longitudinal resolution of the time–frequency domain and variational mode decomposition for adaptive signal segmentation in the frequency domain. Thus, SSVGST can be used to improve the time–frequency resolution of seismic signals, and the Teager–Kaiser energy operator is used to enhance the extracted attenuation gradient and highlight oil and gas regions effectively. The time–frequency focusing ability of SSVGST was verified by using a synthetic signal and theoretical model. Experimental results with the model and field data showed that the combination of SSVGST with the Teager–Kaiser energy operator suppressed the fuzzy energy caused by the low resolution of conventional time–frequency analysis algorithms and could locate reservoirs accurately and effectively.