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Reservoir simulation models are used to design oil field developments, estimate efficiency of geological and engineering operations and perform prediction calculations of long-term development performances. A method has been developed to adjust the permeability cube values during reservoir model history-matching subject to the corederived dependence between rock petrophysical properties. The method was implemented using an example of the Bobrikovian formation (terrigenous reservoir) deposit of a field in the Solikamskian depression. A statistical analysis of the Bobrikovian formation porosity and permeability properties was conducted following the well logging results interpretation and reservoir modelling data. We analysed differences between the initial permeability obtained after upscaling the geological model and permeability obtained after the reservoir model history-matching. The analysis revealed divergences between the statistical characteristics of the permeability values based on the well logging data interpretation and the reservoir model, as well as substantial differences between the adjusted and initial permeability cubes. It was established that the initial permeability was significantly modified by manual adjustments in the process of history-matching. Extreme permeability values were defined and corrected based on the core-derived petrophysical dependence KPR = f(KP) , subject to ranges of porosity and permeability ratios. By using the modified permeability cube, calculations were performed to reproduce the formation production history. According to the calculation results, we achieved convergence with the actual data, while deviations were in line with the accuracy requirements to the model history-matching. Thus, this method of the permeability cube adjustment following the manual history-matching will save from the gross overestimation or underestimation of permeability in reservoir model cells.
Reservoir simulation models are used to design oil field developments, estimate efficiency of geological and engineering operations and perform prediction calculations of long-term development performances. A method has been developed to adjust the permeability cube values during reservoir model history-matching subject to the corederived dependence between rock petrophysical properties. The method was implemented using an example of the Bobrikovian formation (terrigenous reservoir) deposit of a field in the Solikamskian depression. A statistical analysis of the Bobrikovian formation porosity and permeability properties was conducted following the well logging results interpretation and reservoir modelling data. We analysed differences between the initial permeability obtained after upscaling the geological model and permeability obtained after the reservoir model history-matching. The analysis revealed divergences between the statistical characteristics of the permeability values based on the well logging data interpretation and the reservoir model, as well as substantial differences between the adjusted and initial permeability cubes. It was established that the initial permeability was significantly modified by manual adjustments in the process of history-matching. Extreme permeability values were defined and corrected based on the core-derived petrophysical dependence KPR = f(KP) , subject to ranges of porosity and permeability ratios. By using the modified permeability cube, calculations were performed to reproduce the formation production history. According to the calculation results, we achieved convergence with the actual data, while deviations were in line with the accuracy requirements to the model history-matching. Thus, this method of the permeability cube adjustment following the manual history-matching will save from the gross overestimation or underestimation of permeability in reservoir model cells.
In this paper, we used a self-developed anisotropic cubic core holder to test anisotropic relative permeability by the unsteady-states method, and introduced the anisotropic relative permeability to the traditional numerical simulator. The oil–water two-phase governing equation considering the anisotropic relative permeability is established, and the difference discretization is carried out. We formed a new oil–water two-phase numerical simulation method. It is clear that in a heterogeneous rock with millimeter to centimeter scale laminae, relative permeability is an anisotropic tensor. When the displacement direction is parallel to the bedding, the residual oil saturation is high and the displacement efficiency is low. The greater the angle between the displacement direction and the bedding strike, the lower the residual oil saturation is, the higher the displacement efficiency is, and the relative permeability curve tends towards a rightward shift. The new simulator showed that the anisotropic relative permeability not only affects the breakthrough time and sweep range of water flooding, but also has a significant influence on the overall water cut. The new simulator is validated with the actual oilfield model. It could describe the law of oil–water seepage in an anisotropic reservoir, depict the law of remaining oil distribution of a typical fluvial reservoir, and provide technical support for reasonable injection-production directions.
In the process of waterflooding development, high waterflooding PVs will make the fluid percolation in the reservoir more complicated, resulting in lower efficiency of waterflooding. High waterflooding PVs will affect the relative permeability and change the seepage law of oil–water two-phase flow in a high water-cut period. In this study, we performed high waterflooding PVs relative permeability experiments using nine natural cores. The unsteady measurement method is used to test the relative permeability curve. The results show that: (1) the relative permeability is affected by the waterflooding PVs, the recovery efficiency of 2000 waterflooding PVs is 10.72% higher than that of 50 waterflooding PVs on the core scale; (2) it makes water mobility increase sharply, while oil phase flow capacity remains low and decreases at high water cut stage. A new relative permeability characterization method considering high waterflooding PVs is established, which is applied to the numerical simulator. It shows that the remaining oil saturation of the high-permeability belt is higher than the calculation results of the traditional numerical simulator. It means that the injected water does not diffuse much into the low-permeability zone of the formation. The modified simulator is validated with the actual China offshore oilfield model. The numerical saturation of the key section of the passing well is in good agreement with the actual logging interpretation results, and the water cut curve fits better in the whole area. The modified simulator could predict oil production accurately after high waterflooding PVs treatment.
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