Lithology Logging Recognition Technology Based on GWO-SVM Algorithm

Accurate identification of lithology is the basis and key process fine logging interpretation evaluation. However, reservoirs formed by different sedimentary environments tectonic movements generally have characteristics complex diverse strong heterogeneity, which brings great difficulty to reservoir lithology. This paper proposes an automatic technology for based on GWO-SVM algorithm model. The actually applied, results are compared with support vector machine cross-validation optimization model, PNN (probabilistic neural network) ELM (extreme learning machine) show that recognition model can efficiently solve classification problems in analysis has adaptability higher accuracy.