Cheng Guo

Deep-well radar telemetry over ultra-long cables suffers from strong frequency-selective attenuation and impedance drift under high temperature and pressure. We have proposed a channel-adaptive “communication + acquisition” architecture for a 7500 m borehole radar system. The scheme integrates spread-spectrum time domain reflectometry (SSTDR; m-sequence with BPSK) to monitor the cable in situ, identify termination/cable impedance, and adaptively match the load, thereby reducing reflection-induced loss. On the receiving side, we combine time domain adaptive equalization—implemented as an LMS-driven FIR filter—with frequency domain OFDM equalization based on least-squares (LS) channel estimation, enabling constellation recovery and robust demodulation over the distorted channel. The full processing chain is realized in real time on a Xilinx Artix-7 (XC7A100T) FPGA with module-level reuse and pre-stored training sequences for efficient hardware scheduling. In a field deployment in the Shunbei area at 7500 m depth, radar results show high agreement with third-party geological logs: the GR-curve correlation reaches 0.92, the casing reflector at ~7250 m is clearly reproduced, and the key bottom depth error is 0.013%. These results verify that the proposed system maintains stable communication and accurate imaging in harsh deep-well environments while remaining compact and implementable on cost-effective hardware.

Push–pull switch-mode power supplies are widely employed due to their high efficiency and power density. However, traditional designs typically depend on multiple auxiliary circuits to achieve functions such as power-up control, voltage regulation, and system protection, resulting in structural complexity and difficulty in debugging. Additionally, dual-power high-voltage amplifier systems often suffer from voltage deviations caused by supply imbalances or load fluctuations, potentially leading to equipment failure and significant economic losses. To overcome these limitations, we propose a novel digital signal-controlled push–pull driver power supply topology in this paper. Specifically, this design utilizes digital pulse-width modulation (PWM) signals to control multi-stage metal-oxide-semiconductor field-effect transistors (MOSFETs), incorporating adjustable duty-cycle drives, multi-channel current sensing, and fault protection mechanisms. Experimental validation was performed on a ±220 V, 20 kHz, 180 W power supply prototype. The results demonstrate excellent performance, notably enhancing stability and reliability in dual-side synchronous power supply scenarios. Thus, this digital-control topology effectively addresses the drawbacks of conventional push–pull designs and offers potential applications in nondestructive testing and high-voltage driving systems.

This paper presents the world’s first radar detection experiment conducted in a 7500-m ultra-deep well. By applying ground-penetrating radar technology to petroleum logging, the developed borehole radar system successfully achieved stratigraphic information detection in the 7200–7500 m section of Shunbei Well No. 2. Utilizing electromagnetic wave reflection principles, the system acquires echo signals carrying medium characteristics through transmit–receive antenna arrays coupled with field-programmable gate array (FPGA)-based high-speed acquisition for real-time downhole data transmission. Experimental results demonstrate high consistency in Gamma Ray (GR) curves (correlation coefficient: 0.92) between radar data and Sinopec’s geological drilling data, particularly in key stratigraphic features such as casing reflections at a 7250-m depth (error of 0.013%). This breakthrough validates the operational stability and detection accuracy of borehole radar in complex subsurface environments, providing an innovative technological approach for ultra-deep hydrocarbon exploration.

To address the significant impact of noise on the target detection performance of borehole radar (BHR), a key type of ground-penetrating radar (GPR), a denoising scheme based on the whale optimization algorithm (WOA) for adaptive variational mode decomposition (VMD) and multiscale principal component analysis (MSPCA) is proposed. This study initially conducts the modal decomposition of BHR data using an improved adaptive VMD method based on the WOA; it then automatically selects modes meeting specific frequency band standards. The correlation coefficients between these modes and the original signal are computed, discarding weakly correlated modes before signal reconstruction. Finally, MSPCA further suppresses noise, yielding denoised BHR data. Simulations show that the proposed scheme increases the signal-to-noise ratio by 17.964 dB or higher, surpassing the more established denoising techniques of robust principal component analysis (RPCA), MSPCA, and empirical mode decomposition (EMD), and obtains the most favorable results in terms of the RMSE and MSE metrics. The experimental results demonstrate that the proposed scheme more effectively suppresses vertical and random noise signals in BHR data. Both the numerical simulations and experimental results confirm the effectiveness of this scheme in noise reduction for BHR data.

