We present a novel approach to correct accessible/fluid-saturated porosity values calculated using mercury injection capillary pressure (MICP) for shale samples. On the basis of recent studies, accessible porosity of shale samples calculated from the MICP test is corrected to consider conformance and grain compressibility. However, we show here that the shale samples experience an additional phenomenon during the MICP test that has not yet been addressed, i.e., compression of inaccessible/unfilled pores. Therefore, we propose a general approach consisting of three distinct corrections to accurately estimate accessible porosity of the shale sample using MICP data: (1) conformance, (2) grain compressibility, and (3) inaccessible pore compressibility. First, we develop a mathematical model to estimate both pore and grain compressibility using MICP data and then calculate accessible porosity using the above-mentioned corrections. In the mathematical formulation, we divide the shale matrix into three constituents: (1) accessible pores, (2) inaccessible pores, and (3) grains. We, then, estimate volume fractions for each stage using MICP test data. Samples from both Barnett and Haynesville shale plays (11 samples for each shale plays) are used to perform our study and validate the hypothesis. Moreover, the impact of newly proposed corrections on petrophysical properties, such as permeability and pore size distribution, is evaluated. Our results suggest that estimated accessible porosity significantly decreases when new corrections are implemented on the MICP test data. Furthermore, the results suggest that inclusion of correction will shift pore size distribution toward smaller pores and can also dramatically reduce permeability estimations down to 2 orders of magnitude smaller than the original values. The outcome of this study can help determine the fraction of accessible porosity for reserve evaluation purposes in shale plays.

中文翻译：

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页岩样品中使用汞注入毛细管压力数据评估可及孔隙度

我们提出了一种纠正页岩样品使用汞注入毛细管压力（MICP）计算得出的可访问/流体饱和孔隙率值的新方法。在最近的研究的基础上，对通过MICP测试计算得出的页岩样品的孔隙率进行了校正，以考虑一致性和颗粒可压缩性。但是，我们在这里表明，在MICP测试期间，页岩样品还会遇到另一种尚未解决的现象，即无法进入的/未充满的孔隙的压缩。因此，我们提出了一种通用方法，该方法由三个不同的校正组成，以使用MICP数据准确估算页岩样品的可测孔隙度：（1）一致性，（2）颗粒可压缩性和（3）不可访问的孔隙可压缩性。第一的，我们开发了一个数学模型，以使用MICP数据估算孔隙和晶粒的可压缩性，然后使用上述校正来计算可达到的孔隙度。在数学公式中，我们将页岩基质分为三部分：（1）可进入的孔隙，（2）不可进入的孔隙，以及（3）颗粒。然后，我们使用MICP测试数据估算每个阶段的体积分数。来自Barnett和Haynesville页岩层的样本（每个页岩层11个样本）用于进行研究并验证假设。此外，评估了新提出的修正对岩石物理性质（如渗透率和孔径分布）的影响。我们的结果表明，当对MICP测试数据进行新的校正时，估计的可测孔隙度显着降低。此外，结果表明，包含校正将使孔径分布朝较小的孔移动，并且还可以将渗透率估计值显着降低至比原始值小2个数量级。这项研究的结果可以帮助确定页岩气储层可评估孔隙度，以进行储层评估。