通过先进的套管井地层评价,实现油气增产

Heri Tanjung, Ratna Dewanda, Irzal Irzal, Sakti Parsaulian, Adhitya Pratama Lanadito, E. F. Butarbutar, Herbert Sipahutar, Sofyan Sumarna, Muhammad Aldie Syafaat, A. T. Suherman, Muhammad Subhan, Iwan Abdurrahman, I. K. Barus, Mochamad Riza Zakaria, M. Naiola, Mohammad Wildan Alfian, Danto Prihandono, Rizky Sulaksono, Zeppy Irwanzah Budiarto, Rifky Tri Putra, D. Pramudito, Heri Suryadi, Rakhmadian Abdillah
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引用次数: 0

摘要

淡水环境和高粘土含量在印度尼西亚是相当普遍的。这给油气识别和评价带来了一定的挑战,特别是在已经套管井中。在老生产井中,可能出现的情况,如套管后的流体窜流和环空中被困的油气,增加了套管后分析的复杂性,以了解当前的储层状况。为了提高发现剩余油气潜力的成功率,PERTAMINA使用了脉冲中子测井(PNL)来精确定位射孔的目标层段。自2017年以来,PNL活动已经覆盖了PERTAMINA在印度尼西亚各地开发油田的约160口井。PNL服务提供基于核的统计测量,如sigma、热中子衰变孔隙度(TPHI)和碳氧产率,可以同时评估油气饱和度,而不依赖于水的盐度以及地层和流体的其他电学性质。它还允许从元素光谱数据中计算元素干重,可用于确定岩性,以补充标准裸眼测井数据集。更先进的PNL工具通过提供快中子捕获截面(FNXS)测井的新测量方法进一步提高了标准,该方法即使在致密岩层中也有助于识别天然气。最新一代还具有自补偿算法,可以在多套套管/油管等复杂环境下获得更稳健的TPHI和sigma测井。本文展示了几个利用PNL解释在开发井中发现油气的成功案例。与以前使用旧的和/或不完整的裸眼测井数据集建立的结果相比,PNL还提供了一些元素光谱数据,通过提供准确的岩性和孔隙度分析来防止非经济射孔。该PNL活动还提供了可能被忽视的井眼和储层条件的宝贵见解,如环空油气、低压气带识别和巴氏耳边界效应。当PNL的TPHI值明显低于裸眼测井的中子孔隙度测量值时,就可以定性地识别出低压气层。当砂体夹在含碳页岩或煤层之间时,通常会观察到蝙蝠侠耳效应,从而在一个均匀的砂体中产生连续的油-水-油饱和度剖面,在与蝙蝠侠耳相似的床界处显示出油峰。随着砂层变薄,这两个油峰可能合并成一个高含油饱和度的固体,这可能无法描述砂层的真实石油潜力。
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Fashioning the Increase of Oil and Gas Production through Advanced Cased Hole Formation Evaluation
Freshwater environment and high clay content are quite common in Indonesia. This introduces certain challenge in performing hydrocarbon identification and evaluation especially in already cased wells. In old producer wells, possible conditions such as fluid channeling behind casing and trapped hydrocarbon in annulus add more complexity in performing behind casing analysis to understand current reservoir condition. In order to increase the success in finding remaining hydrocarbon potential, PERTAMINA has deployed pulsed neutron logs (PNL) to accurately pinpoint the targeted interval for perforation. Since 2017, the PNL campaign has covered approximately 160 wells in PERTAMINA's development fields across Indonesia up until now. PNL service offers nuclear-based statistical measurement such as sigma, thermal neutron decay porosity (TPHI), and carbon-oxygen yield that allows simultaneous oil and gas saturation evaluation without any dependence on water salinity and other electrical properties of the formation and fluid. It also allows computation of elemental dry weight from elemental spectroscopy data which can be utilized to determine lithology to complement the standard open-hole logs dataset. The more advanced PNL tool raises the bar even further by offering new measurement of fast neutron capture cross section (FNXS) log which is useful to identify gas even in tight rock formation. The latest generation also features self-compensation algorithm resulting in more robust TPHI and sigma log under complex circumstances such as multi-casing/tubing. This paper showcases several prominent success stories of oil and gas findings identified from PNL interpretation in development wells. There are also several examples of elemental spectroscopy data utilization from PNL to prevent non-economical perforation by means of providing accurate lithology and porosity analysis as compared to previous result built from old and/or incomplete open-hole logs dataset. This PNL campaign has also given valuable insights of borehole and reservoir condition which might have been overlooked such as hydrocarbon in annulus, low pressure gas zone identification and batman's ear boundary effect. Low pressure gas zone may be qualitatively identified whenever TPHI from PNL is noticeably lower than neutron porosity measurement from the open-hole log. Batman's ear effect is usually observed when a body of sand is sandwiched between carbonaceous shales or coal layers resulting successive oil-water-oil saturation profile in one homogenous body of sand, shown as oil peaks at the bed boundaries similar with the appearance of batman's ear. As the sand gets thinner, these two oil peaks might merge into one solid body of high oil saturation which might not depict the true oil potential of the sand.
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