R. Vahedi; B. Tokhmechi; M. Koneshloo
Abstract
We use a multi-resolution analysis based on a wavelet transform to upscale a 3D fractured reservoir. This paper describes a 3D, single-phase, and black-oil geological model (GM) that is used to simulate naturally-fractured reservoirs. The absolute permeability and porosity of GM is upscaled by all the ...
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We use a multi-resolution analysis based on a wavelet transform to upscale a 3D fractured reservoir. This paper describes a 3D, single-phase, and black-oil geological model (GM) that is used to simulate naturally-fractured reservoirs. The absolute permeability and porosity of GM is upscaled by all the possible combinations of Haar, Bior1.3, and Db4 wavelets in three levels of coarsening. The applied upscaling method creates a non-uniform computational grid, which preserves its resolved structure in the near-well zones as well as in the high-permeability sectors but the data are scaled up in the other regions. To demonstrate the accuracy and efficiency of the method, the values for the oil production rate, mean reservoir pressure, water cut, and total amount of water production are studied, and their mean error is estimated for the upscaled models. Finally, the optimized model is selected based on the computation time and accuracy value.
Mostafa Javid; Behzad Tokhmechi
Abstract
There are two methods for identifying formation interface in oil wells: core analysis, which is a precise approach but costly and time consuming, and well logs analysis, which petrophysists perform, which is subjective and not completely reliable. In this paper, a novel coupled method was proposed to ...
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There are two methods for identifying formation interface in oil wells: core analysis, which is a precise approach but costly and time consuming, and well logs analysis, which petrophysists perform, which is subjective and not completely reliable. In this paper, a novel coupled method was proposed to detect the formation interfaces using GR logs. Second approximation level (a2) of GR log gained from optimum mother wavelet decomposition was used for formation interface detection. Short time Fourier transform (STFT) of a2 was gained since the window band was fixed in the entire of well depths. Inverse STFT of various windows of transformed data was gained, which creates various signals in depth domain. To this end, a novel formulation was developed to obtain modified signal for formation interface detection. The mean of various resulted signals creates a smooth signal the logarithm well of which highlights formation interfaces. Synthetic data were used to test the applicability of proposed algorithm. Accordingly, GR logs corresponding to five different wells located in an oilfield in south of Iran also were used to investigate the accuracy and applicability of the proposed method. Lastly, the validation process took place by comparing the results of core data analysis and the proposed method. Good agreements were obtained between these approaches, demonstrating the applicability of the proposed methodology.
