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We have developed a weighted processing method for wireline microresistivity imaging logging in oil-based mud to estimate not only the low but also the high formation resistivity quantitatively using a support vector regression (SVR) model. Furthermore, the standoff between the logging tool and the formation is also optimized out quite well. The general vertical coupling process is an unweighted method that is only suitable for low-resistivity formation and causes a puzzling reversal phenomenon in high-resistivity formation. Therefore, we have first determined the necessity of introducing a weighted coefficient, and then we developed an improved coupling processing method, i.e., a weighted processing model. We have implemented a sensitivity analysis to determine the change regularity and range of the weighted coefficient. We have developed an SVR model with four main controlling parameters: frequency, real part of measured impedance, imaginary part of measured impedance, and equivalent resistivity to optimize out the weighted coefficient, thus to estimate the formation resistivity accurately. Furthermore, a similar SVR model is also developed to obtain the unknown standoff. We have determined the effectiveness and advantage of the weighted processing in estimating the formation resistivity with two references, respectively, the imaging results in water-based mud and from the general unweighted processing, using three simulated cases. Meanwhile, the optimization of the standoff is also verified.

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Complex characteristics exist in the resistivity response of Gs reservoirs in the central inversion belt of the Xihu Sag, East China Sea Basin. Some drilling wells have confirmed the existence of abnormally low resistivity in gas reservoirs of the area; and the electrical logging response was unable to reflect fluid properties of the reservoir accurately. Therefore, it is necessary to analyze the origin of the low resistivity and determine its controlling factors. Based on experimental data of core analysis and numerical simulations of mud invasion, this study thoroughly explores the origin of low resistivity in the subject gas-bearing reservoir considering both internal and external factors. The results indicated that when there is no or a low degree of mud invasion, the fine lithology, complex pore structure, additional clay mineral conductivity, and high content of pyrite are the main internal factors driving the conditions present in the studied gas reservoir. When mud invasion occurs, the invasion of highly saline mud is the main external cause of low resistivity. The numerical simulation results indicated that a formation with good permeability and high overbalance pressure has a deep invasion depth. The resistivity around the well is obviously reduced after the invasion, and low resistivity would form easily. Combined with actual data of several wells, the main influencing factors of the reservoir’s electrical characteristics were analyzed, and the main controlling factors of low resistivity in the gas reservoirs are given. This study provides valuable support for studying the low-contrast complex reservoir conductivity mechanism. The study also offers novel ideas for accurate calculation of saturation and the meticulous evaluation of reservoir for subsequent studies.