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储集层含油性、物性是储集层流体性质解释评价的基础,由于含油气性、物性等相关单项资料的局限性,每项资料对解释所做的贡献不同,传统的单一参数已不能满足油气层精细解释评价的需求,将多种资料有效结合、综合应用是进行有效解释评价的基础,数学统计方法成为多参数综合分析必要手段,由此建立了产能指数评价图板。产能指数的确定取决于含油性以及物性数据对该指数的贡献率,即参与该指数计算的各个参数的权重系数。以华北油田霸县凹陷东部文安斜坡区储集层解释评价中的气测全烃、岩石热解含油气总量、定量荧光相当油含量、渗透率和孔隙度5项反映含油性和物性的参数为依据,应用灰色关联分析原理,在分析各个参数关联系数的基础上,得出了产能指数计算的关系式;以该区已试油的8口井18个层录井数据和试油结果为依据,在分别计算出产能指数后,制作产能指数与试油产量交会图板,从中可以看出,产能指数大于0.3为产能区,小于0.3为非产能区。该区两口井的应用表明,预测结果与试油结果相符,避免了常规解释评价中的多解性、差异性、交叉性,提高了储集层解释评价准确性。
Reservoir oil and physical properties are the basis for interpretation and evaluation of fluid properties in reservoirs. Due to the limitations of individual data related to oil and gas properties and physical properties, the contribution of each data to interpretation is different. The traditional single parameter can not satisfy The detailed explanation and evaluation needs of the oil and gas layers, the effective combination of a variety of data, comprehensive application is the basis for effective interpretation and evaluation, mathematical statistics methods become a necessary tool for multi-parameter comprehensive analysis, thus establishing a production capacity evaluation board. The determination of productivity index depends on the contribution of the oiliness and physical data to the index, that is, the weight coefficient of each parameter involved in the calculation of the index. Based on the parameters of total gas measurement, total pyrolysis gas content, quantitative fluorescence equivalent oil content, permeability and porosity in gas reservoirs in Wen’an slope area in the eastern Paxian Sag of Huabei Oilfield, five parameters reflecting oil and physical properties As the basis, using the principle of gray relational analysis, based on the analysis of the correlation coefficient of each parameter, the relationship between the calculation of production capacity index was obtained. Based on the 18 well logging data and oil test results of 8 wells in this area, Basis, after separately calculating the productivity index, making the intersection of production capacity index and test oil production chart, it can be seen that the productivity index is greater than 0.3 for the production area, less than 0.3 for the non-production area. The application of the two wells in this area shows that the prediction results are consistent with the test oil results, which avoids the multiple solutions, differences and crossings in the conventional interpretation and evaluation, and improves the accuracy of reservoir interpretation and evaluation.