This design improves imaging quality and reliability in oil-based mud instruments, highlighting anti-interference and signal performance.
With the continuous advancement of oil and gas exploration technologies, the application of oil-based mud electrical imaging instruments has become increasingly widespread in complex drilling environments such as shale gas, high-temperature wells, deep wells, and horizontal wells. Currently, oil-based mud electrical imaging instruments have become indispensable key equipment in logging engineering, and the electrode circuit, as a core component, plays a decisive role in the instrument’s performance and imaging quality. However, existing designs of the electrode circuits in oil-based mud electrical imaging instruments face significant technical challenges, such as low integration, poor anti-interference capabilities, and insufficient signal-to-noise ratios for multi-frequency signal transmission. These issues severely restrict the imaging quality and application range of the instrument. This paper proposes a comprehensive high-integration design theory and architecture for the electrode circuit of oil-based mud electrical imaging instruments. Through the optimization of circuit structures and rational design of key functional modules, efficient integration of the transmission and reception units is achieved. The design primarily focuses on the generation and processing of multi-frequency transmitted signals, the acquisition and conditioning of received signals, and other critical technologies, establishing a systematic theoretical model for the design. To verify the reliability of the design, a specialized testing platform was established, and system performance testing was carried out using high-precision signal analyzers and network analyzers. Experimental results demonstrate that the electrode circuit exhibits excellent measurement performance at both 5.2 MHz and 48.2 MHz working frequencies. This study provides a feasible technical solution for enhancing the performance of oil-based mud electrical imaging instruments.
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Li et al. (2025) studied this question.
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