Article

Ning, Y.C. and Ridha, S. and Ilyas, S.U. and Krishna, S. and Dzulkarnain, I. and Abdurrahman, M. (2023) Application of machine learning to determine the shear stress and filtration loss properties of nano-based drilling fluid. Journal of Petroleum Exploration and Production Technology, 13 (4). pp. 1031-1052.

Maldar, N.R. and Yee, N.C. and Oguz, E. and Krishna, S. (2022) Performance investigation of a drag-based hydrokinetic turbine considering the effect of deflector, flow velocity, and blade shape. Ocean Engineering, 266. ISSN 00298018

Krishna, S. and Thonhauser, G. and Kumar, S. and Elmgerbi, A. and Ravi, K. (2022) Ultrasound velocity profiling technique for in-line rheological measurements: A prospective review. Measurement: Journal of the International Measurement Confederation, 205. ISSN 02632241

Abdullah, A.H. and Ridha, S. and Mohshim, D.F. and Yusuf, M. and Kamyab, H. and Krishna, S. and Maoinser, M.A. (2022) A comprehensive review of nanoparticles: Effect on water-based drilling fluids and wellbore stability. Chemosphere, 308. ISSN 00456535

Krishna, S. and Ridha, S. and Campbell, S. and Ilyas, S.U. and Dzulkarnain, I. and Abdurrahman, M. (2021) Experimental evaluation of surge/swab pressure in varying annular eccentricities using non-Newtonian fluid under Couette-Poiseuille flow for drilling applications. Journal of Petroleum Science and Engineering, 206. ISSN 09204105

Krishna, S. and Ridha, S. and Vasant, P. and Ilyas, S.U. and Sophian, A. (2020) Conventional and intelligent models for detection and prediction of fluid loss events during drilling operations: A comprehensive review. Journal of Petroleum Science and Engineering, 195. ISSN 09204105

Krishna, S. and Ridha, S. and Vasant, P. and Ilyas, S.U. and Irawan, S. and Gholami, R. (2020) Explicit flow velocity modelling of yield power-law fluid in concentric annulus to predict surge and swab pressure gradient for petroleum drilling applications. Journal of Petroleum Science and Engineering, 195. ISSN 09204105

Krishna, S. and Ridha, S. and Vasant, P. (2020) Prediction of Bottom-Hole Pressure Differential During Tripping Operations Using Artificial Neural Networks (ANN). Lecture Notes in Networks and Systems, 118. pp. 379-388. ISSN 23673370

Krishna, S. and Ridha, S. and Vasant, P. and Ilyas, S.U. and Ofei, T.N. (2020) Simplified predictive model for downhole pressure surges during tripping operations using power law drilling fluids. Journal of Energy Resources Technology, Transactions of the ASME, 142 (12). ISSN 01950738

Krishna, S. and Nagarajan, T. and Rani, A.M.A. (2011) Review of current development of pneumatic artificial muscle. Journal of Applied Sciences, 11 (10). pp. 1749-1755. ISSN 18125654

Conference or Workshop Item

Ridha, S. and Khanbesh, S. and Arain, A.H. and Yusuf, M. and Krishna, S. (2023) Improved Predictive Model for Surge/Swab Pressure Estimation using a New Simplified (NS) Model. In: UNSPECIFIED.

Krishna, S. and Ridha, S. and Ilyas, S.U. and Campbell, S. and Bhan, U. and Bataee, M. (2021) Application of deep learning technique to predict downhole pressure differential in eccentric annulus of ultra-deep well. In: UNSPECIFIED.

Krishna, S. and Ridha, S. and Vasant, P. and Ilyas, S.U. (2020) New analytical approach for predicting surge/swab pressure gradient using mud clinging effect and frictional pressure losses: For yield power law fluid. In: UNSPECIFIED.

Book

Krishna, S. and Ridha, S. and Vasant, P. (2020) Development of DNN model for predicting surge pressure gradient during tripping operations. IGI Global, pp. 294-315. ISBN 9781799836469; 9781799836452