Marine　oil　spills　is　one　of　the　most　serious　sea　pollution　which　has　a　horrible　effect　on　environment,　economy,　and　quality　of　life　for　coastal　inhabitants.　How　to　reduce　the　risk　of　oil　spill　disasters　has　become　one　of　the　principal　problems　faced　with　marine　environment　management.　Oil　spill　observation　and　spill　processes　simulation　are　two　main　parts　for　oil　spill　accident　controlling　and　management.　Traditionally,　the　oil　spill　information　detection　and　spill　simulation　is　disjoined　without　any　feedback.　The　modeling　approach　is　all　conducted　with　fixed　structure　and　static　data　input　while　the　observation　system　is　always　static　with　fixed　monitoring　scheme.　In　such　a　circumstance,　neither　the　observation　system　nor　the　simulation　can　provide　highly　accurate　information.　This　paper　propose　a　new　framework　combining　oil　spill　monitoring　and　simulation　as　a　symbiotic　feedback　control　system　based　on　the　theory　of　Dynamic　Data　Drive　Application　System　(DDDAS),　a　new　paradigm　dynamically　integrated　simulations,　measurements,　and　applications.　The　numerical　oil　spill　model　can　accepts　real　time　data　from　remote　sensing　monitoring　which　assure　modeling　a　more　accurate　and　more　reliable　outcomes.　Multiple　simulations　will　be　executed　with　different　remote　sensing　monitoring　scheme　and　the　feedback　from　simulation　guide　and　determine　how　to　gather　the　data.　For　mathematical　modeling　of　the　DDDAS　based　marine　oil　spill　management　system,　we　built　a　multi-stage　optimization　model.　Such　system　could　promise　more　accurate　prediction　and　more　reliable　outcomes　with　real　time　oil　spill　input,　which　will　improve　modeling　technologies,　advance　prediction　capabilities　of　simulation　systems,　and　enhance　oil　spill　monitoring.