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    Rock Type Connectivity Estimation Using Percolation Theory

    , Article Mathematical Geosciences ; Vol. 45, issue. 3 , April , 2013 , p. 321-340 ; ISSN: 18748961 Sadeghnejad, S ; Masihi, M ; Pishvaie, M ; King, P. R ; Sharif University of Technology
    Abstract
    Complicated sedimentary processes control the spatial distribution of geological heterogeneities. This serves to make the nature of the fluid flow in the hydrocarbon reservoirs immensely complex. Proper modeling of these heterogeneities and evaluation of their connectivity are crucial and affects all aspects of fluid flow. Since the natural variability of heterogeneity occurs in a myriad of length scales, accurate modeling of the rock type connectivity requires a very fine scheme, which is computationally very expensive. Hence, this makes other alternative methods such as the percolation approach attractive and necessary. The percolation approach considers the hypothesis that a reservoir can... 

    Integrating constrained random waves in endurance time analysis of offshore structures subjected to sea waves

    , Article Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE, 1 July 2012 through 6 July 2012 ; Volume 2 , July , 2012 , Pages 677-684 ; 9780791844892 (ISBN) Matin Nikoo, H ; Estekanchi, H ; Zeinoddini, M ; Golestani, M ; Sharif University of Technology
    2012
    Abstract
    This paper introduces a novel methodology for design and assessment of offshore structures exposed to irregular sea waves. For this, Constrained NewWave (CNW) is integrated with the Endurance Time Analysis (ETA) methodology, which is basically developed for the performance based analysis of onshore structures to earthquake loads. In this approach, the offshore structure is simulated in time-domain under a set of calibrated intensifying wave functions. They are devised to represent a gradually increasing roughness of the sea state by time. A performance index such as base shear, drift or stress in a critical structural members are monitored until they reach to a predefined maximum value. A... 

    Rock type connectivity estimation using percolation theory

    , Article Mathematical Geosciences ; Volume 45, Issue 3 , 2013 , Pages 321-340 ; 18748961 (ISSN) Sadeghnejad, S ; Masihi, M ; Pishvaie, M ; King, P. R ; Sharif University of Technology
    2013
    Abstract
    Complicated sedimentary processes control the spatial distribution of geological heterogeneities. This serves to make the nature of the fluid flow in the hydrocarbon reservoirs immensely complex. Proper modeling of these heterogeneities and evaluation of their connectivity are crucial and affects all aspects of fluid flow. Since the natural variability of heterogeneity occurs in a myriad of length scales, accurate modeling of the rock type connectivity requires a very fine scheme, which is computationally very expensive. Hence, this makes other alternative methods such as the percolation approach attractive and necessary. The percolation approach considers the hypothesis that a reservoir can... 

    A reservoir conductivity evaluation using percolation theory

    , Article Petroleum Science and Technology ; Volume 29, Issue 10 , 2011 , Pages 1041-1053 ; 10916466 (ISSN) Sadeghnejad, S ; Masihi, M ; King, P. R ; Shojaei, A ; Pishvaie, M ; Sharif University of Technology
    Abstract
    Oil reservoirs are very complex with geological heterogeneities that appear on all scales. Proper modeling of the spatial distribution of these heterogeneities is crucial, affecting all aspects of flow and, consequently, the reservoir performance. Reservoir connectivity and conductivity evaluation is of great importance for decision-making on various possible development scenarios including infill drilling projects. This can be addressed by using the percolation theory approach. This statistical approach considers a hypothesis that the reservoir can be split into either permeable (good sands) or impermeable flow units (poor sands) and assumes that the continuity of permeability contrasts... 

    Adaptive neuro-fuzzy algorithm applied to predict and control multi-phase flow rates through wellhead chokes

    , Article Flow Measurement and Instrumentation ; Volume 76 , 2020 Ghorbani, H ; Wood, D. A ; Mohamadian, N ; Rashidi, S ; Davoodi, S ; Soleimanian, A ; Kiani Shahvand, A ; Mehrad, M ; Sharif University of Technology
    Elsevier Ltd  2020
    Abstract
    A Takagi-Sugeno adaptive neuro-fuzzy inference system (TSFIS) model is developed and applied to a dataset of wellhead flow-test data for the Resalat oil field located offshore southern Iran, the objective is to assist in the prediction and control of multi-phase flow rates of oil and gas through the wellhead chokes. For this purpose, 182 test data points (Appendix 1) related to the Resalat field are evaluated. In order to predict production flow rate (QL) expressed as stock-tank barrels per day (STB/D), this dataset includes four selected input variables: upstream pressure (Pwh); wellhead choke sizes (D64); gas to liquid ratio (GLR); and, base solids and water including some water-soluble...