Kazakhstan journal for oil & gas industry

2707-42262957-806X

KMG Engineering

109025

10.54859/kjogi109025

Research Article

GPU-based parallel simulation of wind-driven sea currents for oil spill forecasting

Kudaikulov

Aziz A.

PhDaziz.kudaikulov@gmail.comhttps://orcid.org/0000-0002-4389-4097Amanzholov

Tannur Ye.

tannur.amanzholov@gmail.comhttps://orcid.org/0000-0001-7386-9717Aliuly

Abdurashid

aliulyabdurashid@gmail.comhttps://orcid.org/0000-0001-6845-6571Seitov

Abzal N.

seitovabzal9@gmail.comhttps://orcid.org/0000-0002-7317-3047Assilbekov

Bakytzhan K.

PhDassilbekov.b@gmail.comhttps://orcid.org/0000-0002-0368-0131Kuldzhabekov

Alibek B.

PhDalibek.kuljabekov@gmail.comhttps://orcid.org/0000-0003-4384-6463Shabilov

Spartak M.

sshabilov@gmail.comhttps://orcid.org/0009-0002-3467-5842Baimbetov

Dinmukhambet B.

PhDd2.baimbetov@yu.edu.kzhttps://orcid.org/0000-0002-4992-0890Syrlybekkyzy

Samal

PhD, Associate Professorsamal.syrlybekkyzy@yuedu.kzhttps://orcid.org/0000-0002-0260-0611Kaltayev

Aidarkhan Zh.

D. Sc. (Physics & Mathematics), Professoraidarkhankaltayev@gmail.comhttps://orcid.org/0000-0003-2180-2785

Satbayev UniversityAl-Farabi Kazakh National UniversityIonosphere InstituteTashenev UniversityYessenov University

30092026

83141152

28072026

09092026

2026

Background: Kazakhstan is one of the largest oil producers in Central Asia, with a significant share of oil and gas projects associated with the Caspian region (primarily, these include the North Caspian Project at Kashagan, the Tengiz oil field, and the port infrastructure of Aktau). Oil spills in marine waters pose a serious ecological threat to the environment, making it essential to develop effective tools for forecasting their spread. Aim: To develop and test parallel algorithms for the simulation of wind-driven sea currents on graphics processing units (GPUs) for oil spill forecasting. Materials and Methods: Three-dimensional hydrodynamic models with parameterized turbulent viscosity were were used. Numerical schemes were implemented in explicit and implicit forms, parallelized along x and y coordinates using the OpenCL library. Computations were performed on the CPU and GPU for both uniform and non-uniform grids. Results: GPU-based computations demonstrated significant acceleration: up to 23 times faster on uniform grids and up to 13 times faster on non-uniform grids. The accuracy computations on a non-uniform grid with 40 nodes was comparable to that of computations on a uniform grid with 500 nodes. Conclusion: Parallel GPU algorithms substantially reduce computation time while maintaining high accuracy in modeling wind-driven currents. This makes them a promising tool for forecasting oil spill dispersion in the Caspian Sea.

GPUOpenCLparallel computingwind velocity fieldsea currents

GPUOpenCLпараллель есептеулержел жылдамдықтарының өрісітеңіз ағыстары

GPUOpenCLпараллельные вычисленияполе скоростей ветраморские течения

trade.gov [Internet]. Energy Information Administration. Oil and Gas – Kazakhstan: Explore oil and gas export opportunities and the regulatory environment in Kazakhstan [cited 2026 June 01]. Available from: www.trade.gov/energy-resource-guide-oil-and-gas-kazakhstan?anchor=content-node-t7-field-lp-region-2-1.

ncoc.kz [Internet]. NCOC. Sustainability report 2022 [cited 2026 June 01]. Available from: www.ncoc.kz/ru/sustainability/2022/reports.

Davies AM. Application of a sigma coordinate sea model to the calculation of wind-induced currents. Continental Shelf Research. 1985;4(4):389–423. doi: 10.1016/0278-4343(85)90002-0.

Elliott AJ. Shear diffusion and the spread of oil in the surface layers of the North Sea. Deutsche Hydrographische Zeitschrift. 1986;39:113–137. doi: 10.1007/BF02408134.

Davies AM, Stephens CV. Comparison of the finite difference and Galerkin methods as applied to the solution of the hydrodynamic equations. Applied Mathematical Modelling. 1983;7(4):226–240. doi: 10.1016/0307-904X(83)90076-8.

Zuur EAH, Dietrich DE. The SOMS model and its application to Lake Neuchatel. Aquatic Sciences. 1990;52(2):115–129.

Korotenko K, Bowman MJ, Dietrich DE. High-Resolution Numerical Model for Predicting the Transport and Dispersal of Oil Spilled in the Black Sea. Terrestrial, Atmospheric and Oceanic Sciences. 2010;21(1):123–136. doi: 10.3319/TAO.2009.04.24.01(IWNOP).

Korotenko K, Bowman MJ, Dietrich DE. Modeling of the circulation and transport of oil spills in the Black Sea. Oceanology. 2003;43(4):367–378.

Ibrayev RA. Model of enclosed and semi enclosed sea hydrodynamics. Russian Journal of Numerical Analysis and Mathematical Modelling. 2001;16(4):291–304.

10.

Ibrayev RA, Ozsoy E, Schrum C, Sur HI. Seasonal variability of the Caspian Sea three dimensional circulation, sea level and air sea interaction. Ocean Science. 2010;6(1):311–329. doi: 10.5194/os-6-311-2010.

11.

Blumberg AF, Mellor GL. A Description of a three dimensional coastal ocean circulation model. Coastal and Estuarine Sciences. 1987;4:1–16. doi: 10.1029/co004p0001.

12.

Mellor GL. On the two components of wind driven ocean surface stress with extension to scalar fluxes. Ocean Dynamics. 2019;69:43–50. doi: 10.1007/s10236-018-1228-7.

13.

Mellor GL. On theories dealing with the interaction of surface waves and ocean circulation. Journal of Geophysical Research: Oceans. 2016;121(7):4474–4486. doi: 10.1002/2016JC011768.

14.

Korotenko K, Osadchiev A, Melnikov V. Mesoscale Eddies in the Black Sea and Their Impact on River Plumes: Numerical Modeling and Satellite Observations. Remote Sensing. 2022;14(17):4149. doi: 10.3390/rs14174149.

15.

Korotenko K, Osadchiev A, Melnikov V. Mesoscale Eddy Chain Structures in the Black Sea and Their Interaction with River Plumes: Numerical Modeling and Satellite Observations. Remote Sensing. 2023;15(6):1606. doi: 10.3390/rs15061606.

16.

khronos.org [Internet]. Khronos Group. OpenCL Homepage [cited 2026 June 01]. Available from: www.khronos.org/opencl/.

17.

GitHub.com [Internet]. GitHub repository. Oil Transport in Caspian Sea [cited 2026 June 01]. Available from: github.com/azizka85/oil_trans_in_caspian_sea.