COMPRESSIVE SENSING BASED OPTICAL SPECTROMETER FOR DOWNHOLE FLUID ANALYSIS

Bin Dai, C. M. Jones, Jimmy Price, Darren Gascooke, Anthony Van Zuilekom
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引用次数: 1

Abstract

Downhole fluid analysis has the potential to resolve ambiguity in very complex reservoirs. Downhole fluid spectra contain a wealth of information to fingerprint a fluid and help to assess continuity. Commonly, a narrowband spectrometer with limited number of channels is used to acquire optical spectra of downhole fluid. The spectral resolution of this type of spectrometer is low due to limited number of narrowband channels. In this paper, we demonstrate a new type, compressive sensing (CS) based broadband spectrometer that provides accurate and high-resolution spectral measurement. Several specially designed broadband filters are used to simplify the mechanical, electrical, optical, and computational construction of a spectrometer, therefore provides measurement of fluid spectrum with high signal-to-noise ratio, robustness, and a broader spectral range. The compressive sensing spectrometer relies on reconstruction technique to compute the optical spectrum. Based on a large spectral database, containing more than 10000 spectra of various fluids at different temperature and pressure conditions, which were collected using conventional high resolution spectrometer in a lab, the basis functions of the optical spectra of three types of fluids (water, oil and gas/condensate) can be extracted. The reconstruction algorithm first classifies the fluid into one of three fluid types based on multichannel CS spectrometer measurements, the optical spectrum is reconstructed by using linear combination of the basis functions of corresponding fluid type, with weighting coefficients determined by minimizing the difference between calculated detector responses and measured detector responses across multiple optical channels. The reconstructed data may then be used for purposes such as contamination measurement, fluid property trends for reservoir continuity assessment, and digital sampling. Digital sampling is the process of extrapolating clean fluid properties from formation fluids not physically sampled. The reconstruction spectrum covers wavelengths from 500 nm to 3300 nm, which is a wider spectral region than has historically been accessible to formation testers. The expanded wavelength range allows access of the mid-infrared spectral region for which synthetic drilling-fluid components typically have higher optical absorbance. This reconstruction spectra may allow contamination to be directly determined. This paper will discuss the CS optical spectrometer design, fluid classification and spectral reconstruction algorithm. In addition, the applicability of the technique to fluid continuity assessment, sample contamination assessment and digital sampling will also be discussed.
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基于压缩感知的井下流体分析光谱仪
井下流体分析有可能解决非常复杂油藏的模糊性问题。井下流体光谱包含丰富的信息,可用于识别流体,并有助于评估连续性。通常使用通道数有限的窄带光谱仪来获取井下流体的光谱。由于窄带通道数量有限,这种光谱仪的光谱分辨率较低。在本文中,我们展示了一种新型的基于压缩感知(CS)的宽带光谱仪,它提供了精确和高分辨率的光谱测量。几个专门设计的宽带滤波器用于简化光谱仪的机械、电气、光学和计算结构,因此提供了高信噪比、鲁棒性和更宽的光谱范围的流体光谱测量。压缩感知光谱仪依靠重构技术来计算光谱。利用实验室常规高分辨率光谱仪采集的1万多个不同温度和压力条件下各种流体光谱的大型光谱数据库,可提取3种流体(水、油气/凝析油)光谱的基函数。重建算法首先根据多通道CS光谱仪测量结果将流体分为三种流体类型之一,利用相应流体类型基函数的线性组合重建光谱,通过最小化多个光通道上计算的检测器响应与测量的检测器响应之间的差异来确定加权系数。然后,重建的数据可用于污染测量、储层连续性评估的流体性质趋势和数字采样等目的。数字采样是从未物理采样的地层流体中推断干净流体性质的过程。重建光谱覆盖的波长范围从500 nm到3300 nm,比以往的地层测试人员所能获得的光谱范围更宽。扩大的波长范围允许进入中红外光谱区域,而合成钻井液成分通常具有更高的光学吸光度。这种重建光谱可以直接确定污染。本文将讨论CS光谱仪的设计、流体分类和光谱重建算法。此外,还讨论了该技术在流体连续性评价、样品污染评价和数字采样中的适用性。
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