Paper
22 August 2011 A new approach for cuttings identification using laser induced breakdown spectroscopy
Zhen-nan Wang, Ye Tian, Ying Li, Rong-er Zheng
Author Affiliations +
Abstract
In the process of oil exploration and development, it becomes difficult to identify the lithology of cuttings due to the small size of cutting particles produced by extensively used Polycrystalline Diamond Compact (PDC) drill bit. Laser Induced Breakdown Spectroscopy (LIBS) is an appealing technique compared with many other conventional analysis methods due to its simple set-up, on-line, real time, stand off and multi-element analytical capabilities. In this paper, a newly developed approach for cuttings identification using laser-induced breakdown spectroscopy was introduced. Principal component analysis (PCA) and partial least squares (PLS) were applied to analyze LIBS spectra of three drill cuttings to perform cuttings identification. With the purpose of reducing workload and improving predictive accuracy, 23 characteristic spectra ranges were extracted as "fingerprints" from each integrated LIBS spectrum. Leave-one-out cross-validation method (LOO-CV) was used to evaluate the predictive capability of this approach. All the LIBS spectra were identified correctly under a lax criterion. The obtained preliminary results demonstrated the potential feasibility of cutting identification using LIBS in combination with chemometric methods.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhen-nan Wang, Ye Tian, Ying Li, and Rong-er Zheng "A new approach for cuttings identification using laser induced breakdown spectroscopy", Proc. SPIE 8192, International Symposium on Photoelectronic Detection and Imaging 2011: Laser Sensing and Imaging; and Biological and Medical Applications of Photonics Sensing and Imaging, 81923Z (22 August 2011); https://doi.org/10.1117/12.901044
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Cited by 2 scholarly publications.
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KEYWORDS
Laser induced breakdown spectroscopy

Laser cutting

Principal component analysis

Chemometrics

Plasma

Diamond

Multi-element lenses

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