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首页> 外文期刊>Journal of African Earth Sciences >Estimating density and vertical stress magnitudes using hydrocarbon exploration data in the onshore Northern Niger Delta Basin, Nigeria: Implication for overpressure prediction
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Estimating density and vertical stress magnitudes using hydrocarbon exploration data in the onshore Northern Niger Delta Basin, Nigeria: Implication for overpressure prediction

机译:使用尼日利亚北部尼日尔河三角洲陆上陆上油气勘探数据估算密度和垂直应力大小:对超压预测的意义

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Different techniques for predicting density have been driven by the generally poor resolution with depth, and the lack of good quality density data for quantitative formation evaluation studies. The accuracy of most empirical methods is sometimes affected by the methodological uncertainty, but mainly influenced by the reliability of the input data. The benefits of using different methods in density prediction were demonstrated on the basis of a pore pressure prediction study from the Northern Niger Delta Basin (NNDB). The assessment of three density prediction methods (Wyllie, Gardner and Bellotti & Giacca) shows that the Wyllie's method is the preferred choice for the density prediction in the study area because it has the lowest Least Squares Misfit (LSM) error of 0.0019. The vertical stress gradients (constrained from densities) vary vertically with depth from 19 MPa/km (near the surface) to 25.7 MPa/km (at 4 km depth) and laterally between wells, particularly at the top of high magnitude overpressures (at 3.5 km) from 23.6 MPa/km to 25.0 MPa/km. The differences in the vertical stress gradients are consistent with the density variations observed in the area, and they have implications for the predicted pore pressures. We found there to be an increase in pressure gradient from the top to the bottom of wells, which is consistent with data from 87 wells in the area of study. We have therefore been able to identify three main pressure magnitudes in the area of study: (i) low pressure (close to hydrostatic pressure), (ii) abnormal pressure (a little above hydrostatic) and (iii) high pressure (far above hydrostatic). (C) 2016 Elsevier Ltd. All rights reserved.
机译:总体上较差的深度分辨率以及缺乏用于定量地层评估研究的高质量密度数据,已经推动了不同的密度预测技术。大多数经验方法的准确性有时受方法论不确定性的影响,但主要受输入数据的可靠性影响。在北尼日尔三角洲盆地(NNDB)进行的孔隙压力预测研究的基础上,证明了使用不同方法进行密度预测的好处。对三种密度预测方法(Wyllie,Gardner和Bellotti&Giacca)的评估表明,Wyllie方法是研究区域密度预测的首选,因为它的最小二乘失配(LSM)误差最低,为0.0019。垂直应力梯度(受密度限制)垂直变化,深度从19 MPa / km(靠近表面)到25.7 MPa / km(在4 km深度),并且在井间横向变化,特别是在高幅超压顶部(3.5)从23.6 MPa / km到25.0 MPa / km。垂直应力梯度的差异与在该区域观察到的密度变化一致,并且它们对预测的孔隙压力有影响。我们发现从井的顶部到底部的压力梯度有所增加,这与研究区域中87口井的数据一致。因此,我们已经能够确定研究领域中的三个主要压力幅度:(i)低压(接近静水压力),(ii)异常压力(静水压力略高)和(iii)高压(远高于静水压力) )。 (C)2016 Elsevier Ltd.保留所有权利。

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