Loading...
Search for: channelized-reservoirs
0.007 seconds

    Real-time oil Reservoir Characterization by Assimilation of Production Data

    , Ph.D. Dissertation Sharif University of Technology Biniaz Delijani, Ebrahim (Author) ; Pishvaie, Mahmoud Reza (Supervisor) ; Bozorgmehry Boozarjomehry, Ramin (Supervisor)
    Abstract
    Hydrocarbon reservoirs development and management is based on their dynamic models. To encounter various types of error during model building, model parameters are adjusted to produce reservoir historical data by assimilation (history matching) of reservoir production or 4D seismic data. Among the existing sequential methods for automatic history matching, ensemble Kalman filter and its variants have displayed promising results. The innovations of this thesis for ensemble Kalman filter (EnKF) are presented into three major orients; these includes adaptive localization/regularization, characterization of original PUNQ test model and characterization of channelized reservoir.
    To mitigate... 

    Intelligent and Sequential Reservoir Model Updating and Uncertainty Assessment during EOR Process

    , Ph.D. Dissertation Sharif University of Technology Jahanbakhshi, Saman (Author) ; Pishvaie, Mahmoud Reza (Supervisor) ; Bozorgmehry Boozarjomehry, Ramin (Supervisor)
    Abstract
    Hydrocarbon reservoir management and development as well as planning of enhanced oil recovery (EOR) processes are based on the reservoir dynamic model. Thus, successful implementation of EOR scenarios greatly depends on the quality of the dynamic model and accuracy of the associated parameters in order to correctly describe fluid flow through porous media. First, a dynamic model is constructed based on the prior knowledge. However, because of the various types of error during model building, the prior model is not so accurate and perfect. Accordingly, new observation data, such as production and 4D seismic data, are utilized to calibrate the prior model and characterize the reservoir under a... 

    Investigating the Effectiveness of Wells and Their Anti-Collision Analysis in a Percolation Reservoir Model

    , M.Sc. Thesis Sharif University of Technology Hajizadeh, Sadegh (Author) ; Masihi, Mohsen (Supervisor) ; Jamshidi, Saeed (Co-Supervisor)
    Abstract
    In drilling the percolation structure reservoirs (such as offshore Channelized reservoirs), one of the most important factors in the effectiveness of wells is drilling permeable areas (Channels), while Channel constraints make it possible for two wells to collide. On the other hand, if the desired reservoir is an offshore reservoir, these restrictions have been increased because usually several wells are drilled near together from one platform. Therefore, proper well collision analysis method is also important in these situations. In this project, anti-collision analysis is performed using the MWD device error model between two or more wells in a static reservoir model with channel... 

    Joint estimation of facies boundaries and petrophysical properties in multi-facies channelized reservoirs through ensemble-based Kalman filter and level set parametrization

    , Article Journal of Petroleum Science and Engineering ; Volume 167 , 2018 , Pages 752-773 ; 09204105 (ISSN) Jahanbakhshi, S ; Pishvaie, M. R ; Boozarjomehry, R. B ; Sharif University of Technology
    Elsevier B.V  2018
    Abstract
    Ensemble-based assimilation methods are the most promising tools for dynamic characterization of reservoir models. However, because of inherent assumption of Gaussianity, these methods are not directly applicable to channelized reservoirs wherein the distribution of petrophysical properties is multimodal. Transformation of facies field to level set functions have been proposed to alleviate the problem of multimodality. Level set representation ensures that the estimated fields are facies realizations as well as no modification of the assimilation method is required. Moreover, due to the complexity of the history matching problem in the channelized reservoirs, most researchers conventionally...