首页> 外国专利> CONDITIONING RANDOM SAMPLES OF A SUBTERRANEAN FIELD MODEL TO A NONLINEAR FUNCTION

CONDITIONING RANDOM SAMPLES OF A SUBTERRANEAN FIELD MODEL TO A NONLINEAR FUNCTION

机译:亚场模型对非线性函数的条件随机样本

摘要

A method for performing a field operation in a field includes obtaining subterranean field models that are generated based on measured data of a portion of the field. The subterranean field models include statistically derived data for a remainder portion of the field where the measured data is not available. Using a constraint optimization algorithm, weighting factors are determined that represent contributions of the subterranean field models to a combined model. The weighting factors are determined based on a statistical constraint defined by a statistical distribution of the subterranean field models and based on an optimization constraint such that a difference between a modeled value of the field and a pre-determined target value is less than a pre-determined threshold. The combined model is generated from the subterranean field model based on the weighting factors A field operation is performed based on the combined model.
机译:一种用于在田野中执行田野操作的方法,包括获得基于田野的一部分的测量数据而生成的地下田野模型。地下油田模型包括无法获得测量数据的油田剩余部分的统计数据。使用约束优化算法,确定代表地下场模型对组合模型的贡献的加权因子。加权因子是根据地下田野模型的统计分布所定义的统计约束条件和优化约束条件来确定的,以使田野的建模值与预定目标值之间的差小于预先确定的目标值。确定的阈值。基于加权因子从地下现场模型生成组合模型。基于组合模型执行现场操作。

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