| Nanoparticle applications as beneficial oil and gas drilling fluid additives: A review M Al-Shargabi, S Davoodi, DA Wood, A Al-Musai, VS Rukavishnikov, ... Journal of Molecular Liquids 352, 118725, 2022 | 79 | 2022 |
| Experimental and field applications of nanotechnology for enhanced oil recovery purposes: A review S Davoodi, M Al-Shargabi, DA Wood, VS Rukavishnikov, KM Minaev Fuel 324, 124669, 2022 | 71 | 2022 |
| Carbon dioxide applications for enhanced oil recovery assisted by nanoparticles: Recent developments M Al-Shargabi, S Davoodi, DA Wood, VS Rukavishnikov, KM Minaev ACS omega 7 (12), 9984-9994, 2022 | 71 | 2022 |
| Review of technological progress in carbon dioxide capture, storage, and utilization S Davoodi, M Al-Shargabi, DA Wood, VS Rukavishnikov, KM Minaev Gas Science and Engineering, 205070, 2023 | 44 | 2023 |
| Predicting shear wave velocity from conventional well logs with deep and hybrid machine learning algorithms M Rajabi, O Hazbeh, S Davoodi, DA Wood, PS Tehrani, H Ghorbani, ... Journal of Petroleum Exploration and Production Technology 13 (1), 19-42, 2023 | 34 | 2023 |
| Permeability prediction of heterogeneous carbonate gas condensate reservoirs applying group method of data handling MZ Kamali, S Davoodi, H Ghorbani, DA Wood, N Mohamadian, ... Marine and Petroleum Geology 139, 105597, 2022 | 33 | 2022 |
| Thermally stable and salt-resistant synthetic polymers as drilling fluid additives for deployment in harsh sub-surface conditions: A review S Davoodi, M Al-Shargabi, DA Wood, VS Rukavishnikov, KM Minaev Journal of Molecular Liquids 371, 121117, 2023 | 32 | 2023 |
| A comprehensive review of beneficial applications of viscoelastic surfactants in wellbore hydraulic fracturing fluids S Davoodi, M Al-Shargabi, DA Wood, VS Rukavishnikov Fuel 338, 127228, 2023 | 31 | 2023 |
| Machine-learning predictions of solubility and residual trapping indexes of carbon dioxide from global geological storage sites S Davoodi, HV Thanh, DA Wood, M Mehrad, VS Rukavishnikov, Z Dai Expert Systems with Applications 222, 119796, 2023 | 30 | 2023 |
| Insights into application of acorn shell powder in drilling fluid as environmentally friendly additive: filtration and rheology VRKM S. Davoodi, A. Ramazani S.A. International Journal of Environmental Science and Technology, 2020 | 27* | 2020 |
| Machine-learning models to predict hydrogen uptake of porous carbon materials from influential variables S Davoodi, HV Thanh, DA Wood, M Mehrad, M Al-Shargabi, ... Separation and Purification Technology 316, 123807, 2023 | 23 | 2023 |
| A critical review of self-diverting acid treatments applied to carbonate oil and gas reservoirs M Al-Shargabi, S Davoodi, DA Wood, M Ali, VS Rukavishnikov, ... Petroleum Science 20 (2), 922-950, 2023 | 22 | 2023 |
| Synthetic polymers: A review of applications in drilling fluids S Davoodi, M Al-Shargabi, DA Wood, VS Rukavishnikov, KM Minaev Petroleum Science, 2023 | 19 | 2023 |
| Hybridized machine-learning for prompt prediction of rheology and filtration properties of water-based drilling fluids S Davoodi, M Mehrad, DA Wood, H Ghorbani, VS Rukavishnikov Engineering Applications of Artificial Intelligence 123, 106459, 2023 | 18 | 2023 |
| Combined machine-learning and optimization models for predicting carbon dioxide trapping indexes in deep geological formations S Davoodi, HV Thanh, DA Wood, M Mehrad, VS Rukavishnikov Applied Soft Computing 143, 110408, 2023 | 18 | 2023 |
| Machine learning clustering of reservoir heterogeneity with petrophysical and production data D Konoshonkin, G Shishaev, I Matveev, A Volkova, V Rukavishnikov, ... SPE Europec featured at EAGE Conference and Exhibition?, D011S007R003, 2020 | 13 | 2020 |
| How does the definition of the objective function influence the outcome of history matching? G Eremyan, I Matveev, G Shishaev, V Rukavishnikov, V Demyanov ECMOR XVII 2020 (1), 1-14, 2020 | 13 | 2020 |
| Predicting uniaxial compressive strength from drilling variables aided by hybrid machine learning S Davoodi, M Mehrad, DA Wood, VS Rukavishnikov, M Bajolvand International Journal of Rock Mechanics and Mining Sciences 170, 105546, 2023 | 8 | 2023 |
| Automatic Interpretation of Facies from Wireline Logs by Using Hierarchical Machine Learning Approach DV Egorov, NV Bukhanov, BV Belozerov, VS Rukavishnikov Saint Petersburg 2018 2018 (1), 1-5, 2018 | 8 | 2018 |
| Dynamic cluster analysis for updating simulation model using time-lapse seismic V Rukavishnikov, S Kurelenkov 74th EAGE Conference and Exhibition incorporating EUROPEC 2012, cp-293-00844, 2012 | 8 | 2012 |
Shadfar DavoodiResearch Associate, Ph.D., Tomsk Polytechnic UniversityVerified email at hw.tpu.ru
