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辽河油区每年都有相当规模的新增储量和新建产能区块，需要进行储量评价和开发前期方案的编制，进行油藏工程计算和油藏研究。但辽河油区的断块油气田具有含油层系多、断块多、油品多和油藏类型复杂、规模小的特点，使得获取各油藏地层条件下的高压物性资料难度很大，有些单元往往缺少实测的地层条件下的高压物性资料。因而在确定地层原油粘度时没有足够的实测地层条件下高压物性资料，不能满足实际生产需要。依据原油粘度的影响因素，结合地层原油粘度与地面原油物性之间的联系，对辽河油区稀油、稠油两种油品５４ 个已开发单元的原油物性进行分析研究，建立了地层原油粘度与地面原油物性间的相关经验公式。新增储量单元只要获得易取的地面原油物性分析资料，就可利用本区（ 油田） 公式很方便地求出地层原油粘度值。文章还对该方法的准确性进行了误差分析，指出了实际应用过程中以不同油田为单元建立相关经验公式效果会更好，相对误差基本在０．６％ ～２０％ 。图１ 表１ 参４（ 苏继红摘）
Each year, Liaohe Oilfield has a considerable amount of newly-added reserves and new production capacity blocks. Reserves evaluation and pre-development program development are required for reservoir engineering calculation and reservoir research. However, the fault block oil and gas fields in Liaohe Oilfield are characterized by many oil-bearing formations, more fault blocks, more oil products and complex reservoir types and smaller scale, making it difficult to obtain high-pressure physical properties under various reservoir formation conditions. Some units Often the lack of high-pressure physical properties of the measured formation conditions. Therefore, when determining the viscosity of crude oil in the formation, there is not enough high-pressure physical data under the actual measured formation conditions to meet the actual production needs. According to the influencing factors of crude oil viscosity and the relationship between the viscosity of crude oil and the physical properties of the crude oil on the ground, the oil properties of 54 developed units of two kinds of thin oil and heavy oil in Liaohe Oilfield were analyzed and studied. The viscosity of crude oil And the surface of the physical properties of crude oil between the empirical formula. As long as the newly added reserves measure the physical properties of crude oil on the ground, the viscosity of the formation crude oil can be easily calculated by using the formula of this area (oil field). The article also made an error analysis on the accuracy of the method and pointed out that the practical experience of using different oilfields to establish relevant empirical formulas will be better, with a relative error of 0.6% ~ 20%. Figure 1 Table 1 Reference 4 (Su Ji-red abstract)