Journal
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
Volume 160, Issue -, Pages 433-441Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.petrol.2017.10.048
Keywords
Wavelet transform; Density logging; Mother wavelet; Decomposition level; Thin-layer identification
Categories
Funding
- National Natural Science Foundation of China [41574119, 41504099]
- National Major Oil and Gas Special Fund of China [2017ZX05019005-004]
- Natural Science Foundation of Shandong Province [ZR2015DQ003]
- Special Fund of Central College Basic Research Operating Expenses [15CX06008A, 17CX02070]
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In the late stage of oilfield development, thin reservoirs become particularly important for oil and gas exploration. However, current density logging, as a primary method of reservoir identification, has a lower resolution in identifying thin-layers. In this study, a discrete wavelet transform (DWT) is utilized in density logs to identify thin-layers. By adopting different Daubechies (dbN) wavelets and decomposition levels, we analyze the approximation coefficients (cA) and detailed coefficients (cD) and identify the thin-layer signal from detailed coefficients. And then, we reconstruct a new density curve with enhanced thin-layer signal for identifying the thin layer. Results show that db4 wavelet and 3 level are the optimum mother wavelet and decomposition level for the density logging. Detailed coefficients (cD3) from 3rd level decomposition are highly consistent with the thin-layer information, which is suitable for thin-layer identification. Besides, the reconstructed density curve shows a higher thin-layer resolution. This method is successfully applied in the oilfield, and the thin-layer resolution of density curve is improved from 30 cm to 15 cm in accordance with microspherically focused logging (RXO).
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