Fluid saturation and pressure are two of most important reservoir parameters during oil and gas production scheme adjustment. A method to compute the change of fluid saturation and pressure with multi-parameters regression was presented based on time-lapse seismic inversion data. Rock physical models of unconsolidated sand rock reservoirs were determined according to the real field’s conditions to analyze how seismic attributes change with variation of reservoir parameters. The radial basis function artificial neural network which was trained by this model was used to predict saturation and effective pressure. The predicted results are of high consistency with reservoir numerical simulation, which provide valuable reference for reservoir dynamic monitoring.
With low permeability reservoir into the scale of development, well test gets further attention and application. But in the field application, well test interpretation model, interpretation methods of choice still exist more problems in low permeability and extra-low permeability reservoir. In this paper, with low permeability reservoir build-up well test process, we established mathematical model of the low permeability reservoir build-up well test, and deduce the analytical solution of the mathematical model. Using the deduced theoretical formula, analyze the impact factors. The results of the study show that: well storage coefficient, inner zone permeability and outer zone permeability are sensitive factors; skin coefficient is not sensitive factors.
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