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An Improvised Method for Determining Reservoir Rock Porosity Cut-off with Support of Laboratory Mercury Injection Data

机译:一种简易方法,用于确定水库岩孔隙率截止的支持,支持实验室汞注射数据

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Porosity cut-off is a major key parameter in evaluation of reservoir dimensions. Through the use of this parameter formation rocks regarded as ‘reservoir(s)’ are distinguished from ‘non-reservoir’ ones. This makes determination of this parameter to have a direct impact on estimations of reservoir volumes and in turn volumes of hydrocarbon accumulation. Error in the determination may influence commerciality of the hydrocarbon accumulation. Traditionally, determination of porosity cut-off values is made through relationship between rock porosity and permeability. Although some suggested the use of supporting data such as clay volume and porosity types or computational methods such as artificial neural network, this method is often regarded as unsatisfactory due to different intrinsic features between the two. Relationship between rock pore throat size – obtained from mercury injection on core samples – and permeability is on the other hand more direct in nature. This study actually attempts to integrate this more theoretically consistent relationship into the old porosity – permeability relationship. The integration is essentially made through multi-variable regression analysis using data from eight (4 sandstone and 4 limestone) oil and gas fields in Indonesia. Results from the study have shown significant improvement in porosity – permeability relationship resulting in more reliable porosity cut-off estimates. The method, which procedure is presented in this article is hoped to have helped petrophysicists in reducing and overcoming high uncertainties in estimating porosity cut-off.
机译:孔隙率截止是评估储层尺寸的主要关键参数。通过使用这种参数形成岩石被视为'储存器'的岩石与“非水库”的岩石不同。这使得该参数的确定是对储层体积的估计并反过来的碳氢化合物积累的直接影响。确定中的误差可能影响烃积累的商业。传统上,通过岩石孔隙率和渗透性之间的关系来确定孔隙截止值的测定。尽管有些建议使用支持数据,例如粘土体积和孔隙率类型或诸如人工神经网络的计算方法,但由于两者之间的不同内在特征,这种方法通常被视为不令人满意的。岩石咽喉尺寸之间的关系 - 从核心样品上的汞注射获得 - 另一方面,渗透性在自然界中更直接。本研究实际上试图将这种更为一致的关系融为旧孔隙率关系。基本上通过使用印度尼西亚八(4个砂岩和4石石灰石)石油和天然气场的数据的多变量回归分析来进行集成。该研究的结果表明孔隙率关系的显着改善,从而产生更可靠的孔隙率切断估计。本文中介绍的方法,希望有助于岩石物理学家在估算孔隙截止时减少和克服高不确定性。

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