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Subsidence Prediction and Inversion of Subsidence Data

机译:沉降预测和沉降数据反演

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This paper presents a forward model for subsidence predictionrnand an inversion model to calculate the reservoir behaviourrnfrom subsidence data. The forward model employsrncombinations of analytic solutions to the elasticity equations,rnwhich approximate the boundary conditions. There are onlyrnfew free parameters and consequently the calculation times arernlimited. Still, the model is applicable to a multi-layerrnsubsurface with elasticity parameters changing per layer. Therninverse problem is usually ill-conditioned or ill-posed and hasrntherefore been regularized by introducing a priori data aboutrnthe pressure field or by imposing a certain amount ofrnsmoothness. The strength of the regularization parameters arernbest determined using the model resolution of the inversionrnand synthetic cases. These also can be used to optimize thernexperimental design. Inversion of a synthetic case with arn“wrong” forward model shows the importance of obtainingrnreliable subsurface elasticity data. Without such data, thernquality of the inversion can be highly compromised.
机译:本文提出了沉降预测的前向模型和从沉降数据计算储层行为的反演模型。前向模型对弹性方程采用解析解的组合,近似边界条件。只有很少的自由参数,因此计算时间受到限制。该模型仍然适用于弹性参数每层变化的多层地下。逆问题通常是病态的或不适的,因此已通过引入有关压力场的先验数据或施加一定量的平滑度进行了规范化。正则化参数的强度最好使用反演和综合案例的模型分辨率来确定。这些也可以用来优化实验设计。带有“错误”正向模型的合成案例的反演表明获得可靠的地下弹性数据的重要性。没有这些数据,反演的质量可能会受到很大影响。

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