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• Systematic use of two distinct full-scale borehole models (semi-wellbore and vertical wellbore) for seismoelectric logging, providing a geologically realistic simulation environment that bridges the gap between laboratory research and field conditions. • Development and verification of a custom high-sensitivity logging instrument, featuring an integrated EMI-shielded excitation source and a six-channel receiving array with demonstrated 1 µV sensitivity and 120 dB dynamic range. • Application of the Slowness-Time Coherence (STC) algorithm to multi-channel seismoelectric data for robust, objective estimation of compressional, shear, and Stoneley wave velocities, validating traditional slope-based analysis. • Establishment of a quantitative linear relationship between seismoelectric signal amplitude and formation porosity through controlled experiments, advancing beyond qualitative demonstration towards practical formation evaluation. • Effective EMI mitigation via an integrated source-shielding design, enabling the clear detection of weak seismoelectric signals in a high-power excitation environment. The seismoelectric (SE) effect represents a promising route for in-situ formation evaluation. However, its transition from laboratory research to field application has been hindered by two fundamental gaps: the environmental realism gap of scaled models and the signal fidelity gap in acquisition and interpretation. This article introduces an integrated paradigm to bridge these gaps through the development and experimental validation of a high-fidelity SE logging system. Our work presents an integrated framework comprising three key components: (1) A full-scale environmental simulation paradigm, utilizing two distinct full-scale borehole models (a horizontal semi-wellbore and a vertical wellbore) to provide geologically realistic conditions for signal acquisition. (2) A high-fidelity signal acquisition framework, featuring a custom-built instrument suite with integrated EMI-shielded excitation and a sensitive six-channel receiving array, achieving a verified sensitivity of 1 µV and a dynamic range of 120 dB. (3) A quantitative interpretation framework, which applies the slowness-time coherence (STC) algorithm for robust wave velocity estimation and establishes a clear linear relationship between SE signal amplitude and formation porosity. The system unequivocally detected SE signals associated with compressional (P), shear (S), and Stoneley (ST) waves in both models. Our findings, derived from this integrated approach, demonstrate the practicality and potential of SE logging as a promising tool for determining key formation parameters, such as wave velocity and porosity.
Ma et al. (Mon,) studied this question.