【作者】 冯立；

【导师】 贾振岐； 刘合；

【作者基本信息】 大庆石油学院 ， 油气田开发工程， 2008， 博士

【摘要】 油田进入中高含水期后,油水井增产增注的措施潜力井越来越少,增产增注措施的经济效益逐年下降,油田面临着主力层系含水高,产量逐年递减,剩余可采储量少,开采难度大等问题,因此有必要对油田、区块的主要增产增注措施的效果进行分析、预测,以评价主体措施的潜力,优化措施结构,解决措施种类筛选、确定措施量和措施候选井,为油田的增产增注措施工艺设计提供依据,为编制科学合理的油田措施方案提供理论支撑,从而进一步提高措施挖潜的效果。本研究提出了利用动态数据对无分层测试资料和已知分层测试资料两种情况下的地质参数进行校正的方法,将措施层段内的小层地质参数,生产参数加权合并成措施层,将剩余小层地质参数、生产参数加权合并成非措施层,从而将实际的地质模型转化成包含措施层和非措施层的理想地质模型。以建立的理想地质模型为基础,对油井压裂、油井堵水、水井酸化、水井压裂和水井调剖五种主要增产、增注措施,针对单井通过渗流阻力法建立了能够满足采油工程规划需要的多层措施效果预测解析模型,用于单井增产增注措施效果预测与评价;针对区块采用统计分析的方法,根据已措施井的资料,通过分析影响油田区块一类、二类储层油水井增产增注措施效果的因素,建立影响因素样本库,分别利用多元回归方法和人工神经网络方法建立起区块油水井增产措施效果预测模型。评价出不同工艺条件、不同储层类型下的措施效果,并建立起措施效果与相应工艺类型和储层类型的统计关系,进而利用建立的统计关系反过来预测不同条件下的措施效果。最后根据上述两种方法得出的油水井措施效果预测结果,在一定约束条件下,优化措施工作量以及筛选措施候选井,最大限度的提高措施的整体经济效益,建立了控制成本前提下的单井最优规划和控制开发指标前提下的单井最优规划两种措施规划数学模型,将求解措施规划转化为求解有限制条件的全局最优化问题,并利用遗传算法成功地实现了该复杂模型的求解。在上述研究方法的基础上编制了采油工程措施规划计算软件,实现了效果预测的参数预处理(辅助决策)、效果预测及措施规划的一体化和效果预测的实时化、动态化。更多还原

【Abstract】 After high water cut period, potential wells that adopt augmented injection and increase production measures become fewer, and economic benefit declines year by year, oil field confronts many problems such as high water cut of main layers, production rate decreases progressively, remaining oil becomes little, exploitation changes into difficult and so on. It’s necessary for fields to predict the effects of main measures to evaluate their potentials and optimize measures’structure, criteria can be provided for measures’design and theory can be given for reasonable measures’scheme, so the effects of measures can be developed.The research raises a method that correcting geologic parameters with performance data under two situations: layering test data known and layering test data unknown. Measure layer can be incorporated by layers implemented measures with their little layers geology parameters and production parameters weighting, and other layers incorporate to non-measure layer, so the actual geology model can be changed into ideal geology model containing measure layer and non-measure layer.On the basis of the ideal geology model, effects of five kinds of main measures which are oil wells fracturing, water shutoff, water wells fracturing, water wells acidifying and water wells’adjusting sections should be predicted. The analysis model of single well measure effect predicting that can meet the need of petroleum engineering planning is built by means of filtrational resistance. On the basis of data of wells which have been taken measures, factors that influence the effects of measure taken on the wells of no.1 and no.2 reservoirs are analyzed, samples bank is built. And models for predicting the measures’effects are built by means of multiple element linear regression and artificial neural network. With the models effects of measures can be evaluated under different technology and reservoir types conditions, and then the statistics relations can be used to predict measures’effects.With the predicting results gained form the two methods depicted above, measure work load is optimized and candidate wells are selected, so the whole economy beneficial can be raised utmost. Two kinds of models of measure planning are built under cost controlling and development index controlling preconditions, in this way, solving the measure problems is changed into solving the whole optimization with limited conditions which can be solved by way of genetic algorithm.On the basis of research above, software that can be used to calculate measure planning of reservoir engineering is compiled. It can realize the integration of parameters preprocessing, effects predicting and measure planning , effects predicting dynamically and currently is also achieved.更多还原