The　study　aimed　to　examine　the　use　of　Geomagnetic　Anomaly　Detection　(GAD)　to　locate　the　buried　ferromagnetic　pipeline　defects　without　exposing　them.　However,　the　accuracy　of　GAD　is　limited　by　the　background　noise.　In　the　present　work,　we　propose　an　approximate　entropy　noise　suppression　(AENS)　method　based　on　Variational　Mode　Decomposition　(VMD)　for　detection　of　pipeline　defects.　The　proposed　method　is　capable　of　reconstructing　the　magnetic　field　signals　and　extracting　weak　anomaly　signals　that　are　submerged　in　the　background　noise,　which　was　employed　to　construct　an　effective　detector　of　anomalous　signals.　The　internal　parameters　of　VMD　were　optimized　by　the　Scale-Space　algorithm,　and　their　anti-noise　performance　was　compared.　The　results　show　that　the　proposed　method　can　remove　the　background　noise　in　high-noise　background　geomagnetic　field　environments.　Experiments　were　carried　out　in　our　laboratory　and　evaluation　results　of　inspection　data　were　analysed;　the　feasibility　of　GAD　is　validated　when　used　in　the　application　to　detection　of　buried　pipeline　defects.