A　novel　network　with　Wavelet　denoising-GARCHSK　and　Mixed　CoVaR　method　is　proposed　to　construct　full-sample　and　dynamic　networks　for　investigating　the　risk　spillover　effects　across　international　crude　oil　and　Chinese　stock　sectors　before　and　after　the　COVID-19　outbreak.　The　empirical　results　denote　that　the　total　bidirectional　oil-sector　risk　spillover　effects　increase　rapidly　after　the　COVID-19　outbreak.　Interestingly,　sectors　shift　from　net　risk　receivers　to　net　risk　contributors　in　the　oil-sector　risk　transfer　effects　during　the　pandemic　period.　Second,　unlike　the　pre-COVID-19　period,　Shanghai　crude　(SC)　replaces　Brent　as　the　largest　oil　risk　transmitter　to　stocks　during　the　COVID-19　period.　Third,　there　are　notable　sectoral　features　in　the　oil-sector　risk　spillovers,　which　differ　across　different　periods.　After　the　burst,　Energy　has　an　incredibly　weak　connection　with　crude　oil,　while　the　sectors,　which　oil　products　are　input　for,　become　close　with　crude　oil.　Far　more　surprising　is　that　the　petroleum-independent　sectors　have　increasing　closer　risk　transfer　effects　with　crude,　even　becoming　the　largest　risk　contributors　to　oil,　after　that.　Finally,　the　oil-sector　relationships　during　the　same　period　are　time-varying　but　stable.　This　paper　provides　policymakers　and　investors　with　new　method　and　insight　into　the　oil-sector　relationships.