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On the value of 3D seismic amplitude data to reduce uncertainty in the forecast of reservoir production

机译：关于3D地震振幅数据的价值以减少储层产量预测中的不确定性

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Three-dimensional (3D) seismic data are commonly used to identify the size and shape of putative flow barriers in hydrocarbon reservoirs.It is less clear to what extent determining the spatial distribution of engineering properties (e.g.,porosity,permeability,pressures,and fluid saturations) can improve predictions (i.e.,improve accuracy and reduce uncertainty) of hydrocarbon recovery,given the multiple non-linear and often noisy transformations required to make a prediction.Determining the worth of seismic data in predicting dynamic fluid production is one of the goals of this paper. We have approached the problem of assessing uncertainty in production forecasts by constructing a synthetic reservoir model that exhibits much of the geometrical and petrophysical complexity encountered in clastic hydrocarbon reservoirs.This benchmark model was constructed using space-dependent,statistical relationships between petrophysical variables and seismic parameters.We numerically simulated a waterflood in the model to reproduce time-varying reservoir conditions.Subsequently,a rock physics/fluid substitution model that accounts for compaction and pressure was used to calculate elastic parameters.Pre-stack and post-stack 3D seismic amplitude data (i.e.,time-domain amplitude variations of elastic responses) were simulated using local one-dimensional approximations.The seismic data were also contaminated with additive noise to replicate actual data acquisition and processing errors.We then attempted to estimate the original distribution of petrophysical properties and to forecast oil production based on limited and inaccurate spatial knowledge of the reservoir acquired from wells and 3D seismic amplitude data. We compared the multiple realizations of the various predictions against predictions with a reference model.The use of seismic amplitude data to construct static reservoir models affected production performance variables in different ways.For example,seismic amplitude data did not uniformly improve the variability of the predictions of water breakthrough time;other quantities,such as cumulative recovery after the onset of production,did exhibit an uncertainty reduction as did a global measure of recovery.We evaluate how different degrees of spatial correlation strength between seismic and petrophysical parameters may ultimately affect the ensuing uncertainty in production forecasts. Most of the predictions exhibited a bias in that there was a significant deviation between the medians of the realizations and that the value from the reference case.This bias was evidently caused by noise in the various transforms (some of which we introduced deliberately) coupled with nonlinearity.The key nonlinearities seem to be in the numerical simulation itself,specifically in the transformation from porosity to permeability,in the relative permeability relationships,and in the conservation equations themselves.
机译：三维（3D）地震数据通常用于识别油气藏中假定的流动屏障的大小和形状。目前尚不清楚在多大程度上确定工程特性（例如孔隙度，渗透率，压力和流体）的空间分布鉴于进行预测需要多次非线性且通常有噪声的转换，饱和度可以改善烃采收率的预测（即提高准确性并减少不确定性）。确定地震数据在预测动态流体产量中的价值是目标之一本文。我们通过建立一个显示出碎屑油气藏遇到的许多几何和岩石物理复杂性的合成油藏模型来解决评估产量预测不确定性的问题。该基准模型是使用岩石物理参数与地震参数之间的空间相关统计关系构建的我们对模型中的注水进行了数值模拟，以再现随时间变化的储层条件。随后，使用了考虑压实和压力的岩石物理/流体替代模型来计算弹性参数。叠前和叠后3D地震振幅数据（即弹性响应的时域振幅变化）使用局部一维近似进行模拟，地震数据也被附加噪声污染，以复制实际数据采集和处理误差，然后尝试估算岩石物理特性的原始分布并预测根据从井和3D地震振幅数据获得的储层空间知识有限且不准确而进行的石油生产。我们将各种预测与参考模型的预测的多种实现方式进行了比较。使用地震振幅数据构建静态油藏模型会以不同方式影响生产性能变量。例如，地震振幅数据并不能统一提高预测的可变性突破水的时间;其他数量（例如生产开始后的累积采收率）和总体采收率测量方法都表现出不确定性降低。我们评估了地震参数和岩石物理参数之间不同程度的空间相关强度最终可能对随后产生的影响生产预测的不确定性。大多数预测都表现出偏差，因为实现的中位数与参考案例的值之间存在显着偏差，这种偏差显然是由各种变换（我们故意引入其中的一些变换）中的噪声引起的。关键的非线性似乎在于数值模拟本身，特别是从孔隙度到渗透率的转换，相对渗透率关系以及守恒方程本身。

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