In　the　late　production　stages　of　oil　and　gas　fields,　unheated　oil　gathering　and　transportation　technology　is　widely　used　for　high-water-content　crude　oil,　significantly　reducing　energy　consumption.　However,　the　resulting　lower　pipeline　temperatures　can　lead　to　wax　deposition　issues.　In　this　study,　a　wax　deposition　prediction　model　was　developed　based　on　experimental　and　simulation　data,　and　was　further　optimized　using　the　Levenberg–Marquardt　regression　algorithm.　The　wax　deposition　characteristics　of　two　high-water-content　crude　oils　were　investigated　using　a　flow　loop　apparatus,　and　the　effects　of　oil　temperature,　flow　velocity,　water　content,　and　deposition　time　on　wax　deposition　mass　and　rate　were　analyzed.　CFD　numerical　simulations　were　conducted　to　examine　the　flow　conditions　within　the　pipeline,　revealing　trends　in　the　radial　temperature　gradient　and　wall　shear　stress.　The　study　found　that　wax　appearance　temperature,　molecular　diffusion,　shear　effects,　encapsulation　by　water　molecules,　and　the　thickness　of　the　deposition　layer　all　influenced　wax　deposition　process.　Radial　temperature　gradients　were　found　to　be　most　sensitive　to　oil　temperature,　while　wall　shear　stress　was　primarily　affected　by　viscosity　and　velocity.　Model　validation　demonstrated　high　consistency　between　the　predicted　results　and　experimental　data,　with　average　absolute　errors　of　7.73　%　and　7.61　%,　respectively.　The　relative　errors　between　the　predicted　values　of　the　model　and　the　OLGA　simulation　results　were　within　15　%.　©　2025　Elsevier　Ltd