Abstract

In the process of oil and gas exploration and development, carbon isotope ratio can reflect the maturity of oil and gas and predict the recovery factor, and the isotope ratio in the composition of shale gas is particularly important. Thus, a carbon isotope spectrum logging system was designed and exploited based on tunable diode laser absorption spectroscopy (TDLAS) technology under the fundamental frequency absorption band of 12CO2 and 13CO2 molecules, and a quantum cascade laser (QCL) with center wavelength of 4.35 μm was applied. For further detection sensitivity, wavelength modulation spectroscopy (WMS) technology was combined to suppress background noise through the modulation of QCL. A multi-pass gas cell (MPGC) with an optical path length of 41 m was utilized for lower limit of detection (LoD). In order to suppress the temperature dependence of the absorption spectrum, the optical subsystem was placed in a high-precision thermostat to maintain a stable temperature, so as to achieve high-precision and high-stability detection. Meanwhile, sparrow search algorithm-back propagation (SSA-BP) was applied for concentration prediction of 12CO2 and 13CO2. Taking advantage of the excellent optimization ability, fast convergence speed and high stability of SSA, the problem that BP neural network algorithm is highly dependent on initial value can be solved to some extent. Sensor performance was validated through calibration and stability experiments. The LoD of 12CO2 reached a minimum of 0.618 parts-per-billion (ppb) with an 88 s averaging time, and the LoD of 13CO2 reached 0.181 ppb when the averaging time was 96 s. Besides, the standard deviation of carbon isotope ratio obtained by this system was ∼ 0.61 ‰. The results illustrate that this self-developed sensor has a bright prospect in the field of shale gas isotope detection.

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