As an emerging geophysical exploration technology in recent years, airborne electromagnetic exploration has the advantages of adapting to diverse terrains, wide coverage, and providing a large amount of electromagnetic data, and can be applied to the rapid collection of large amounts of data. Scenarios are often used in fields such as deep geological structures, mineral resource exploration, and environmental engineering research. However, traditional airborne electromagnetic data inversion technology usually takes a long time to process a large amount of airborne electromagnetic data, and it is difficult to remove the noise in the later signals. Therefore, this paper proposes a multi-task learning network structure based on Transformer. By constraining the two network branches of imaging and denoising, a sub-network with simultaneous denoising and imaging is established to process aeronautical electromagnetic data. The noise test set is introduced for testing. This model achieved a 582.61% signal-to-noise ratio improvement in smooth Gaussian noise denoising, and a 129.69% and 112.74% signal-to-noise ratio improvement in non-smooth Gaussian noise and random impulse noise denoising, respectively. The method proposed in this article overcomes the shortcomings of traditional inversion imaging such as slow speed and low resolution, and at the same time eliminates the influence of noise in airborne electromagnetic data. This is of great significance for the application of deep learning in the field of geophysical exploration.

The resolving power of metalens telescopes rely on their aperture size. Flat telescopes are advancing with the research on super-resolution confocal metalenses with large aperture. However, the aperture sizes of metalenses are usually bound within hundreds of micrometers due to computational and fabrication challenges, limiting their usage on practical optical devices like telescopes. In this work, we demonstrated a two-step designing method for the design of dual-band far-field super-resolution metalens with aperture sizes from the micro-scale to macro-scale. By utilizing two types of inserted unit cells, the phase profile of a dual-wavelength metalens with a small aperture of 100 μm was constructed. Through numerical simulation, the measured FWHM values of the focal spots of 5.81 μm and 6.81 μm at working wavelengths of 632.8 nm and 1265.6 nm were found to all be slightly smaller than the values of 0.61 λ/NA, demonstrating the super-resolution imaging of the designed metalens. By measuring the optical power ratio of the focal plane and the incident plane, the focusing efficiencies were 76% at 632.8 nm and 64% at 1265.6 nm. Based on the design method for small-aperture metalens, far-field imaging properties through the macro metalens with an aperture of 40 mm were simulated by using the Huygens–Fresnel principle. The simulation results demonstrate confocal far-field imaging behavior at the target wavelengths of 632.8 nm and 1265.6 nm, with a focal length of 200 mm. The design method for dual-band far-field super-resolution metalens with a large aperture opens a door towards the practical applications in the dual-band space telescope system.

The current inverter is the core component of the helicopter transient electromagnetic (HTEM) detection system. It should meet the concerns of low loss, high power, and fast turn-OFF time. This article proposes a new circuit topology based on nine-level inverter technology to overcome the drawbacks of typical PWM (pulse width modulation) inverters, such as switching losses and harmonics. This circuit topology overcomes the shortcomings of the traditional single constant voltage clamp circuit in which the turn-OFF time is not adjustable. Using an inverter with the proposed topology is able to avoid the complex PWM control method and switching loss. In this way, the current rising edge and falling edge of this inverter are also improved effectively. The proposed inverter has adjustable turn-ON-time and turn-OFF time, which is significantly different from the conventional single-clamp inverter. Through subsequent experiments, the inverter proved to have the capability of generating trapezoidal current waveforms. Moreover, by modifying the FPGA (Field Programmable Gate Array) control program, three different turn-OFF times are achieved. The nine-level inverter has a peak current of 1.5 A with an adjustable turn-OFF time from 129 μs to 162 μs. Moreover, the switching frequency of the inverter is reduced from 10 kHz to below 100 Hz. The experimental results further demonstrate that it achieves lower switching losses and more flexible transmission. Our work in this article provides an efficient way to improve the performance of HTEM detection systems.

The predecessor of China Optics was China Optics and Applied Optics Digest, which was founded in 1985. At that time, it was the only retrieval journal in the field of optics in China. At the end of 2008, China Optics and Applied Optics Digest was renamed 《中国光学》的前身是1985年创办的《中国光学与应用光学文摘》，当时是国内光学领域唯一的检索刊物。2008年底《中国光学与应用光学文摘》转型更名为《中国光学与应用光学》期刊，刊载内容突破了文摘的限制，正式成为学术刊物。