The factor of safety (FoS) is a measure of the operational safety of a reservoir and is defined as the ratio of the yield strength to the applied effective stress. In the steam assisted gravity drainage (SAGD) process, maintaining the caprock FoS within the prescribed limits during the operation is crucial in adhering to safe operational standards. Deformations associated with the development of the steam chamber in the reservoir affect the FoS of the caprock significantly. With a limited number of well-logs, precise quantification of heterogeneity in petrophysical and geomechanical parameters is a challenge in coupled reservoir-geomechanics modelling; this, along with nonlinearity in the process dynamics, gives rise to non-Gaussian uncertainties in the pore pressure/temperature, which poses severe challenges in reservoir control and optimization. The large scale nature of the reservoir imposes computational complexity in uncertainty quantification through first-principles modelling; hence, a data-driven methodology using the results from first-principles simulations is valuable. In this work, a data-driven polynomial chaos expansion (PCE)-based proxy model is developed from sequentially coupled reservoir-geomechanics simulation. Proper orthogonal decomposition (POD) combined with the PCE yields a proxy model which can provide a quick and accurate estimation of caprock FoS along with quantifying its uncertainty.

安全系数（FoS）是储层操作安全的量度，并定义为屈服强度与施加的有效应力之比。在蒸汽辅助重力排水（SAGD）过程中，在操作过程中将盖层FoS保持在规定的限值内对于遵守安全的操作标准至关重要。与储层中蒸汽室发育相关的变形会显着影响盖岩的FoS。由于测井数量有限，岩石物理和地质力学参数的非均质性的精确定量是储层-地质力学耦合建模中的一个挑战。这与过程动力学的非线性一起，导致孔隙压力/温度的非高斯不确定性，这对储层控制和优化提出了严峻的挑战。通过第一性原理建模，储层的大规模性质给不确定性定量带来了计算上的复杂性。因此，使用第一原理模拟结果的数据驱动方法很有价值。在这项工作中，从顺序耦合的储层-地质力学模拟中开发了基于数据驱动的多项式混沌扩展（PCE）的代理模型。适当的正交分解（POD）与PCE结合可产生代理模型，该模型可以快速准确地估算盖层FoS并量化其不确定性。通过顺序耦合的储层-地质力学模拟，建立了基于数据驱动的多项式混沌扩展（PCE）的代理模型。适当的正交分解（POD）与PCE结合可产生代理模型，该模型可以快速准确地估算盖层FoS并量化其不确定性。通过顺序耦合的储层-地质力学模拟，建立了基于数据驱动的多项式混沌扩展（PCE）的代理模型。适当的正交分解（POD）与PCE结合可产生一个代理模型，该模型可以快速准确地估算盖层FoS并量化其不确定性。