The positive amplitude anomalies and base line drifts of self-potential (SP) curves make it difficult to recognize the amplitude anomalies and impossible to carry on the standardized calibration. In this way, it becomes extremely hard to read the amplitude anomalies of self-potential curves, increasing the difficulty in lithology recognition and stratigraphic correlation. What’s more, it is impossible to apply the computer technology to do the batch processing. Aimed at the practical problems, taking advantages of the collected digital logging data, positive self-potential anomaly recognition and transformation models have been established, converting the positive anomalies in the sandstone intervals into negative ones, solving the problem of two types of amplitude anomalies in the same scale range. Self-potential base line drift processing moves the biased base line to the null line step by step, adopting the method of piecewise fitting differential migration. With satisfying results, the conformation, amplitude and jugged degree are accordant with the primary curve, forming the technique of self-potential curve processing, laying foundation for logging translation and geological research.
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