【摘要】 对于井数少且以地震资料为主的海上油田,虽然已经投入较长时间的开发,但是由于井间和油藏边部等缺少井控部位的认识程度偏低,会严重影响后续开发方案的实施。已有的建模约束方法不能解决模拟过程中面临的边界内部参数控制不到位、单一趋势考虑不全面、多个趋势难以同时整合的问题,在海上油田应用效果较差。针对上述问题,为了准确反映砂体和储层参数在空间的分布,提出了多趋势融合的概率体约束方法。以南海珠江口盆地W油田地质模型建立为例,综合应用地震、测井、地质和开发动态等资料,分别采用块克里金插值和基于位置的加权线性组合方法,整合多个类型和级次的趋势建立了离散变量和连续变量的概率体,并将其作为约束条件应用于沉积相和孔、渗参数的模拟过程。与常规建模约束方法相比,多趋势融合的概率体约束方法克服了边界约束建模的局限性和单一趋势约束建模的不足,达到了对多个趋势同时整合的目的,对落实相带边界和减小参数在井间分布的不确定性效果明显,具有良好的应用前景。更多还原

【Abstract】 The offshore oilfields have been developed for a long time,which have a small number of wells and rich seismic data.However,the implementation of follow-up development plans will be seriously affected because of the less understanding of cross-well area and reservoir edge in lack of well control.The existing modeling constraint method cannot solve problems in the simulation process,such as inadequate control of inner-boundary parameters,incomprehensive considerations on sole trend and difficulties in simultaneously integrating multiple trends.Thus,this method has a poor application effect in offshore oilfields.In order to solve the above problems and accurately reflect the spatial distribution of sand body and reservoir parameters,this study proposes a probability constraint method based on multiple trend integration.Taking the geological modeling of Oilfield W in the South China Sea as a case,and using seismic,logging,geological and development dynamics data,Block Kriging interpolation and position-based weighted linear combination method was adopted to integrate multiple types and levels of trends,so as to establish the probability for discrete and continuous variables.Further,probability was used as a constraint applied in the simulation processes of sedimentary facies,porosity and permeability parameters.Compared with conventional modeling constraint method,the probability constraint method overcomes the limitation of boundary-controlled modeling and the deficiency of singletrend constraint modeling,so as to achieve simultaneous integration of multiple trends.Moreover,this method is most favorable for determination of the facies edge and reduction of uncertainty in cross-well distribution of parameters,showing agood application prospect.更多还原