Data processing and application of resistivity logging after casing

In the later stages of oilfield development, monitoring remaining oil saturation is of great significance for increasing reserves, boosting production, and controlling water production. Resistivity Logging After Casing (RLAC) can measure the resistivity of the formation outside the casing, and is an electrical logging technique. Its interpretation is simple, its methods are mature, and it has a relatively large radial detection range, giving it distinct advantages over radioactive logging techniques in remaining oil monitoring. However, the original measurement data of RLAC has characteristics such as multiple values, discrete values, and uneven depth intervals, making it difficult to directly collaborate with open-hole well logging data for analysis. To address this issue, this paper proposes a systematic RLAC data processing and interpretation method: first, using the Grubbs test and box plot methods to automatically remove resistivity anomalies, then synthesizing the single resistivity data using the arithmetic mean method, and utilizing the Akima interpolation method to densify the single resistivity data into an equal-depth interval dataset. Furthermore, by combining the open-hole well resistivity logging data, the remaining oil saturation is calculated based on the Indonesian formula, and a waterflooded layer grading evaluation standard is established by introducing a depletion index. Practical applications show that both the Grubbs test and box plot methods can effectively eliminate resistivity measurement anomalies in RLAC. The Akima interpolation method can better retain the original data shape while ensuring the smoothness of the curve. In the study area, the RLAC performs well in measuring medium and low resistivity formations. The Indonesian formula and the waterflooded layer identification standard based on the depletion index are reasonable and reliable for evaluating remaining oil saturation and waterflood levels. The processing results of well G35 are consistent with the actual production situation, verifying the rationality and accuracy of the data processing and interpretation method presented in this paper, and providing reliable technical support for remaining oil saturation monitoring and waterflooded layer evaluation in oilfields.