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预测高陡复杂断块岩性油藏产油量的一种新模型 被引量:2

A NEW MODEL FOR PREDICTING PRODUCTION OF HIGH-STEEP COMPLEX FAULT-BLOCK OIL RESERVOIRS
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摘要 现有产量预测方法,尤其是Arps递减方程在国内外油田得到广泛应用,有效指导了油田开发。但所应用油田一般规模较大,地层倾角较小,而且一般都是在高含水—特高含水阶段应用。现有产量预测方法多数基于历史产油量数据的拟合进行预测,产量数据越多,油田规模越大、地质情况越简单,准确率越高。对处于中低含水阶段的高倾角复杂岩性油藏,没有开发指标预测应用实例。从基本渗流理论出发,通过应用二项式公式表征油相相对渗透率随含水饱和度的变化规律,拟合砂岩、砂砾岩储层,达到较好效果,同时将油水相对渗透率融入产油量预测模型,使模型具备严格的渗流理论基础,结合重力校正系数,可以准确预测高倾角复杂岩性油藏产油量。在已开发区块应用情况表明,新方法预测精度在90%以上,能够用于产油预测。 The existing production forecasting methods,especially Arps decline equation,have been widely used in the domestic and abroad oilfields and have effectively guided the oilfield development. However,the applied oilfields are generally characterized by a larger scale,smaller dip angle,and usually adopted in the high watercut-extra high watercut stage. Most of the existing predicting methods are based on the match of the historical oil production data,the more the data are,the larger sizes of the oilfields are,the simpler the geological situation is,the higher the accuracy will be. There is no applied example of the development index prediction for the high-dip-angle complex lithologic oil reservoirs in the middle and low watercut stages. From the viewpoint of the basic seepage theory,by means of applying the binomial formula characterizing Krochange with the water saturation,the sandstones and glutenite reservoirs were matched to achieve much better results,meanwhile the Kroare integrated into the oil production predicting model,thus the model can has the strict theoretical basis,and furthermore combined with the gravity correcting coefficient,the production of the high-dip-angle complex lithologic oil reservoir can by accurately predicted. The applied conditions in the developed blocks show that the predicted precision of the new method ismore than 90%,so it can be used for the oil production prediction.
出处 《大庆石油地质与开发》 CAS CSCD 北大核心 2017年第6期75-79,共5页 Petroleum Geology & Oilfield Development in Daqing
关键词 高倾角复杂岩性油藏 二项式公式 油水相对渗透率 产量预测模型 校正系数 应用价值 high-dip-angle complex lithologic oil reservoir binomial formula oil-water relative permeability production predicting model correcting factor application value
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