Human-operated　submersibles　can　guide　visitors　on　explorations　of　the　deep　sea.　Nevertheless,　unknown　factors　that　cause　submersible　failures　may　lead　to　their　vanishing.　Hence,　it　is　crucial　to　develop　models　that　can　forecast　the　whereabouts　of　lost　underwater　vessels.　This　work　focuses　on　the　problem　of　lost　submersible　search,　locating,　and　other　difficulties　encountered　in　deep-sea　situations　where　submersibles　have　power　and　communication　failures.　We　utilize　principles　from　fluid　mechanics　to　create　a　sophisticated　submersible　model　that　predicts　the　position　of　a　submersible.　Taking　into　account　the　decrease　in　buoyancy　in　deep-sea　environments,　we　utilize　ArcGIS　simulation　to　obtain　the　influence　of　various　factors　on　the　movement　of　the　target　underwater　vessel,　resulting　in　precise　location　forecasting.　We　calculate　the　most　efficient　search　area　to　establish　the　locations　along　the　search　path.　By　employing　a　genetic　algorithm,　we　formulate　the　most　efficient　search　trajectory,　progressively　modifying　the　search　area.　Lastly,　we　calculate　the　likelihood　of　locating　the　submersible　based　on　the　passage　of　time　and　the　accumulation　of　search　outcomes.　Essentially,　this　work　utilizes　principles　derived　from　fluid　mechanics　and　geographical　mathematics　to　develop　several　models　that　handle　numerous　issues　that　have　an　impact.　During　the　search　phase,　additional　factors　are　provided　to　ascertain　the　minimum　range.　The　submersible　models　exhibited　in　this　work　undergo　computer　simulation　validation,　showcasing　their　practical　value.　To　a　certain　degree,　they　possess　the　ability　to　anticipate　the　whereabouts　of　submerged　vessels　that　are　lost,　therefore　shortening　the　duration　of　search　and　rescue　operations.